Handbook of Vascular Motion 0128157135, 9780128157138

Table of contents :
Cover
Handbook of Vascular Motion
Copyright
Dedication
List of Contributors
Foreword
Endorsements
Part I: Tools for Quantifying Vascular Motion
1 Introduction
Do Blood Vessels Move?
Absence of Evidence is Not Evidence of Absence
Importance of Vascular Motion
2 Deciding What Vascular Motions You Need
Function and Accommodation
Indication and Patient Population
Cardiac Pulsatility
Respiration and Valsalva
Musculoskeletal Influences
Body Position and Gravity
Don’t Reinvent the Wheel
Animal Studies
Cadaver Studies
Clinical Studies
Outside Partners
Conclusion
Reference
3 Medical Imaging Modalities and Protocols
Medical Imaging Modalities
X-Ray Transmission
Acoustic and Light Reflection
Magnetic Resonance
Radiation Emission
Imaging Based on Target
Imaging Based on Type of Motion
Imaging Based on Timescale and Periodicity
Medical Imaging Protocols
Contrast Injection and Acquisition Timing
Computed Tomography Imaging Parameters
Risk/Benefit
Patient Recruitment and Imaging Challenges
Conclusion
References
4 Geometric Modeling of Vasculature
Imaging Processing Software
Image Format and Viewing
Image Segmentation and Editing
Centerline Extraction
Optimization of Geometric Modeling
Identifying Branch Vessel Ostia
Model Coregistration
Vessel Surface Modeling
Conclusion
References
5 Quantifying Vascular Deformations
Defining and Utilizing Fiducial Markers
Cross-Sectional Deformation
Axial Length Deformation
Bending Deformation
Branch Angle Deformation
Axial Twist Deformation
Surface Curvature Deformation
Conclusion
References
Part II: How the Blood Vessels Move
6 Coronary Arteries and Heart
Coronary ANATOMY
Coronary Artery Cross-Sectional Deformations
Coronary Artery Axial, Bending, Twisting, and Bifurcation Angle Deformations
Cardiac Anatomy
Direct Measurement of Myocardial Motion and Deformation
Myocardial Deformation Estimated From Coronary Artery Motion
Aortic Valve Motion and Deformation
Conclusion
References
7 Arteries of the Head and Neck
Carotid Artery Anatomy
Carotid Artery Motion from Cardiac Pulsatility
Carotid Artery Diameter Changes
Longitudinal Motion of the Carotid Artery
Carotid Artery Motion from Musculoskeletal Movement with and without Medical Devices
Vertebrobasilar Artery Anatomy
Vertebrobasilar Artery Motion from Natural Musculoskeletal Movement
Vertebrobasilar Artery Motion from Manipulation
Vertebrobasilar Artery Motion Due to Medical Devices
Conclusion
References
8 Thoracic Aorta and Supra-Aortic Arch Branches
Anatomy of Thoracic Aorta
Thoracic Aorta
Supra-Aortic Arch Branches
Geometric Analysis Methods
Pathologies of the Thoracic Aorta
Thoracic Aortic Aneurysm
Aortic Dissection
Thoracic Aortic Deformations
Native Thoracic Aortic Deformations
Morphologic Alterations Due to Thoracic Aortic Endograft Placement
Deformation Alterations Due to Thoracic Aortic Endograft Placement
Long-Term Aortic Remodeling
Pathologies of the Aortic Arch and Supra-Aortic Arch Branches
Thoracic Outlet Syndrome
Supra-Aortic Branch Vessel Aneurysm
Aortic Arch Dissection
Supra-Aortic Arch Branch Vessel Deformations
Native Supra-Aortic Arch Branch Vessel Deformations
Musculoskeletal Influences (Thoracic Outlet Syndrome)
Morphologic Alterations Due to Thoracic Aortic Endograft Placement
Conclusion
References
9 Abdominal Aorta and Renovisceral Arteries
Anatomy of Abdominal Aorta
Abdominal Aorta
Renovisceral Arteries
Geometric Analysis Methods
Pathologies of the Abdominal Aorta
Abdominal Aortic Deformations
Cardiac Pulsatility Before and After Endograft Placement
Musculoskeletal Influences
Long-Term Aortic Remodeling after Endograft Placement
Pathologies of the Renovisceral Arteries
Renovisceral Artery Deformations
Native Renovisceral Artery Motion
Renovisceral Artery Motion after Complex Endovascular Abdominal Aortic Repair
Acute and Long-Term Morphologic Alterations Due to Complex Endovascular Abdominal Aortic Repair
Conclusion
References
10 Lower Extremity Arteries
Iliac Artery
Anatomy
Motion From Pulsatility
Motion From Musculoskeletal Movement
Motion From External Influences
Femoropopliteal Artery
Anatomy
Motion from Pulsatility
Native Artery Deformations from Musculoskeletal Movement
Stented Artery Deformations from Musculoskeletal Movement
Cross-Sectional Compression
Tibial Arteries
Anatomy
Tibial Artery Motion
Conclusion
References
11 Veins of the Upper Body
Upper Body Venous Anatomy
Changes in Venous Anatomy With Posture
Respiration and Its Effects on Venous Caliber
Pathological Conditions and Venous Devices
Central Line Movements With Respiration and Postural Change
Deep Versus Superficial Fixation and the Effects of Body Habitus
Complications of Device Placement
Upper Limb Deep Venous Thrombosis
Challenges of Vascular Access for Renal Replacement Therapies
Arteriovenous Fistulae
Arteriovenous Grafts
Central Venous Catheters
Conclusion
References
12 Inferior Vena Cava and Lower Extremity Veins
Veins versus Arteries
Inferior Vena Cava and Renal Veins
Anatomy and Pathology
Inferior Vena Cava Motion with Respiration
Inferior Vena Cava Motion with Valsalva and Other Influences
Nutcracker Syndrome
Iliofemoral Veins
Anatomy and Pathology
Iliac Vein Deformation with Respiration and Valsalva
Iliac Vein Compression from External Structures
Iliofemoral Vein Deformation with Hip Joint Movement
Femoropopliteal Veins
Anatomy and Pathology
Common Femoral Vein Deformations with Posture, Respiration, and Calf Contraction
Femoropopliteal Vein Deformations from Musculoskeletal Influences
Conclusion
References
Part III: Utilizing Vascular Motion Data and Implications
13 Developing Boundary Conditions for Device Design and Durability Evaluation
Choosing Deformation Metrics
Sample Statistics
Defining the Duty Cycle
Diametric Deformation Example
Axial Length Deformation Example
Bending Deformation Example
Walking
Stair-Climbing
Other Deformations and Considerations
Number and Frequency of Cycles
Goldilocks Zone
Conclusion
References
14 Device Design and Computational Simulation
Since the Dawn of Stent Engineering
Rapid Change
The Product Development Process
The Discovery Cycle
Inspiration
Goals and Constraints
Engineering
Fabrication
Design Control and Engineering Specifications
Simulation
Finite Element Analysis
Feasibility Screening
Prototype and Test
Conclusion
References
15 Evaluation of Mechanical Fatigue and Durability
Principles of Fatigue and Durability Assessment
Cardiovascular Implant Analysis and Testing Methods
Case Study 1: Balloon-Expandable Stent
Case Study 2: Nitinol Self-Expanding Stent
Cardiac Pulse Pressures
Musculoskeletal and Respiratory Motions
Case Study 3: Structural Heart Implant Device
Conclusion
References
16 Clinical Implications of Vascular Motion
Clinical Consequences of Coronary Stent Fracture
Clinical Consequences of Lower Extremity Artery Stent Fracture
Clinical Consequences of Early Aortic Endograft Failures
New Endografts: Are We Reliving Past Problems?
Postimplantation Surveillance for Device Failure
Example of Endovascular Aneurysm Repair
Example of Percutaneous Coronary Intervention
Conclusions on Surveillance Testing for Device Failure
Conclusion
References
17 Product Development and Business Implications
The Endurant Evo Experience
So Close
Transition Stent Fractures
Root Cause Investigation
Lessons Learned
The TAG Experience
Need and Expertise Come Together
TAG 1.0 Design
Spine Wire Fractures
Incorrect Early Assumptions
Improved Testing and Design
Coordination of R&D and Sales Rollout
Sales Call
The Responsibility and Burden of R&D
When R&D and Sales Meet
Surprises With Early Endovascular Aortic Repair
Biomechanical Loading Data Is Critical
The Path Was Murky in the Early Days
Lack of Understanding Led to Failures
Knowledge and Devices Are Improving
The Future Is Bright
The Zilver PTX Experience
The Wild West
A Measured Approach to Boundary Conditions
Thorough Mechanical Evaluation
Improving Stent Performance
Expand Success
Stick with What Works
Improvement without Change
Conclusion
References
18 Conclusion and Future Directions
Vasculature Mobility Is Important
Fractures Do Not Equal Failures
Vascular Deformations Beyond Mechanical Durability Testing
Improving Mechanical Durability in a Pinch
Conclusion
References
Acknowledgments
About the Author
Index
Back Cover

Citation preview

HANDBOOK OF VASCULAR MOTION

HANDBOOK OF VASCULAR MOTION Edited by

Christopher P. Cheng Stanford University, Stanford, CA, United States

Academic Press is an imprint of Elsevier 125 London Wall, London EC2Y 5AS, United Kingdom 525 B Street, Suite 1650, San Diego, CA 92101, United States 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom Copyright © 2019 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: http://www.elsevier.com/ permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress ISBN: 978-0-12-815713-8 For Information on all Academic Press publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Mara E. Conner Acquisition Editor: Fiona Geraghty Editorial Project Manager: Leticia M. Lima Production Project Manager: James Selvam Cover Designer: Miles Hitchen Typeset by MPS Limited, Chennai, India

Dedication Those fortunate enough to have met my mother, Ivy, know that she had a thirst for knowledge, a generous soul, and the sharpest of minds. Without her guidance, teaching, and

mentorship, I would never have been become the scientist I am today. So I dedicate this book to my mother, who passed in 2018 while I was writing it. She will forever shine brightly in my heart.

List of Contributors

C. Bonsignore Confluent Medical Technologies, Fremont, CA, United States

J. Metcalf Cook Group, Bloomington, IN, United States

A. Byrne W.L. Gore & Associates, Newark, DE, United States

C. Myers Medtronic, Dublin, Ireland M. Nilson W.L. Gore & Associates, Newark, DE, United States

A. Carr Intensive Care Medicine, Southern District Health Board and University of Otago, Otago & Southland, New Zealand

K. Ouriel Syntactx LLC, New York, NY, United States

J. Carroll Department of Medicine, Division of Cardiology, University of Colorado, Aurora, CO, United States

A.R. Pelton G.RAU Inc., Santa Clara, CA, United States A. Ragheb Cook Group, Bloomington, IN, United States

J. Chen Department of Medicine, Division of Cardiology, University of Colorado, Aurora, CO, United States

B. Roeder Cook Group, Bloomington, IN, United States

Christopher P. Cheng Division of Vascular Surgery, Stanford University, Stanford, CA, United States

S. Rush

G. Suh Division of Vascular Surgery, Stanford University, Stanford, CA, United States

G. Choi Division of Vascular Surgery, Stanford University, Stanford, CA, United States; HeartFlow, Inc., Redwood City, CA, United States T.

Duerig Confluent Medical Fremont, CA, United States

J.

Elkins Serial Executive

Entrepreneur

R. Swift Cook Group, Bloomington, IN, United States B. Ullery Division of Vascular Surgery, Stanford University, Stanford, CA, United States; Providence Heart and Vascular Institute, Portland, OR, United States

Technologies, and

Terumo Corporation, Tokyo, Japan

Corporate

B. Wolf Medtronic, Dublin, Ireland

D. Frakes School of Biological and Health Systems Engineering, School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, AZ, United States

xi

Foreword I was delighted when Chris told me he was going to undertake the task of writing this book. I have often lamented the dearth of information regarding anatomical boundary conditions when compared to the massive amount of published work regarding how one can predict device lifetime and failure modes from those boundary conditions. Yet without question, most device failures can be traced back to the wide variation of anatomical geometries, compliances, and motions that develop as our bodies age. When I was 12 years old, I somehow got into a ridiculous argument with my classmates in Sunday school: If the Earth were to blow up with a huge atomic bomb, would the pieces come back together or would the fragments just keep going into outer space? I was the sole person to take the position that gravity would cause the bits to come back together. This was bitterly disputed for weeks and I was ostracized for my stand. My father worked for Bell Labs at the time and often took me to work on weekends to play on a computer—being 1963, this was really quite special. One weekend I wrote a little BASIC program to print out three pages of random numbers, then the simple text: “The Earth Will Come Back Together.” The next Sunday I plopped the printout in front of my Sunday school colleagues and instantly won the argument. And from then on everybody looked to me for answers to all their scientific questions. Of course the question was absurd, but a computer had sided with me so that was that. Yet we do the same thing today: From a poor foundation of assumptions regarding the human anatomy, we do careful finite element

analyses to predict the stresses and strains in our devices, then we do expensive and time consuming physical tests to determine how long our devices will last and precisely how they will fail. We stare at beautiful color maps of stresses and strains, and because they are calculated to six significant digits, they must be right. We even do “Maximum and Minimum Material Condition” analyses, changing device dimensions by microns to see how this affects the output. But in fact, everything hinges on the original physiological inputs, which are typically very poorly defined. So the clinical trial begins, and fractures are found when and where we do not expect them. Then we go back and figure out what physiological inputs might give rise to these unexpected failures. And to close the loop, we retrospectively examine the films from the patients and indeed find unanticipated anatomic and biomechanical factors. Regretfully, this cycle is altogether too common, and precisely why this book is so important. Indeed, accurately defining the full range of anatomical boundary conditions in elderly, sick populations is both expensive and difficult, but if we expect devices to work in 99% of the population, then we need to understand 99% of the range of boundary conditions. To share another embarrassing anecdote, one of the first devices I worked on was a novel concept for a percutaneously delivered abdominal aortic aneurysm endograft. From the literature and physician discussions, we built glass models representing the diameters and lengths of the aortoiliac bifurcation. We then tested the devices in the glass “Y” models,

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FOREWORD

and found excellent acute sealing. Of course we also made silicone models with what we felt was the right compliance, did durability testing, moved into human trials, but then quickly withdrew from the clinical trial due to acute endoleaks. Only then did we think of using CT scans to 3D print actual diseased human aortoiliac bifurcations we could hold in our hands. With tortuous twists and abrupt turns, they bore no relationship at all to the models we had been using. And of course when we built glass models with the

anatomical extremes existing in our target patient population, our devices failed to seal. While 95% of our effort goes into what we do with the anatomical boundary conditions, 95% of our effort should really go into defining those conditions. This book represents a giant step in that direction. Tom Duerig Founder of Confluent Medical Technologies, Fremont, CA, United States

Endorsements

unaddressed need in an increasingly relevant field of study by focusing on how motion in a wide range of vascular beds impacts the design and performance of medical devices. It is the first comprehensive source to provide a well-organized presentation of the important considerations, including previously unpublished scientific and computational data that underpin the influential effects of vascular motion in humans. Michael D. Dake—Interventional Radiologist, Senior Vice President of University of Arizona Health Sciences & Professor of Medical Imaging, Surgery, and Medicine, University of Arizona, Tucson, AZ, United States.

It’s exciting when a new field opens up—and that’s where we are with vascular motion. Dr. Cheng has provided a clear and highly readable overview of the medical and engineering science surrounding the motion of vessels and the consequences for treatments and technologies. As a bonus, the book is sprinkled with some intriguing hints of new things to come as clinicians, investigators, and inventors pursue this rapidly evolving area. Paul G. Yock—Interventional Cardiologist, Martha Meier Weiland Professor of Medicine, Professor of Bioengineering and Mechanical Engineering (by courtesy), and Director of Byers Center for Biodesign, Stanford University, Stanford, CA, United States.

I very much enjoyed reading this book which provides a wealth of information on the complex and dynamic movement of blood vessels and how this motion can affect the effectiveness and durability of intravascular devices used to treat cardiovascular disease. We have witnessed remarkable advances in the sophistication and effectiveness of implanted medical devices used to treat cardiovascular disease, which is the number one cause of death and disability in the world. However, our understanding of the biomechanical forces acting on these devices as a result of the complex, dynamic movement of blood vessels in everyday life is limited. This is the first book to bring together the large body of scientific information on the movement of blood vessels to show how this motion can impact the durability and function of implanted devices. This book is a must read and reference source for physicians, scientists, biomedical engineers, medical device developers, safety engineers, and regulators who have an interest in improving the treatment of cardiovascular disease. Christopher K. Zarins—Vascular Surgeon, Emeritus Professor of Surgery, Stanford University, Stanford, CA and Cofounder and Senior VP of Medical Affairs, HeartFlow, Inc., Redwood City, CA, United States.

This first of its kind textbook deals with topics that will gain increasing importance as endovascular grafts are increasingly used to treat vascular lesions. These endografts have to dwell and function in a hostile vascular environment governed by some of the forces described in this unique text. Overcoming these forces is a key challenge for the future. This book will help meet that challenge. Frank J. Veith—Vascular Surgeon, Professor of Surgery, New York University, New York, NY, United States and Director of VEITHsymposium.

“Handbook of Vascular Motion” is destined to be a “must-read” for all those interested in the human vascular system. From anatomists to physiologists, vascular clinicians to sports medicine practitioners, biomedical engineers to medical device entrepreneurs, all will find that this special volume provides enlightening evidence of how data-driven insights have dramatically enhanced our understanding of vascular motion and its impact on normal function, development of vascular disease, and design of durable vascular implants. Indeed, Professor Cheng’s superb text tackles a previously

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ENDORSEMENTS

This scientifically well-researched, lavishly illustrated, yet easy to read and entertainingly written, new book is the first comprehensive discussion of all aspects of vascular motion. It fills a giant gap in our understanding of this important topic that until now, sadly, many, if not most of us, did not even realize we lacked; it will become a must read for clinicians, researchers, inventors, and manufacturers interested in vascular disease and its treatment. It not only broadens our knowledge of vascular pathology, pathophysiology, and biomechanics, but adds a new and rational basis and dimension to the development of innovative new preventative and therapeutic medical therapies, vascular surgical and minimally invasive procedures, and implants for the treatment of all types of vascular diseases. Thomas A. Sos—Interventional Radiologist, Professor of Radiology, Weill Cornell Medical College, Cornell University, New York, NY, United States.

This book is long overdue. As a vascular surgeon, I have seen first-hand the incredibly dynamic nature of the vascular system. To date, there has not been a good repository of the collective knowledge on this topic. How can we optimally design modern devices and perform surgery on patients without knowing how their blood vessels move? The answer is we can’t. This book puts us on the right path. Benjamin W Starnes—Vascular Surgeon, Alexander W. Clowes Endowed Chair in Vascular Surgery, Professor and Chief of Division of Vascular Surgery, Vice Chair of Department of Surgery, University of Washington, Seattle, WA, United States.

C H A P T E R

1

Introduction Christopher P. Cheng Division of Vascular Surgery, Stanford University, Stanford, CA, United States

DO BLOOD VESSELS MOVE?

upcoming clinical trial and have every reason to believe that we are on to something big. If the results in the superficial femoral artery (SFA) look anywhere near as good as what we are seeing in the coronaries, this could be a game changer for the industry and the treatment of peripheral vascular disease. Today we’d like to briefly review our preclinical benchtop, animal, and biocompatibility work on the product and then launch into a deeper discussion about what to expect from the trial. This is where your expertise is invaluable.

The following scenes are based on real events . . . When: Sometime in 2000. Where: In a large, upscale conference room at a prestigious US university medical school. Who: Clinical specialists from a multinational, publicly traded medical device company and 15 of the world’s most prominent vascular surgeons, interventional radiologists, and interventional cardiologists. What: Meeting in preparation to launch a clinical trial for femoral artery stents. Why: The medical device company wanted to make sure they knew what to expect from the clinical trial before launching the resource-intensive study. Mood: Businesslike, but light-hearted with positive excitement.

Two hours of discussion about technical data and expectation of clinical outcomes followed . . . Company Clinical Specialist: Thank you for that fruitful discussion! We are encouraged with your optimism for this new product. One last question here from a couple of our engineers back home. They suspect that there might be some motions in the superficial femoral artery based on some anecdotal observations in the cath lab. They are concerned that the movements would impact the mechanical durability of the stent. Do you think this is anything to worry about? Prominent Physician #1: Hmmm, I don’t think I’ve seen any evidence to support that concern. So no, I don’t think so. What would even cause the motion? The superficial femoral artery should be pretty tightly constrained in the adductor canal, so I would not expect it to move. Prominent Physician #2: The SFA should not experience any motion. The superficial femoral artery and vein are packed in the adductor canal between the vastus

Company Clinical Specialist: Thank you all for taking time out of your very busy schedules to join us today. We are truly appreciative to those of you who have signed on as investigators and advisors to the trial. As you know, we have been very busy preparing for this

Handbook of Vascular Motion DOI: https://doi.org/10.1016/B978-0-12-815713-8.00001-2

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© 2019 Elsevier Inc. All rights reserved.

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1. INTRODUCTION

medialis, adductor longus, adductor magnus, and sartorius muscles. Perhaps I’d be more concerned if we were stenting at the hip or crossing the knee, but the SFA should stay straight and stable. Prominent Physician #3: Absolutely. No question. The SFA is right in the middle of the thigh. Even during hip and knee flexion and extension, the SFA is nowhere near the joints, so it should be rock solid. Prominent Physicians #4 15: Yes, agreed. The SFA definitely does not move.

Approximately 2 years later . . . When: Sometime in 2002. Where: In a large, upscale conference room at a prestigious East Coast university medical school. Who: Executives, design engineers, testing engineers, quality engineers, regulatory affairs, preclinical scientists, and clinical specialists from a multinational, publicly traded medical device company along with the same 15 prominent vascular surgeons, interventional radiologists, and interventional cardiologists. What: Meeting to discuss the 1-year results from the clinical trial for femoral artery stents. Why: The femoral artery stents were fracturing at an alarming rate and nobody knew why. Mood: Businesslike, with serious concentration and a little grim. Company Executive: Thank you for accommodating this meeting on such short notice. We know you are all busy. I personally wanted to attend this meeting because the outcome of this clinical trial is very important to our company, and most of all, the safety of the patients involved. We want to make sure we are doing everything in our power to protect the patients and to understand whether the stent fractures are of any clinical concern. Company Regulatory Affairs: To be clear, the majority of patients with stent fracture have not

experienced clinical sequelae. While some have experienced lumen narrowing and reocclusion, we have not determined if this was caused by stent fracture and have not found a statistically significant correlation. Prominent Physician #1: Okay, but you’re at only 1 year. If there are clinical sequelae at this point, then you can be sure more will pop up at 2, 3, 5 years. We see clinical durability issues 5 years after open surgery all the time. Prominent Physician #2: Yeah, and what’s going to happen when we try to treat patients with more severe disease? The parameters of this trial were relatively constrained. In the real world, as the product is pushed to tougher cases, will the fracture issue get worse? Company Clinical Specialist: That’s a good point. We wanted to discuss the more real-world use cases and get your input on whether we should limit the treatment population further. Company Regulatory Affairs: Wait, hold on. We shouldn’t restrict the patients we can treat and help clinically without first understanding the underlying issue. Do we think the stent fractures have to do with vessel deformations? Company Testing Engineer: We tested the mechanical durability of the product per the FDA guidance documents based on scientific literature data on radial pulsatility. In fact, we actually performed extra conservative tests where we took worst case deformations. We did not observe any fractures on the benchtop or predict any in the computer simulations. Are there nonpulsatile deformations in the SFA? Prominent Physician #1: Hmmm, I don’t think I’ve seen any evidence to support that the artery doesn’t move. So yes, it seems that might be the case. The superficial femoral artery is in the leg, and the leg moves with every step you take, so the SFA probably moves along with it. Prominent Physician #2: The SFA definitely experiences motion. The superficial femoral artery and vein are packed in the adductor canal between the vastus medialis, adductor longus, adductor magnus, and sartorius muscles. Since all those muscles contract with walking, the SFA will experience dramatic deformation. Prominent Physician #3: Absolutely. No question. The femoral artery is incredibly dynamic with leg motion, as proven in this trial. Clearly, the stents would not be fracturing at this rate if the SFA wasn’t moving. Prominent Physicians #4 15: Yes, agreed. The SFA definitely moves.

I. TOOLS FOR QUANTIFYING VASCULAR MOTION

ABSENCE OF EVIDENCE IS NOT EVIDENCE OF ABSENCE

ABSENCE OF EVIDENCE IS NOT EVIDENCE OF ABSENCE The preceding fictional conversations are shockingly close to what actually happened in the early 2000s. Commercial peripheral vascular stenting was still in its relative infancy, having been around for less than a decade, and the products on the market were the so-called “first-generation” peripheral stents. At that time, vascular motion was mainly considered in the context of radial deformation from cardiac pulsatility, so device engineers, clinicians, and regulators primarily focused on that mode of vascular motion when designing, testing, using, and regulating vascular implants. It is also notable that when there is a scarcity of objective data, expert opinions not only carry more relative weight but unfortunately are also much more prone to error. Beware the lemming effect. When data is scarce, and opinions reign supreme, experts will tend to agree with other experts.

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It took about a decade of using these peripheral vascular stents commercially before stent fracture was brought to light and considered to be a serious clinical concern. Some initially argued that as stents were being distributed and used more widely, they were being implanted in increasingly aggressive ways, thus explaining the suddenly-noticed alarming fracture rate. While this could have been a contributing factor, upon retrospective analysis it was discovered that stent fractures had been happening all along, unnoticed simply because we were not looking for them. It was not until post-stenting follow-up imaging became more common that fractures were detected in significant numbers. As anyone who has looked for in vivo stent fractures can attest, many of them are surprisingly elusive without some kind of perturbation (Fig. 1.1).

FIGURE 1.1 While the leg is straight, the fluoroscopic image only shows a subtle kink feature (white arrow) at the stent fracture (left). When the leg is bent, the kink is much more prominent, along with two additional kink locations (right). Straight and Bent leg, courtesy: Craig Bonsignore.

I. TOOLS FOR QUANTIFYING VASCULAR MOTION

6

1. INTRODUCTION

IMPORTANCE OF VASCULAR MOTION When evaluating the mechanical durability of medical devices, there are three main efforts: (1) quantifying anatomic geometry, physiologic deformations, and number of cycles; (2) quantifying stresses and strains of the medical device based on these deformations; and (3) interpreting fatigue performance based on material properties, stresses and strains, and number of cycles. While a lot of attention has been paid to steps 2 and 3, step 1 has historically been ignored or handled in an ad hoc manner. We can only speculate the reasons for this, but they are probably related to recognition, scientific depth versus breadth, ambiguity of the problem, and resource constraints. When considering medical device development, the highest profile role is probably invention and design. Would a scientist rather be recognized as the inventor of a device that helps and saves thousands of lives, or the person who provides the boundary conditions so that the designer can invent a more durable device? Probably the former. Talented engineers and scientists tend to seek complex problems they can attack deeply. Would they rather become well-respected experts of materials science, or spend twice as much time learning the lingo of mechanical engineering and medicine just so they can describe how blood vessels change shape? Probably the former. Driven professionals like to know that they have accomplished something after a lot of effort. Would they rather know the parameters of a problem where the solution can be validated and improvement can be quantified, or spend time on a nebulous problem that may not even improve the final product? Probably the former. Would a company prefer to invest resources on producing more products that can bring in more sales, or spend valuable time and resources finding a solution for an ill-defined problem that may not increase revenue? Definitely the former.

All of this leads to a field that is underresourced, under-appreciated, and underunderstood. Our knowledge of the field of vascular motion is as clumsy as the word “under-understood.” Thus this book focuses on step 1. Descriptions of vascular motions are needed to test the mechanical durability of medical devices and to understand the mechanical interactions between devices and the vasculature. Improved understanding of vascular motion provides ways to evaluate biomechanical and physiologic viability, guide regulation, and predict the clinical longevity of cardiovascular devices. Quantification of vascular motions is also needed to conceptualize more mechanically harmonious and durable designs, which can fundamentally change what types of devices are developed to improve patient care. For example, a whole host of “second generation” stents and interventional techniques were developed for the superficial femoral artery after the discovery of stent fractures and vascular motions were carefully quantified. Finally, the dynamic behavior of blood vessels goes beyond medical devices. Measurement of vascular motion can be a critical diagnostic tool. Vessel elasticity, for example, has been shown to correlate with cardiovascular health. These indicators may be used not only for monitoring and assessing risk but may also be utilized to help develop pharmaceutical or genetic therapies. While physicians and scientists have known since the beginning of medicine that muscles and bones move with body motion, the vascular system has mainly been studied in the context of how blood moves through the blood vessels and how disease develops. The work summarized in this book focuses on how the tubes themselves move. This book is composed of three sections, covering (1) methods by which to quantify vascular motions; (2) a summary of the motions of the most important vascular beds; and (3) implications of these blood vessel motions on device design, durability evaluation, clinical care, and business.

I. TOOLS FOR QUANTIFYING VASCULAR MOTION

C H A P T E R

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Deciding What Vascular Motions You Need Christopher P. Cheng Division of Vascular Surgery, Stanford University, Stanford, CA, United States

Making an incorrect assumption about what is required can be costly. The most critical step of determining the appropriate mechanical durability boundary conditions for your cardiovascular device is deciding what boundary conditions are appropriate. Sounds easy enough, but it turns out doing this step correctly is often elusive. Choosing inappropriate boundary conditions can be extremely costly down the road. For example, a device fracturing at a high rate in a clinical trial could jeopardize the commercialization of a product. Or, if the chosen boundary conditions are too rigorous, mechanical testing may yield false negative results, which could equally damage a development program. This chapter follows a recipe of how to determine what boundary conditions are needed for a product, and then provides some options of how to obtain them.

long term. As an analogy, the primary function of airplanes is to fly and transport people and things quickly. While taking off, landing, and staying intact during operation in a variety of weather conditions are not the plane’s primary function, these features are absolutely necessary to accommodate for the primary function of flying. The act of flying requires features that control thrust, lift, brakes, steering, and navigation, but the wings must also be durable and resilient, and the landing gear must work (Fig. 2.1). For a cardiovascular device, one must consider the primary function as well as the accommodation of concomitant anatomic and physiologic challenges in parallel. Take the example of a typical arterial stent. Arterial stents implanted for occlusive disease are primarily used to combat radial recoil after expansion of the flow lumen with balloon angioplasty. This means that the stent needs to supply a resistance to radial compression without itself substantially compromising the flow lumen area. This is exactly why stent manufacturers take great pains to produce stents with structures that provide high radial resistive force but are also thin and do not take up a lot of luminal cross-sectional area.

FUNCTION AND ACCOMMODATION A cardiovascular implant typically has a primary function, but it also must possess other features that allow it to function over the

Handbook of Vascular Motion DOI: https://doi.org/10.1016/B978-0-12-815713-8.00002-4

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© 2019 Elsevier Inc. All rights reserved.

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FIGURE 2.1 Landing without landing gear may negatively affect the durability of the plane and decrease its effectiveness in the future. From https://iainhall.wordpress.com/2009/09/15/i-belive-that-this-is-an-example-of-a-good-landing/.

FIGURE 2.2 Balloon-expandable stent with axial bridges (circled) to enable ease of manufacturing and consistent delivery. Adapted from https://commons.wikimedia. org/wiki/File:Kovovej.png, Mick Hensman.

While arterial stents primarily need to resist radial compression once they are in place, they first need to be deployed accurately into the diseased artery via a low-profile, minimally invasive catheter. For traditional pin-and-pull delivery systems, a stent with high longitudinal stiffness is easier to deliver. Stents often achieve a certain amount of longitudinal stiffness from axial bridges so that they can have predictable lengths during delivery (Fig. 2.2). These bridges also aid in the manufacturing of the device by enabling easy loading onto balloon catheters or into delivery sheaths and, in fact, enhance in vivo stability by preventing

FIGURE 2.3 Short disconnected segments can tilt and become malapposed to the vessel wall (left) while segments connected by axial bridges (in red) prevent tilting and keep the stent securely apposed to the wall (right).

stent tilting and ensuring good wall apposition (Fig. 2.3). Mechanical durability issues come into play when the features that help accommodate one set of requirements come into conflict with another set of requirements. For example, while axial bridges help with manufacturability, delivery, and in vivo stability of the stent, they may also negatively affect the mechanical durability of the stent and the tissue response of the contacting artery (Fig. 2.4). Furthermore, the axial bridges provide stiffness in the bending and twisting directions, which further complicates the mechanical compatibility of the stent with the vessel environment.

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INDICATION AND PATIENT POPULATION

FIGURE 2.4 While the axial stiffness of a stent can assist delivery and in vivo stability, it can add fatiguesensitive features (black circles) and may cause tissue irritation at the ends of the stent (red arrows). Adapted from https://www.flickr.com/photos/serviermedicalart/10084870576.

The next few sections will focus on how to identify the types of blood vessel motion that interact mechanically with a cardiovascular implant. With knowledge about these motions, we may then consider how a medical device can accommodate them.

INDICATION AND PATIENT POPULATION Let us return to the airplane analogy. While most of the time planes fly in relatively smooth, nonturbulent conditions, a portion of their time is spent taking off, landing, navigating through storms, and performing emergency maneuvers. Furthermore, a commercial

FIGURE 2.5

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airline Boeing 777 will have an entirely different set of specifications compared to a fighter jet or a stealth bomber or a Cessna 4-seater. Similarly, while many people who receive medical devices spend most of the day either lying down sleeping or sitting in a chair, some will want to climb Everest or do triathlons. So the first step is to identify the indication for the device. Is the device indicated for very sick elderly patients with limited mobility, or in children with a treatable congenital heart defect who are otherwise healthy? Not only does this “indication” drive the design requirements for the device, but it also sets the mechanical durability testing standards for regulatory submission. While there are relatively defined standards for wind tunnel functionality and conditions with which to test planes in them, mechanical durability standards for medical devices are largely selfdefined and justified based on indication. When it comes to cardiovascular implants, most of the regulatory documents are “Guidance” documents that provide general advice, rather than “Standards” documents, which give defined recipes. There is so much innovation with new medical devices for new indications, and the human body is so complex and variable, that one set of standards cannot be concretely defined (Fig. 2.5). With the information of “who” identified, now the “what” can be considered. Anticipating all the motions that may affect a cardiovascular

What would happen if we tried to define mechanical durability standards for cardiovascular medical devices.

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device is impossible, but it is worth spending some time on the general categories of vessel motion drivers.

CARDIAC PULSATILITY Cardiac pulsatility most simply manifests in an artery as a radial expansion during systole and radial narrowing during diastole for every heartbeat. While systole and diastole occur technically during the contraction and relaxation phases of the left ventricle, respectively, radial expansion and narrowing may occur at slightly different times depending on the location in the body. For example, while the thoracic aorta experiences systole and diastole nearly exactly in phase with the heart due to its proximity, it takes a fraction of a second for the same pressure wave to reach the legs (Fig. 2.6). To make things more complicated, due to vessel branching and abrupt changes in vessel

compliance, reflected pressure waves can superpose onto the incoming waves, altering the shape of pressure waveforms depending on vascular stiffness and location in the body. Note that the coronary arteries are a special case in regard to radial deformation since they are embedded on the surface of the myocardium. Because they are compressed by the contraction of the myocardium during systole, they actually experience a “double pulse,” where there are two peaks of blood flow and radius. There is one during systole with the peak blood pressure, and another one during diastole when the myocardium relaxes and allows the caliber of the coronary arteries to increase (Fig. 2.7).

FIGURE 2.6

The thoracic aorta (middle graph) experiences radial deformation nearly exactly in phase with systole and diastole of the heart (top graph) due to its proximity, but it takes a fraction of a second for the pressure wave and commensurate deformations to reach the legs (bottom graph). Adapted from https://en.m.wikipedia.org/ wiki/File:Arterial_system.svg.

FIGURE 2.7 The left coronary artery (and other coronary arteries) experiences two pulses in blood flow and radius during the cardiac cycle: the first during the high pressure pulse of systole, and the second during diastole when the myocardium relaxes and allows the coronary arteries to expand.

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CARDIAC PULSATILITY

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FIGURE 2.8 The blood pressure pulsatility of the large arteries is damped by the compliance of the elastic arteries and the resistance of the arterioles such that the capillaries and veins experience essentially no cardiac pulsatility. From https://commons.wikimedia.org/wiki/File:2109_Systemic_Blood_Pressure.jpg.

Larger arteries and those closer to the heart tend to experience greater radial pulsatility than small arteries farther away from the heart because the elasticity of arteries tends to decrease distally. For example, the aorta generally experiences greater radial expansion/ contraction than do the tertiary arteries in the hands and feet. By the time blood has passed the elastic large arteries and high-resistance arterioles, and enters the capillary and venous circulations, cardiac pulsatility has all but disappeared (Fig. 2.8). In certain circumstances, cardiac-driven pulsatility can manifest in other directions, such as axial length change, bending, or twist. For example, in the case of a highly curved femoral artery at the adductor hiatus,

FIGURE 2.9 A curved femoral artery at diastole (left) is subject to increased bending at systole (right). The red lines outline the femoral artery, and the green arrow shows the direction of blood flow.

the high pressure pulse of systole preferentially pushes against the wall of the outer curve and causes the artery to bend further (Fig. 2.9).

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RESPIRATION AND VALSALVA Respiration can affect the motion of blood vessels in two general ways. The first is through the motion of respiration itself, namely, the expansion and collapse of the chest cavity. During inspiration, the diaphragm and intercostal muscles contract, flattening and lowering the diaphragm while pulling the ribcage upward and outward, respectively (Fig. 2.10). This combination of motions expands the chest cavity, decreasing intrathoracic pressure and forcing air into the lungs. During the “passive” process of expiration, the diaphragm and intercostal muscles relax, allowing the elastic lungs to recoil inward,

making the diaphragm curve upward and the ribcage move downward and inward. This process increases intrathoracic pressure, forcing air out of the lungs and decreasing the volume of the chest cavity. As the thoracic cavity expands during inhalation, the abdominal cavity is compressed downward from the descending diaphragm. This means that the abdominal organs, and any blood vessels in contact with those organs, can be pulled downward during inhalation. Conversely, exhalation causes the organs and blood vessels to rebound upward. These thoracic and abdominal cavity motions can cause changes in blood vessel length, branch angles, and curvature.

FIGURE 2.10 During inspiration, the diaphragm and external intercostal muscles contract, expanding the thoracic cavity upward, downward, and forward. During expiration, the diaphragm and external intercostal muscles relax, causing the chest cavity to recoil back to the resting position. From https://commons.wikimedia.org/wiki/ File:2316_Inspiration_and_Expiration.jpg.

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RESPIRATION AND VALSALVA

The second driver of respiratory-induced blood vessel motion is from the change in intrathoracic pressure. During inhalation, the thoracic cavity expands, while the abdominal cavity compresses. This combination of decrease in intrathoracic pressure and increase in intraabdominal pressure increases venous return from the abdomen toward the thorax, and to a lesser extent increases venous return from the upper body veins (Fig. 2.11). This works to increase the cross-sectional area of the inferior and superior venae cavae in the thorax during inspiration. During expiration, the increased intrathoracic pressure forces the blood from the venae cavae into the right atrium (compressing the venae cavae in the thorax), while the decreased abdominal pressure encourages venous return from the legs into the inferior vena cava (expanding the inferior vena cava in the abdomen). There are other respiratory-related physiologic phenomena that can affect the motion of the blood vessels, with one of the most common being the Valsalva maneuver. During Valsalva,

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forceful exhalation is attempted against a closed airway, otherwise known as “bearing down.” This maneuver is common during defecation, equalizing ear pressure, childbirth, weight lifting, and clinical diagnostic tests. Upon initiating Valsalva, the increased intrathoracic pressure forces blood from the pulmonary arteries into the left atrium, which causes a brief (perhaps for one or two heartbeats) increase in stroke volume and thus arterial pulsatile deformation (Fig. 2.12). However, because intrathoracic pressure is increased, venous return is compromised, leading to decreased blood flow to the heart and decreased stroke volume. Due to the smaller stroke volume, the heart compensates by increasing heart rate but overall cardiac output is still decreased. This leads to pulmonary artery and aortic constriction, decreased arterial pulsatile deformation, and increased cyclic deformation rate. In parallel, the large veins tend to expand as the blood is “dammed” back. When the forced exhalation pressure is released, intrathoracic pressure drops to

FIGURE 2.11 Intrathoracic pressure decreases during inspiration, thus encouraging increased venous blood return into the thorax from the abdomen and upper body. During expiration, the increased intrathoracic pressure pushes the venous blood into the right atrium of the heart. Adapted from http://slideplayer.com/slide/10843351/, slide 23.

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FIGURE 2.12 Systolic BP and pulse rate changes during the Valsalva maneuver. (1) 5 7 s—With initiation of Valsalva, there is a brief increase in systolic BP and decrease in pulse rate due to rush of blood being pushed from the pulmonary arteries into the left atrium. (2) 7 20 s—Due to decreased venous return, systolic BP and stroke volume decrease significantly, causing a compensatory increase in pulse rate. The systolic BP rises during the latter part of this phase as the arteries constrict in response to lower stroke volume. (3) 20 22 s—When Valsalva is stopped, there is a brief period of systolic BP decrease as the aorta expands, and a large drop in pulse rate as venous return and stroke volume rise. (4) 22 30 s—During recovery, systolic BP and stroke volume increase, while pulse rate continues to decline. These effects actually shoot past normal levels before equilibrating back to normal. BP, Blood pressure.

normal, allowing the pulmonary arteries and aorta to expand, and enabling venous return and cardiac output to increase. The body compensates for the previous period of low cardiac output by elevating stroke volume to above normal levels, causing above normal arterial pulsatile deformation and a slower cyclic rate. In parallel, the veins collapse and empty their contents into the right atrium. Finally, as the body reequilibrates, the blood pressure, stroke volume, heart rate, and cardiac output return to normal.

MUSCULOSKELETAL INFLUENCES While cardiac- and respiratory-induced deformations of the blood vessels are often hemodynamic-based influences, musculoskeletalinduced deformations are purely geometric. For

FIGURE 2.13 Blood vessels that cross mobile joints in the body have to bend and straighten during flexion and extension, respectively. Adapted from https://commons.wikimedia.org/wiki/File:Cheselden_t36_prayer.jpg.

example, blood vessels that cross joints can bend and straighten with joint flexion and extension, respectively (Fig. 2.13). And since most blood vessels are in contact with muscles, and their branches course in between and through muscles, muscle contraction and relaxation can pull and push on blood vessels even in the absence of a skeletal joint. This can happen in the lengthwise direction of the blood vessel, or in the direction perpendicular to the longitudinal axis (Fig. 2.14). To make things more interesting,

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MUSCULOSKELETAL INFLUENCES

since muscles in a single limb do not necessarily act on the same path or direction, different branches on a single vessel can be pulled in inconsistent directions, causing the blood vessel to twist. Another interesting way that blood vessels can deform is by changing path length and tension. As a child grows, his blood vessels are stretched to match the growing path lengths with increased body length. This

FIGURE 2.14 Blood vessels adjacent to muscles are pushed perpendicular to their long axis as muscles bulge outward. From https://www.flickr.com/photos/mrflip/8916916.

stretching of the blood vessels acts to increase axial strain, which is accommodated by the vessels growing more tissue and getting longer to relieve that strain. As the child becomes an adult and no longer grows taller, the blood vessels are still stretched under tension. During adulthood, the blood vessels continue to grow longer and axial stretch decreases over time. In parallel, elastin in the blood vessels degrades as the person ages. In combination, these two processes cause the blood vessels to lengthen, stiffen, and experience a reduction of stretch and tension over time. Now imagine that due to musculoskeletal motion, the path length of a blood vessel decreases. If the vessel is elastic and was substantially stretched originally, this shortening in path length would result in a shortening in vessel length. If, however, the blood vessel was not stretched originally, this shortening in path would result in extra blood vessel length, or redundancy. This is analogous to taking a stretched rubber band and having it stay straight as some of the stretch is relieved, while shortening the path length of a nonelastic string would cause it to bow (Fig. 2.15). To put it another way, stretched elastic vessels can shorten, lengthen, or bend, while nonelastic vessels can only bend or kink. In fact, as people reach more advanced ages, and even in some younger patients with congenital vascular

FIGURE 2.15 An elastic band that is stretched will stay straight upon shortening path length (left); however, a nonelastic string will bow when its ends are brought closer together (right).

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FIGURE 2.16 This 10-year-old girl suffers from a congenital vascular condition where her vessels grew much longer than normal and are chronically in a tortuous state. From Ertugrul, Circulation, 1967; 36: 400 407, Figure 4.

diseases, the blood vessels may lengthen beyond the point of slack and be tortuous all the time (Fig. 2.16).

BODY POSITION AND GRAVITY As described in the cardiac and respiration sections, hemodynamics can affect vascular geometry and deformation. And since body position and gravity can affect hemodynamics, it stands to reason that posture and gravitational environment can affect vascular motion. For example, when soldiers stand straight at attention during inspection, they do not activate their leg muscles which typically serve as muscle pumps to aid venous return back to the

heart (Fig. 2.17). After standing at attention for too long, some people can feel faint because much of their blood volume pools in their lower extremity veins due to the pull of gravity, causing the leg veins to expand and become more circular in cross section. Hint: If you are ever in this situation and are about to faint, you can easily pulse your calf muscles imperceptibly to assist venous return. A persistent change in gravitational environment can cause chronic changes to vascular structure and motion. For example, the arteries of a person on bed rest for an extended period of time adapt in dramatic ways (Fig. 2.18). The arteries in the upper half of the body (above the heart) are normally relatively thin walled because as blood travels toward the head against gravity, the pressure decreases. Thus the arterial walls do not need to be especially thick. Conversely, the lower extremities artery walls need to be relatively thick in order to hold in the higher blood pressure since gravity assists in downward blood flow. With chronic bed rest, however, gravity no longer fights against blood flow toward the head, so the upper body artery walls must thicken in order to decrease circumferential wall stress. In parallel, the lower body arteries experience lower blood pressure due to eliminating the gravity assist, and also carry less blood flow due to lack of activity and atrophy of muscle mass. Thus the lower body artery walls get thinner since there is lower wall stress, and the diameters decrease in order to elevate the dropping wall shear stress. Interestingly, these vascular adaptations due to chronic postural changes are paralleled in astronauts when they live in the microgravity environment of space. When they are exposed to microgravity for extended periods, the artery walls tend to hypertrophy in the upper body while they atrophy in the lower body in order to accommodate the gravitational and accompanying physiologic changes. In fact,

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FIGURE 2.17 When the calf muscles are relaxed, blood tends to pool in the leg veins (left). However, with calf muscle contracted, the veins are compressed and venous blood is forced upward as the inferior vein valves prevent blood from being pushed downward (right). Once the calf muscle is relaxed again, the driving pressure from the foot pushes the blood upward to the recently emptied calf vein. From https://commons.wikimedia.org/wiki/File:2114_Skeletal_Muscle_ Vein_Pump.jpg.

FIGURE 2.18 With normal upright posture, the upper body arteries tend to have thinner walls while the lower body arteries tend to have thicker walls to withstand higher blood pressure (left). With extended bed rest (right), upper body artery walls thicken to decrease circumferential wall stress from increased blood pressure, while lower body arteries adapt with thinner walls (due to lower circumferential wall stress) and smaller diameters (to increase declining wall shear stress).

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FIGURE 2.19 Compared to the 1-G gravity environment (left), microgravity acutely shifts body fluids, including blood, toward the head and away from the legs, resulting in “Puffy Face” and “Bird Legs.” From Canadian Space Agency, http://www.infobarrel.com/Media/Puffy-Face_BirdLeg_Syndrome_53902.

there is a general shift of all fluids in the body in microgravity, and before the chronic physiologic adaptations can take place, astronauts suffer from “Puffy Face-Bird Leg” syndrome (Fig. 2.19).

DON’T REINVENT THE WHEEL Once you have an idea of what vascular motions you need, it is time to survey the information that already exists. Most likely, you are not the first to seek this information, so there is no reason to start from scratch. Perform

literature searches, look at internal documents within your organization, and talk with experts in the field to point you in the right direction or provide opinions. If the area is relatively unknown, it may make sense to find an expert to do this survey. It is amazing how much time you can spend on an accurate and thorough literature search; however, it is much more amazing how much time you can waste quantifying vascular deformations that you may be able to bootstrap from existing knowledge. A good place to start is PubMed. A properly executed search requires the right keywords, typed in the correct order, with Boolean logic operators (e.g., AND, OR, NOT). This will require some trial and error, preliminary searches to familiarize yourself with the correct terminology, and invariably going after some red herrings. In addition, PubMed enables the user to screen references based on many search field tags and filters (Fig. 2.20). A properly executed PubMed search is a beautiful and time-saving thing. For more hints on how to search in PubMed, see: https://www.ncbi. nlm.nih.gov/books/NBK3827/#pubmedhelp. How_do_I_search_PubMed. Another reason this step may take significant effort is that not all available information is necessarily easily searchable on PubMed. There is a lot of useful information in difficultto-find PhD theses, conference abstracts, nonpeer reviewed journals, and interviews. Google is your friend. Moreover, a dirty little secret about vascular motion boundary conditions is that companies often like to keep them secret. You cannot blame the companies; why would they voluntarily spend valuable time and resources on acquiring key information for product development, and then give it to their competitors for free? So unfortunately, sometimes you do have to reinvent the wheel. Or if you truly are the first one there, you may need to invent the wheel for the first time.

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ANIMAL STUDIES

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FIGURE 2.20 PubMed allows the user to refine literature searches based on search field tags (left) and filters (right). From https://www.ncbi.nlm.nih.gov/pubmed.

ANIMAL STUDIES Perhaps the easiest type of experimentally derived vascular motion data is from animal studies. To perform medical imaging on animals, they need to be anesthetized so there is no concern about motion artifacts, their body position can be manipulated at will, and their respiration can even be completely controlled with a ventilator. In addition, there are effectively no limits on imaging time, contrast injection quantity, or radiation exposure, so image signal can be optimized with no compromises. Another convenience is that multiple animal studies are often needed for most medical device development programs anyway for biocompatibility, procedure safety, and healing evaluation; thus so a vascular motion study can be piggybacked onto an existing study with little incremental cost. Even with all these benefits, however, the usefulness of animal data is rather limited

unless you are designing a medical device to be used for veterinary purposes. The anatomic and physiologic differences between humans and animals are plenty, so most animalderived musculoskeletal induced vascular motions are of limited use. For example, the bipedal nature of humans makes the postural, skeletal structure, and muscle action features of quadrupedal animals fairly useless for deriving motion of human lower extremity blood vessels. And since the structure of the ribcage and diaphragm are so different between upright bipeds and quadrupeds, breathing motion is also very different. Cardiac-induced pulsatility, however, may be relatively preserved between species, especially if blood pressures and vessel wall thicknesses are taken into account. In general, the usefulness of animal models increases with body size getting closer to that of humans: Rodent (mice, rats)-Lagomorph (rabbits, hares)-Canine (dogs), Ovine (sheep),

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CADAVER STUDIES

FIGURE 2.21 In order to conservatively test the mechanical durability of an implant that crosses the knee, a canine model (right) produces much more aggressive deformations as compared to an ovine model (left) due to the much more active leg joints. From http://www.publicdomainfiles.com/show_file.php?id 5 14001904213722, https://pxhere. com/en/photo/715819.

Porcine (pigs). And depending on how challenging you would like the vascular motions to be, certain species may be more appropriate. For example, while sheep tend to stay on all four legs most of the day, dogs often sit with their hind legs tucked beneath their bodies, and thus deform their leg blood vessels frequently and with high magnitude (Fig. 2.21). There is also a theoretical benefit to using primates; however, this can get extremely expensive so primates are rarely used in vascular device development programs. Another drawback of using animal models is that they do not tend to acquire vascular disease as do humans, and thus the mechanical environments are different in that respect. While it is possible to induce aneurysm, dissections, and stenoses in animal models, they lack the same tissue stiffening and hard calcium often seen in the equivalent forms of human disease. This, however, can be a good thing if you are seeking especially mobile boundary conditions to test worst-case scenarios. At the very least, animal models are useful for understanding vascular deformations to a first-order approximation and can be used to compare relative deformations (pre- vs post-implant, or implant 1 vs implant 2).

Cadaver studies can be extremely useful for deriving vascular motion boundary conditions for medical device development. As with animals, they benefit from lack of motion artifacts, free manipulation of body positions, and no limits on imaging time, use of contrast, or radiation exposure. In addition, they possess human anatomy and can even be specifically selected based on disease state. The main drawback, of course, is that in vivo physiology is not present. For information on cardiac pulsatility and respiration, steer clear of cadaver studies. No matter how much you coax them, cadavers just will not cooperate in these areas. For cases of joint motion, however, they can be your best subjects. But there are a few nuances to consider. First, if you want to measure deformations in the presence of Nitinol implants, which exhibit varying mechanical properties at different temperatures, it is critical to warm the regions of implantation to in vivo body temperature. This is easier said than done since cadavers are stored cold to minimize decomposition, and warming an entire limb or body can get smelly quickly. One slick way to get around this is to inject heated contrast and/or saline into the blood vessel of interest, which is required for lumen imaging anyway. It is important to inject plenty of fluid volume since the blood vessel will cool down quickly after the injection, so it is a good thing that the cadaver does not care about contrast toxicity. The second concern has to do with blood pressure. While pulsatile pressure and flow would be a nightmare to reproduce with pulsatile flow pumps in the cadaver, average pressure can be approximated. If occlusion balloons are placed proximal and distal to the vessel segment of interest, pressurized intravenous bags or power injectors can be used to temporarily pressurize the blood vessel.

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CLINICAL STUDIES

Pressurization will not last long since there will be some leakage through small collateral vessels and possibly around the occlusion balloons; however, there should be sufficient time to acquire necessary images. It helps that you can make as many attempts as you want. Third, note that cadavers also lack in vivo muscle contraction. This means that all vascular deformations in a cadaver will result purely from joint motion, devoid of any pulling, twisting, and pushing influence from contracting muscles. However, since cadavers have no scan time or radiation limits, a large number of body positions can be imaged, whereas patients are usually limited to two or three positions.

CLINICAL STUDIES The holy grail of vascular motion data is of course from imaging actual live humans. Depending on the need, these imaging studies can be performed on healthy volunteers or patients with disease. For example, to find aggressive conditions for diametric distension due to cardiac pulsatility, it might be beneficial to quantify the diametric deformation in healthy, elastic arteries. However, to quantify vessel kinking at the end of an implanted stent, it makes sense to scan a patient with occlusive arterial disease treated with angioplasty and stenting. But to achieve this golden data, there are complex issues to surmount, first and foremost, the ethical recruitment of volunteers. There are costs and risks to all imaging procedures, from the minor inconvenience of taking time to undergo an ultrasound scan, all the way to increased cancer risk (from radiation exposure) and renal failure (from iodinated contrast media) from contrast-enhanced computed tomography angiography. These risks need to be carefully justified, weighed with

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potential benefits, and approved through institutional review boards. Because there are costs to these imaging studies, it is often beneficial to piggyback them on clinical trials or on studies that are already indicated for standard clinical care. This can be in the form of diagnostic, preoperative planning, postoperative evaluation, or ongoing surveillance scans. The benefits of this strategy are the ability to select patients with specific disease and treatment characteristics, predictable timing of patients coming to the hospital, not requiring extra visits from the patients, and leveraging any associated risks that will result anyway (e.g., intravenous line insertion, radiation exposure). The downside is that proper clinical care should, and always will, trump data collection for product development, and finding ways to fit into the normal cycle of care is a nuanced game. Partially for this reason, it sometimes makes sense to seek volunteers who are not receiving clinical care, which can either be healthy subjects or patients with disease. In these scenarios, the study procedure and imaging protocols must be as efficient and low risk as possible since participation requires clinically unnecessary trips to the study site. This means that the imaging modalities are usually limited to those without ionizing radiation, such as ultrasound and magnetic resonance imaging. Intravenous contrast media can be used; however, the risk of needle puncture and potential allergic reaction to contrast injection must be amply justified. Do not underestimate how difficult it is to select and recruit volunteers for a clinical imaging study. In my experience, subject recruitment and acquisition of imaging data is approximately a quarter to a half of the total work involved in quantifying vascular motion, which is why the quality of outside partners is so important.

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OUTSIDE PARTNERS Unless your company has its own imaging equipment and has a system in place to perform medical imaging on animals or cadavers, you will have to work with an outside partner. For animal and cadaver studies, there are many labs around the world equipped with the proper staff and imaging equipment to help you collect data. Many of them have veterinarians, imaging technologists, anesthetists, and even interventionalists on staff. However, do not be shy about bringing your own staff and materials if specific expertise and protocols are desired. As for live human studies, outside partners with institutional review boards are a prerequisite. Community and academic hospitals can both be good options for acquiring human imaging data; however, there are some differences between the two. In general, academic institutions have more specialists who are interested in research, and thus may be more amenable to performing clinical trials, research studies, and even early feasibility investigations. Academic hospitals also tend to have the most cuttingedge imaging technology and the capability to stray from traditional clinical protocols. On the other hand, community hospitals may be able to move faster in terms of contracts, be more amenable to sharing imaging information, and have greater patient volumes, which can facilitate patient recruitment. Note that these are soft generalizations with exceptions abound. Whichever hospital(s) you partner with, the absolute most critical piece is the principal investigator. It is much better to have a go-getter investigator motivated to perform your study in a second-tier hospital than an unmotivated investigator in the most sparkling, well-equipped hospital in the country. A good principal investigator will know the hospital’s capabilities, help design your study, and manage the ethical recruitment

of patients, medical imaging, and all the staff needed to accomplish these tasks. If the principal investigator is not well versed in medical imaging, be sure that at least one member of the team is, especially if your study requires nonstandard imaging. Often times, your best ally is the radiology technologist who will be interacting with the patients and actually pushing the buttons on the scanner. Finally comes the person who will help you with all the topics in this book, namely, imaging study design, image analysis, quantification, interpretation of data, conversion to boundary conditions, and application to device evaluation, design, and clinical use. All these skills do not necessarily have to exist in one person, but all the pieces need to be in place to make sure the correct data is efficiently acquired, interpreted, and utilized.

CONCLUSION In order to properly define vascular motions, one must first start with the intended function and clinical indication of the device, and attempt to anticipate drivers of motion that may mechanically interact with it. The drivers of motion include cardiac pulsatility, respiration, musculoskeletal motion, and body position. The actual motion data can be acquired from existing literature, cadaver experiments, animal experiments, or human imaging. Finally, careful selection of outside partners in the form of preclinical laboratories, hospitals, universities, and investigators is critical for collecting and utilizing motion data for boundary conditions.

Reference Ertugrul, A., 1967. Diffuse tortuosity and lengthening of the arteries. Circulation 36, 400 407.

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Medical Imaging Modalities and Protocols Christopher P. Cheng Division of Vascular Surgery, Stanford University, Stanford, CA, United States

This chapter provides a brief overview of medical imaging techniques that can be used to image blood vessels and vascular implants for the purposes of quantifying motion and deformation. Imaging modalities to most appropriately record physiologic motion depends on the target anatomy, type of motion, the speed of the motion, and its

periodicity. For example, while a simple realtime B-mode ultrasound may work very well for imaging radial pulsatility in a native carotid artery, the nonplanar bending of an aortic endograft due to respiration will require multiple breath-held three-dimensional (3D) computed tomography (CT) scans. Choosing the wrong medical imaging modality is more than a matter of not getting the information you seek. Using an inappropriate modality may cause unnecessary risk or even catastrophic harm to the patient. This chapter is about choosing the right tool for the task (Fig. 3.1).

MEDICAL IMAGING MODALITIES The common medical imaging modalities are categorized into X-ray transmission, acoustic or light reflection, magnetic resonance, and radiation emission. While the different modalities in one imaging category share the same fundamental premise, they may include many variations which can be tuned to measure

FIGURE 3.1 Choosing the wrong tool for a task may not only prevent the job from getting done but may also damage the objects involved. From https://pxhere.com/en/ photo/704019.

Handbook of Vascular Motion DOI: https://doi.org/10.1016/B978-0-12-815713-8.00003-6

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© 2019 Elsevier Inc. All rights reserved.

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different structures or phenomena. Here is a brief review of the basic mechanisms for each common type of medical imaging.

X-Ray Transmission X-ray transmission imaging is based on measuring the amount of X-ray radiation that hits a detector after the original X-rays have been attenuated by objects in their path. Attenuation is the combination of X-ray absorption (into an object) and scattering (caused by that object). The way different structures are distinguished from each other is by differing amounts of X-ray attenuation cause by those structures. This means that the difference in attenuation, relative to the average X-ray signal, is the amount of perceived differentiation. Note that X-ray scattering tends

to decrease the amount of signal differentiation that X-ray absorption alone would produce (Fig. 3.2). In its simplest form, X-ray imaging requires a point source and a film, which is called plain film X-ray (Fig. 3.3). In this form of imaging, all structures in the direction of the beam act to attenuate the X-rays together, forming a twodimensional (2D) projection map of attenuation. In other words, you can detect differences in attenuation between structures next to each other, but there is no way to distinguish structures that are in front or behind each other. C-arm X-ray imaging takes the plain film concept and mobilizes the position and direction of the X-ray beam. This means that the X-ray beam source and detector can be translated, rotated, and tilted with three degrees of freedom to get varying projection viewpoints. Combined with an image intensifier,

FIGURE 3.2 A point source transmission of X-rays through different body tissues. When only considering absorption without scatter, there is a larger signal difference between different tissues (left) as compared to the situation where scatter lessens the difference in signal (right). From Seibert, J.A., Boone, J.M., 2005. X-ray imaging physics for nuclear medicine technologists. Part 2: X-ray interactions and image formation. J. Nucl. Med. Technol. 33, 3 18, Figure 8.

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FIGURE 3.3 Plain film X-ray produces a 2D projection map of attenuation, enabling differentiation of attenuation between structures that are next to each other relative to the direction of the X-ray beam, but not in front or behind each other relative to the X-ray beam. 2D, Two-dimensional. From http://en.wikibooks.org/wiki/Basic_Physics_of_Nuclear_Medicine/XRay_CT_in_Nuclear_Medicine.

FIGURE 3.4 C-arm X-ray machines enable the X-ray source and detector to be mobile such that 2D projection images can be produced from varying positions and directions. 2D, Two-dimensional. From https://commons.wikimedia.org/wiki/File:HmhCathLab.JPG.

postprocessing software, and viewing monitors, C-arms are critical for nearly all minimally-invasive cardiovascular procedures (Fig. 3.4).

To move beyond projection images where all structures in-line with respect to the direction of the X-ray beam are overlapped on top of each other and indistinguishable, a technique called filtered back projection can be used to reconstruct a fully resolved matrix image based on a large collection of projections from different angles. The collection of projection images is reconstructed together by computer algorithms, which is why this technique is called computed tomography, or CT (Fig. 3.5). To create a 3D matrix image, many 2D matrix images are essentially stacked together. In practice, this is performed by a sliding table on which the patient rests, and a continuously rotating pair of X-ray source and detector array. This produces a helical coverage of the region of interest with X-ray projections which can then be reconstructed together into a 3D image (Fig. 3.6). There are also C-arm CTs that combine the capabilities

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FIGURE 3.5 CT is a technique where a matrix image is reconstructed from a large collection of X-ray projection images from many angles using computer algorithms. CT, Computed tomography. Adapted from http://en.wikibooks.org/wiki/ Basic_Physics_of_Nuclear_Medicine/X-Ray_CT_in_Nuclear_Medicine.

FIGURE 3.6 3D computed tomography is performed by helical coverage of X-ray projections, and computer reconstruction of those projections into a 3D matrix image. 3D, Three-dimensional. Adapted from http://en.wikibooks.org/wiki/ Basic_Physics_of_Nuclear_Medicine/X-Ray_CT_in_Nuclear_Medicine (Ieft) and image from author (right).

of physician-controlled projection views and rotational computed tomography.

Acoustic and Light Reflection Medical ultrasound works from the same principle as a submarine’s sonar. Sound waves are emitted, and the reflection of those waves provides information about the objects from which they are reflected (Fig. 3.7). Medical ultrasound uses sound waves in the 1 18 MHz frequency range and relies on these

waves reflecting off of tissues to varying degrees to produce images. The sound waves are produced by a piezoelectric transducer, which converts electrical signals into ultrasound waves (transmitter). The reflected sound waves are received either by a different transducer (receiver) or the same transducer (transceiver), and the vibrations detected by the transducer are converted into electrical signals. To create a digital image, the receiver must determine two things from each received echo: (1) how long it took the echo to be received

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FIGURE 3.7 Medical ultrasound works on the same principle as sonar, where sound waves are emitted to and reflected from objects, and the reflections are used to gather information about those objects. From https://commons.wikimedia.org/wiki/File: Sonar_Principle_ES.svg.

FIGURE 3.8 Medical ultrasound relies on the transmission of sound waves and receiving of reflected sound waves (echos), which can then be converted into electric signals and converted into a digital image. Medical ultrasound is commonly used for imaging the fetus in utero, both in 2D (left) and 3D (right). 2D, two-dimensional; 3D, three-dimensional. Adapted from https://en.wikipedia.org/wiki/Ultrasound.

and (2) how strong the echo was. With these two pieces of information, image processing techniques can locate which pixel in the image to light up, and to what intensity. These techniques can be leveraged for 2D or 3D images (Fig. 3.8). While ultrasound typically provides less anatomic detail due to lower signal-to-noise and tissue contrast as compared to X-ray and magnetic resonance imaging, it uses no ionizing radiation, is portable and inexpensive, is very good at capturing moving structures in

real time, and has the ability to track actual material points of tissue with image speckles. This speckle tracking can be utilized for motion and strain imaging, which is included in a set of techniques referred to as ultrasound elastography. To get a more precise look at the blood vessels themselves, especially smaller blood vessels that are not easily reached by surface ultrasound scanners, intravascular ultrasound (IVUS) can be used. Miniaturized piezoelectric transducers are manufactured into intravascular catheters and

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FIGURE 3.9

Intravascular ultrasound scans from within the blood vessel lumen and can distinguish the blood lumen (yellow line), external elastic membrane (blue line), and hence the vessel plaque in between (green shaded area). From https://commons.wikimedia.org/wiki/File:IVUS_of_CAD.png.

emit and receive sound waves from within the blood vessels. Being inside the blood vessels means less imaging depth is required, and thus the transducers can use higher frequencies (20 40 MHz). IVUS can achieve better resolution than regular ultrasound and provides good tissue contrast to differentiate vessel plaque (Fig. 3.9). Similarly, the reflection of near-infrared light can be used to capture optical “echo” images. Vascular optical coherence tomography, or OCT, directs optical beams toward the vessel wall and uses the small proportion of light that reflects from the subsurface of the tissue to create an image. Since most of the light is not reflected but rather scatters at different angles, OCT relies on a technique called low-coherence interferometry to record the optical path length of the received photons and discards the data from photons that scatter multiple times before detection. OCT delivers high resolution on the scale of micrometers; however, it is limited to imaging 1 2 mm below the surface since at greater depths the proportion of light that escapes without scattering is negligible.

Magnetic Resonance Magnetic resonance imaging (MRI) utilizes powerful magnetic fields and radio waves to derive contrasting signals between different types of tissues and materials. The main magnetic field is called B0 and applies a static field in one direction, which encourages certain atomic nuclei to preferentially align in the direction of the field (Fig. 3.10). The nuclei of choice in

FIGURE 3.10 Without an applied magnetic field, the protons within hydrogen atoms point in random directions, producing no net magnetization (left). With an applied B0 field, the protons will preferentially align in the direction of the field (right).

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most medical MRI are that of hydrogen atoms, or simply single protons. Since hydrogen is present in abundance in the tissues of the human body within water and fat, it is a reliable way to image the various tissues of the body. The hydrogen nuclei precess at a known frequency based on the B0 field strength, and thus if energy is applied at that exact frequency through radio waves, these nuclei can be “excited” to a different state. Once excitation is turned off, the atoms “relax” back to their equilibrium states and emit radiofrequency signals

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during that relaxation which are detected by a receiver coil, similar to a radio antenna. The relaxation of the atoms causes a “decay” of transverse magnetization and a “recovery” of longitudinal magnetization (Fig. 3.11). This relaxation of the radiofrequency signals can be encoded to include spatial position information, relaxation signatures of the magnetization, and proton densities (correlated to the amount of magnetization), which can be used in various combinations to distinguish between tissues and tissue properties (Fig. 3.12).

FIGURE 3.11

With the application of energy at the precession frequency, the magnetization of the atoms can be excited from the longitudinal to the transverse axis. Once the excitation is turned off, the magnetization relaxes back to equilibrium at that same precession frequency in a helical fashion (left), and the decay of the transverse magnetization (|Mxy|, middle) and the recovery of the longitudinal magnetization (Mz, right) can be detected as radiofrequency signals.

FIGURE 3.12 Magnetic resonance imaging can derive differential signal between tissue in the brain with T1-weighted (longitudinal component of magnetization; good for identifying general morphology and fatty tissue), T2-weighted (transverse component of magnetization signal; good for identifying edema and inflammation), and proton density-weighted (proton density; good for distinguishing between gray and white matter in the brain) encoding techniques. From https://en. wikipedia.org/wiki/Magnetic_resonance_imaging#/media/File:T1t2PD.jpg.

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MRI can image an arbitrary 2D slice of anatomy by specifically exciting that 2D slice within a 3D volume of space by using precise gradient magnetic fields. A sequential collection of these 2D slices can be stacked together to produce a fully resolved 3D volumetric image.

Radiation Emission Radiation emission imaging, better known as nuclear medicine, relies on the uptake of radioactive material into the body, and the subsequent emission of radiation from that radioactive material. The preferential uptake or reduced uptake of the radioactive material into certain tissues enables the production of images that can identify physiologic, rather than anatomic, phenomenon. Popular nuclear medicine imaging modalities include scintigraphy, positron emission tomography, and single photon

emission CT. Since these modalities do not produce appropriate images to quantify anatomic motion and deformation, they will not be featured in this book. Note, however, that when there are inconsistencies between anatomy and physiology, this type of functional physiologic imaging can be very useful to diagnose disease. To illustrate the importance of nuclear medicine in its ability to reveal physiologic status, here is an example of how a pulmonary ventilation and perfusion scan can diagnose pulmonary embolism (blockage of an artery in the lungs). Patients are required to inhale a radioactive gas and be injected with a radioactive fluid into the vein. Since the radioactive gas will show the areas of air uptake into the lungs (ventilation), and the radioactive fluid will show the areas of blood flow into the lungs (perfusion), regions of high ventilation and low perfusion could indicate a blockage to blood flow (Fig. 3.13).

FIGURE 3.13 Pulmonary ventilation and perfusion scans can reveal pulmonary embolism by showing mismatches in air and blood flow distribution. The ventilation scan (left) shows an even distribution of air, while the perfusion scan (right) shows mismatched defects (circles) which could indicate pulmonary emboli. Adapted from https://en.wikipedia.org/wiki/Ventilation/perfusion_scan#/media/File:Pulmonary_embolism_scintigraphy_PLoS.png.

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IMAGING BASED ON TARGET To select an appropriate imaging modality and protocol to capture a particular type of vascular motion data, the target must first be considered. The three main factors are: (1) what do you need to see, (2) what can be seen, and (3) imaging risk. For example, if the goal is to measure the motion and deformation of a native artery, X-ray, ultrasound, and MRI can all resolve either the lumen or vessel wall. If the deformation to be resolved requires natural fiducial markers, then the quality of the signal, resolution, and field of view need to be considered. In the cases where a large field of view is required to track multiple fiducial markers simultaneously, such as when there are numerous branch vessels, X-ray and MRI modalities will work better than ultrasound (Fig. 3.14). However, ultrasound is capable of identifying tissue material points with speckle tracking, which can be used to quantify strains with elastography (Fig. 3.15). Other useful

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fiducial markers include embedded calcification, bifurcations, sudden diametric transitions (e.g., sinuses and aneurysms), and idents from extravascular structures (e.g., ligamentum arteriosum at the aortic isthmus) (Fig. 3.16). To achieve the highest signal from the vessel lumen, contrast agents can be used. For X-raybased vascular imaging, iodinated contrast is used because it has a much higher X-ray attenuation as compared to blood and soft tissues. For MRI techniques, gadolinium-based agents are used since gadolinium dramatically shortens magnetic relaxation time. Specifically, gadolinium shortens the recovery time of longitudinal magnetization. For ultrasound, gas-filled microbubbles are used as contrast because they possess very high reflectivity of ultrasound waves compared to soft tissue. Thus when iodine, gadolinium, and microbubbles are injected into the bloodstream for X-ray, MRI, and ultrasound, respectively, the vessel lumens show up very bright. This enables clear visualization of the luminal vessel

FIGURE 3.14 When multiple arterial branches need to be identified simultaneously, a large, volumetric field of view may be necessary, as demonstrated with the muscular branches in the superficial femoral artery (left) and the visceral and lumbar branches in the abdominal aorta (right).

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wall boundary, and illumination of small branch vessels that would otherwise be impossible to detect (Fig. 3.17). If the target vessel includes a metallic implant, and the deformation of that implant is of interest, some form of X-ray transmission imaging will serve best because the metallic

FIGURE 3.15 Ultrasound speckle tracking can track moving material points, which can be used to calculate strains. From Gorcsan, J., Tanaka, H., 2011. Echocardiographic assessment of myocardial strain. J. Am. Coll. Cardiol. 58 (14), 1401 1413.

imaging artifacts from MRI and ultrasound will likely obscure the metallic material and the adjacent regions (Fig. 3.18). Note that for X-ray techniques, imaging artifacts may still occur with metal implants, including beam hardening and streak artifacts. In addition, the use of intravascular contrast agents may wash out the adjacent metallic signal of a device because iodine can attenuate X-rays similarly to metal. Imaging patients with metallic devices requires particular attention for MRI, because in addition to metal causing imaging artifacts, ferromagnetic materials can be subject to substantial forces in the strong main magnetic field. Furthermore, long conduction objects (e.g., guidewires) can interact with the radiofrequency fields like antennas and cause heating (McFadden, 2012; Nitz et al., 2001). In fact, vascular metallic implants need to be evaluated for induced force, torque, heating, and imaging artifacts per ASTM standards for regulatory approval (ASTM Standard F2182-11).

FIGURE 3.16

Native non-branch fiducial markers include embedded calcification (left, X-ray), aortic bifurcation and diametric transition at an abdominal aortic aneurysm (middle, magnetic resonance angiography), and diametric transition from the sinotubular junction and lumen indent at the aortic isthmus (right, computed tomography angiography). Adapted from commons.wikimedia.org, Cases courtesy of Dr Roberto Schubert and Dr Henry Knipe, Radiopaedia.org.

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FIGURE 3.17 As gadolinium contrast flows into the arteries in the thigh, magnetic resonance angiography reveals smaller branch arteries in greater detail.

FIGURE 3.18 This patient is not missing a piece of his brain . . . he just has some ferrous metal shrapnel in his head which is corrupting the MRI signal. This may render this particular MRI ineffective, especially if the purpose of the scan is to find out where the shrapnel is in his head. Case courtesy of Dr Ayush Goel, Radiopaedia.org.

In terms of imaging risk, X-ray transmission modalities all require ionizing radiation while ultrasound and MRI do not. Ionizing radiation from normal X-ray imaging has been shown to correlate with increased risk of developing cancer years or decades after exposure. However, at significantly higher doses, X-rays can cause more immediate effects, such as hair loss, cataracts, decreased fertility, bone marrow suppression, and even burns. With these risks, X-ray-based imaging should be reserved for patients for whom X-ray plain films, C-arm fluoroscopy, or CT scanning are part of their clinical care, or in cadavers and animals where radiation risk is essentially not a concern. If the goal is to measure vascular motion in healthy volunteers, ultrasound and MRI will be the safer and more appropriate modalities since any radiation risk may not be tolerated. While contrast agents help with imaging signal and visualization, they also come with risks. Iodinated contrast for X-ray-based imaging can cause side effects from mild nausea and rash, to moderately-dangerous difficulty breathing and abnormal heartbeats, to lifethreatening swelling of the throat and cardiac arrest. And because iodinated contrast needs to be cleared by the kidneys, patients with

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impaired kidney function may experience contrast-induced nephropathy. This means it is critical to evaluate kidney function prior to using iodine contrast. Gadolinium for MRI is much less likely to produce allergic reactions as compared to iodine, and the reactions tend to be less severe. However, in rare cases, people injected with gadolinium contrast will experience itchy eyes, hives, and trouble breathing. These reactions occur in approximately 0.1% of patients, and the author of this book happens to be lucky enough to be one of these one out of a thousand (I had plenty of chances to build up a gadolinium sensitivity since I was often the first test subject when trialing my own MRI protocols). In even rarer cases, gadolinium can also cause severe anaphylaxis or nephrogenic systemic fibrosis. Regarding ultrasound microbubbles, they are quite safe; however, acoustic microbubble destruction can cause damage to microvasculature and red blood cells. Good thing we have plenty of each.

IMAGING BASED ON TYPE OF MOTION Every imaging modality has its trade-offs, so it is important to consider them based on the type of vascular motion to be quantified. Diametric deformation can be described in one dimension and cross-sectional deformation can be described in two. Axial length deformations (shortening and lengthening) is technically in one dimension, however, vessels are usually not straight and thus require 3D visualization to quantify true arc length. In addition, axial length changes require at least two fiducial markers, which are usually not on the same axis or even on the same plane. Axial twist (angular twist along a length) also requires two fiducial markers, so it necessitates 3D geometries. Bending can be defined in two dimensions when it is in plane, but bending requires three dimensions when it occurs out of plane.

When quantifying diametric and crosssectional metrics and deformations where the exact anatomic location of the measurements does not need to be very precise, B-mode ultrasound works well. Since B-mode imaging is only in a 2D plane and the blood vessel may move with respect to that plane, the plane of imaging may wander somewhat in relation to the anatomy. B-mode ultrasound is low cost, easy to acquire in real time, does not require any contrast agents or specialty equipment, does not pose any risk to the patient, and is a great choice when the desired vascular deformations are in a single plane. For example, this is an ideal modality for quantifying the approximate diametric (1D) or cross-sectional (2D) pulsatility of a native aorta (Fig. 3.19). In fact, for simple diametric deformation, even 1D M-mode ultrasound could suffice in certain circumstances. In cases where the exact location of the cross-sectional deformation is required, a fiducial marker in the form of a branch vessel, vascular calcification, implanted device, or other stable geometric feature is required. MRI and CT are both able to identify anatomic markers, especially with the aid of intravascular contrast media enhancement; however, precise localization of metallic devices should be relegated to CT. For axial length, axial twist, and bending deformations, 3D imaging is often required, usually with the need to track multiple fiducial markers. For these applications, particularly for larger fields of view, volumetric MRI or CT is the most appropriate imaging modality. In cases where the fiducial markers are small, such as with small branch vessels or specific small features on a device (e.g., individual struts or strut apices), resolution is paramount. For example, if a branch vessel being used as a marker is of similar dimension, or smaller, as compared to the voxel dimension, then partial voluming may inhibit clear identification of that marker (Fig. 3.20).

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FIGURE 3.19

Two-dimensional B-mode ultrasound can be used to measure cross-sectional deformation (blue box, left and middle images) or diametric deformation in the anteroposterior axis along the axial length of the aorta (green box, left and right images) Adapted from https://ca.wikipedia.org/wiki/Fitxer:Aorta_scheme.jpg (left) and www.ultrasoundpaedia.com/normalabdominal-vascular/ (middle and right).

FIGURE 3.20 Example of partial voluming effect with MRI of the brain. In the top row, the red and yellow circles represent nerves and scar tissue, respectively, both residing in cerebrospinal fluid. The blue rectangles represent 5 (left) and 1 mm (right) imaging slice thicknesses, and the corresponding MR images are shown in the bottom row. Because the 5 mm slice is thicker than the individual nerves and pieces of scar tissue, the signals of these tissues are indistinguishably mixed with cerebrospinal fluid (left). However, the thin 1 mm slice enables visualization of non-mixed nerve and scar tissue signal, making the individual tissues distinguishable. Courtesy of Allen D. Elster, MRIquestions.com.

Bearing in mind that the amount of signalto-noise ratio (SNR), a measure of how much true information there is in relation to random

noise, is intimately related to resolution, SNR must be considered. For X-ray-based imaging, including plain films, X-ray fluoroscopy, and

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FIGURE 3.21 Two examples of dedicated biplane angiography X-ray equipment manufactured by Scanflex Healthcare (left) and Siemens Healthcare (right). Adapted from https://en.wikipedia.org/wiki/G-arm_medical_imaging#/media/File:Biplanar.jpg (left) and healthcare.siemens.com (right).

CT, the greatest drivers of SNR are radiation dose, number of detectors, spatial resolution, and temporal resolution. Analogously for MRI, SNR is related to main field strength, amount of imaging time, spatial resolution, and temporal resolution. Since SNR and spatial resolution are at odds with each other for both imaging modalities, it is a balancing act of parameters to simultaneously achieve sufficient resolution and SNR to resolve small features, and similarly, small motions. And since sharp contrast between adjacent structures enables precise localization of borders, contrast enhancement is often used in cases of small fiducial markers, of small motions, or with a need to have high precision of motion and/or deformation. Note that in the case of X-ray imaging, 3D CT can potentially be approximated with multiple 2D X-rays in different views. Two views, as close to orthogonal from each other as possible, can be combined to form a projection in 3D space. In fact, this practice is so useful that biplane angiography has its own dedicated type of equipment and is commonly used (Fig. 3.21). Even in the cases where biplane

equipment is not available, multiple views can be taken with C-arm X-ray machines. This practice is especially useful considering that multiview 2D imaging can be performed periprocedure in the catheterization lab, eliminating the need for an extra imaging procedure and substantial additional radiation exposure for the patient.

IMAGING BASED ON TIMESCALE AND PERIODICITY Another major topic to understand when performing medical imaging is timescales of the phenomena of interest. Are the motions happening within fractions of a second, over many seconds, or over minutes or longer? Are the motions driven by consistent cyclic phenomena, or are they inconsistent and non-periodic? Do the motions have to be captured in real time, or can they be captured over multiple cycles, or can they be artificially slowed down in order to have more time to capture them?

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For cardiovascular motions and deformations, the fastest timescales are usually related to the cardiac cycle. While the normal resting heart beats approximately once per second (typical heart rate is B70 beats per minute), the heart can beat significantly faster during exercise or in states of stress (up to 200 beats per minute). Furthermore, while the entire cardiac cycle may last a second, most of the action happens during systole, which is usually shorter than half of the entire cycle. In fact, while systole may last approximately one-third of a second, cardiovascular deformations can be very dramatic during that time, and temporal resolution may need to be on the timescale of one-tenth of a second, or shorter, in order to capture a “freeze frame” of fast-moving anatomy. Also note that as heart rate increases, the diastolic phase accommodates the brunt of the shortening of the cardiac cycle, so its timescale may also require temporal resolution of onetenth of a second or shorter. For 1D M-mode and 2D B-mode ultrasound, which typically scan at temporal resolutions of 30 100 and 1000 2000 frames per second, respectively, cardiac pulsatilityinduced motion is easily detectable. Similarly, for C-arm X-ray fluoroscopy, images are typically acquired at 30 Hz, providing plenty of temporal resolution. Even for MRI and CT, relatively small volumetric “freeze frame” images can be achieved in less than 100 ms with advanced techniques, such as dualsource and cone beam technologies for CT, and rapid coverage pulse sequences and parallel imaging technologies for MRI. However, these more modern techniques may not be readily available at many imaging facilities. For larger volumes that can capture the thoracic aorta, abdominal aorta, or long peripheral arteries, in combination with smaller branch vessels, real-time imaging may not be a viable option. This is where cardiac-gated imaging becomes useful.

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Cardiac gating is a concept that works with all imaging modalities; it is when an image is collected in multiple segments, each segment during successive heartbeats. This means that while the true temporal resolution of an imaging modality is too slow to adequately capture fast movements, smaller portions of a full image can be captured in real time over many cycles, and then reconstructed together to form the full image with sufficient temporal resolution (Fig. 3.22). This, of course, requires that the multiple cycles during imaging acquisition are essentially alike, which is usually the case with heartbeats. However, with irregular heartbeats or heart rates, this technique can be compromised. Typically, cardiac-gated scans are performed during a breath-hold so that respiratory motion does not corrupt the image. Cardiac gating can be controlled by electrocardiogram (ECG) or plethysmograph signal and comes in two main flavors: prospective and retrospective (Fig. 3.23). Only ECG gating will be described here, although plethysmograph-gating works in a similar fashion. Prospective gating is when acquisition of the multiple segments of an image is triggered by an ECG signal. For example, acquisition of data can be triggered to occur 300 ms after the QRS wave on the ECG, effectively capturing the anatomy during the relatively motionless phase of diastole. The main drawbacks of prospective gating are that it is extremely sensitive to very fast and irregular heartbeats, and it cannot fully describe all stages of the cardiac cycle. Retrospective gating, on the other hand, consists of continuously acquiring data while an ECG signal is being recorded, and then subsequently using the ECG recording and sorting algorithms to arrange the data such that full images of the anatomy are reconstructed for multiple “frozen” time points. This means retrospective gating can describe the entire cardiac cycle and can adjust somewhat for inconsistency in irregular heartbeats.

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FIGURE 3.22 When imaging a large field of view, real-time imaging may not be sufficient to capture crucial anatomic details in moving structures. Without cardiac gating, motion artifacts are seen in the aortic root and ascending aorta (left). With cardiac gating, the anatomy is much clearer, with an observable pseudoaneurysm at the aortic root (right). From Giambuzzi, M., Seitun, S., Salsano, A., Passerone, G., Ferro, C., Santini, F., 2015. Nongated vs electrocardiography-gated CT imaging of blunt aortic root rupture in a trauma patient. J. Cardiovasc. Comput. Tomogr. 9 (2), 146 148.

FIGURE 3.23 Prospective gating relies on the electrocardiogram signal to trigger image acquisition during certain portions of the cardiac cycle (top), while retrospective gating acquires data continuously (bottom) and reorganizes them according to the simultaneously recorded electrocardiogram signal. Courtesy of Allen D. Elster, MRIquestions.com.

Besides the qualitative differences in images between prospective and retrospective gating for X-ray-based CT scanning, these two methods of image acquisition also vary greatly in terms of radiation dose to the patient (Fig. 3.24). For prospective gating, since

scanning only occurs during a fractional portion of the cardiac cycle after triggering, the radiation dose tends to be relatively low at the cost of not imaging the entire cardiac cycle. With regular retrospective gating, the radiation is on at full dose during the entire time of

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FIGURE 3.24 With prospective gating, since scanning only occurs during a short portion of the cardiac cycle, radiation dose is relatively low (top). With regular retrospective gating, the radiation is on at full dose during the entire cardiac cycle, and thus the radiation dose is very high (middle). Retrospective gating with ECG-gated dose modulation enables imaging of the entire cardiac cycle with a compromise of image quality and radiation dose during much of the cardiac cycle. ECG, Electrocardiogram. From Pelgrim, G.J., Oudkerk, M., Vliegenthart, R., 2013. Computed tomography imaging of the coronary arteries. In: Baskot, B.G. (Ed.), What Should We Know About Prevented, Diagnostic, and Interventional Therapy in Coronary Artery Disease. IntechOpen, Figure 1.

continuous scanning, which generates images with full signal for all time points at the cost of very high radiation dose. Retrospective gating with dose modulation is a technique that borrows from both concepts and provides a compromise of data richness and radiation dose. Full radiation dose is only used during a selected portion of the cardiac cycle, and the dose is dramatically reduced for the rest of the cardiac cycle. This means that during the

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periods of full dose, anatomic structures are imaged with full signal and clarity, while during the periods of low dose, those structures are imaged albeit with less SNR. For other physiologic phenomena, such as respiration and musculoskeletal motion, imaging “snapshots” usually work quite nicely. This is not only because these phenomenon are either slower than cardiac cycles or can be voluntarily controlled, but because they are generally less periodic than heartbeats. For large fields of view, such as when covering the entire thorax, abdomen, or legs, X-ray imaging can capture a 2D picture in a fraction of a second, and CT and MRI can capture a 3D volume in single-digit seconds to 20 30 s, depending on the resolution and image quality. This means that to resolve respiratory-induced motion, the patient would need to perform a breath-hold for the duration of a scan, for example, once during inspiration and once again during expiration. For musculoskeletal induced motion, the patient must hold each body position motionless for the duration of a scan. There are a few important things to note here. While holding breath IN for 20 30 s may seem easy, holding breath OUT for that same period is significantly more difficult, especially for sick patients. Thus there is always a balance of image quality to what the subject can accomplish. Also, while various body positions can be held passively for extended periods, certainly long enough for imaging, these positions may not include normal physiologic muscle action. For example, when imaging the femoral artery with hip and knee flexion inside conventional CT or MRI scanners, subjects must be lying down to fit inside the bore of the scanner, and thus it is difficult to establish weight bearing. Special scanner-compatible equipment can be constructed to enable weight-bearing during imaging procedures (Fig. 3.25). There are even open and upright scanners, which provide much more flexibility in scanning configurations.

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FIGURE 3.25 Schematic and photograph of an MRI-compatible weight-bearing device to enable imaging of muscle action. MRI, Magnetic resonance imaging.

Imaging multiple drivers of vascular motion simultaneously (e.g., cardiac and respiratory, cardiac and musculoskeletal) requires mixing the techniques described previously. This can get rather complicated. For example, you may want to perform a retrospectively cardiacgated scan during a breath-hold in and a breath-hold out. Or you can simultaneously gate for the cardiac and respiratory cycles to disentangle the influence of each (Frederickson et al., 1995; Badea et al., 2004; Kolbitsch et al., 2017). Keep in mind that since respiratory cycle duration and breathing depth are not as consistent as heartbeats, it will take a metronome, respiratory bellows around the diaphragm, and special instructions to accomplish this. Imagine trying to keep every breath exactly 5 seconds long with exactly 4.0 cm of diaphragm excursion while lying in a cramped CT scanner for several minutes, and you will see why this practice is rarely used.

MEDICAL IMAGING PROTOCOLS In general, it makes sense to leverage the simplest, cheapest, and lowest risk imaging modality that can accomplish the task at hand. This is not only for efficient use of resources and patient safety but also for data quality and relevance.

Using less resource-intensive and lower-risk modalities and protocols usually translates into acquiring more data in a shorter amount of time. The greater number of data sets adds robustness to the quantified boundary conditions and enables a better estimation of the vascular motion that the overall patient population experiences. Faster acquisition of data encourages the use of these boundary conditions for product design and development, rather than just to incorporate into documentation for final regulatory submission or to rationalize device fractures after completion of a clinical trial. The following is an example of a protocol and rationale for a contrast-enhanced CT angiography imaging protocol of the thoracic aorta after thoracic aortic endograft repair with retrospective cardiac gating during inspiratory and expiratory breath-holds. Note that the parameters are only examples, and details may vary. At the end, some common challenges of patient recruitment and imaging are presented.

Contrast Injection and Acquisition Timing Iodine contrast injection will be performed via power injector into the antecubital vein of either arm. The quantity of contrast will be dependent on patient body weight, with a ratio of 1.6 mL of contrast per kg of body weight.

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MEDICAL IMAGING PROTOCOLS

Injection rate will be 4 6 mL/s, with a total injection time of 20 30 s, followed by a saline flush of the same rate and volume of 25 40 mL. In order to ensure that the image acquisition is performed during peak lumen enhancement, either a contrast timing bolus or automatic bolus triggering should be used. For a timing bolus, perform a low-dose dynamic scan at the region of interest while injecting 15 mL of contrast, followed by 15 mL of saline flush. Record the time it takes for the maximum attenuation to occur at the region of interest, and then use that time as the delay between the start of contrast injection and image acquisition. For automatic bolus triggering, the CT scanner tracks the attenuation at the region of interest and automatically begins the scan procedure when it detects a rise of 50 Hounsfield units. The scan procedure begins with an 8-s delay so that full contrast enters the field of view prior to actual image acquisition. The actual image acquisition time is 20 30 s and must be performed during a breath-hold.

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The first scan is performed with an inspiratory breath-hold with the first pass of contrast media, and the second acquisition is performed with an expiratory breath-hold B40 s after the end of injection, which coincides approximately with the second pass of contrast through the aorta. During the intervening time between scans, the patient is instructed to breathe normally in order to catch his/her breath in preparation for the more difficult expiratory breath-hold. Note that the second scan is performed without any additional contrast injection and is essentially done for “free” considering that a second “stent delay” scan is often performed to evaluate aortic endograft endoleaks anyway.

Computed Tomography Imaging Parameters Imaging parameters are shown in Table 3.1.

TABLE 3.1 Retrospective Cardiac-Gated CTA Imaging Parameters Start axial position

Superior to the brachiocephalic artery bifurcation into the right subclavian and right common carotid arteries or B5 cm superior to aortic arch

End axial position

Distal descending aorta past the distal end of the thoracic aortic endograft and inferior to the apex of the heart

Field of view

Appropriate for the subject

Scan type

Helical

Axial slice resolution

512 3 512 pixel

Slice collimation/ thickness

# 0.625 mm collimation, # 1.25 mm slice thickness

Reconstruction interval

10 30% overlap

Temporal resolution

Capture $ 10 evenly spaced cardiac phases

Scan delay (contract)

Automatic bolus triggering with 8-s delay

Contrast medium

1.6 mL/kg of body weight

Contrast medium administration

4 6 mL/s via antecubital vein, followed by saline push with same injection rate with 25 40 mL volume

Kilovoltage

120 kVp or as appropriate

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Risk/Benefit To quantify the 3D deformations of the aorta, high-signal, high-resolution, and timeresolved 3D images of the vascular anatomy are essential. Retrospective cardiac-gated CT will provide the data needed for this analysis. To minimize the radiation risk of the study, a dose modulation protocol can be implemented to result in only a small increase of dose when compared to a non-gated acquisition. The ECG dose modulation protocol downregulates the tube current to 4% of the full dose for the non-diagnostic phase of the cardiac cycle. The cardiac-gated CT sequence for this study may increase radiation dose length product by approximately 255 milligray-cm (mGy-cm), which leads to increase of the total radiation exposure by 4 millisieverts (mSv). This is a relative dose increase of approximately 25%, which may vary depending on the patient’s heart rate. As a comparison, increase of exposure by 10 mSv is reported to increase the risk of cancer by 1/2000 or 0.02%. Of note, the natural risk of cancer in the US population is about 20%, and the impact of the additional radiation exposure should be less significant for older patients.

Patient Recruitment and Imaging Challenges Recruiting and consenting patients and successfully executing the study protocol is a complicated dance with many partners including interventionalists, radiologists, imaging technologists, research coordinators, and the patients and their families. The following are some common challenges to patient recruitment and imaging: 1. After a patient candidate is identified, the interventionalist does not respond in time to approve the recruitment of the candidate.

2. A patient candidate is admitted, treated, and scanned immediately after emergent treatment or over the weekend without a chance to recruit into the study. 3. During the consenting process, the patient candidate does not understand the risks of imaging (in which case, they cannot be consented) or declines based on concerns about the imaging procedure. 4. The patient candidate agrees to participate but changes his/her mind after discussing with family members. 5. The patient candidate is identified and fits into the inclusion criteria but his/her creatinine level is too high, precluding iodine contrast injection. 6. When performing breath-holding practice sessions, the patient candidate cannot hold his/her breath long enough. 7. The patient candidate has incompatible medical insurance and decides to perform the imaging procedure at a different facility. 8. The CT scan is executed at a time when the radiologists and imaging technologists familiar with the special imaging protocol are not available (e.g., weekend, vacation, at night). 9. The imaging protocol, particularly respiration breath-holding and lying still, is not properly coached by the imaging technologist or followed by the patient. 10. The field of view does not reach superior enough above the aortic arch to catch the arch vessels or does not reach inferior enough to cover the distal end of the aortic endograft. 11. The intravenous line is not placed properly in the vein, and the iodine contrast leaks out or is injected into muscle tissue instead. Since each patient is only allowed a certain ration of contrast media based on body weight, the injection cannot be repeated. 12. The patient has an erratic heart rate, and problematic cardiac gating causes image artifacts.

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REFERENCES

CONCLUSION To capture vascular motions and deformations, proper medical imaging modalities and protocols must be used. X-ray, CT, ultrasound, and MRI each have benefits and drawbacks in terms of data type, data quality, radiation dose, contrast risk, and ease of acquiring data. In addition, image quality trade-offs can be adjusted to optimize for resolution, signal-to-noise, and radiation exposure. A plethora of strategies to capture motions induced by cardiac pulsatility, respiration, and musculoskeletal motion exists and differs by imaging modality and timescales of motion. Standard clinical protocols are good starting points to develop motion-capture imaging protocols, where special attention should be paid to additional patient risk and patient recruitment and imaging challenges.

References ASTM Standard F2182-11, 2011. Standard test method for measurement of radio frequency induced heating on or near passive implants during magnetic resonance imaging. In: ASTM International, West Conshohocken, PA, 2011. doi:10.1520/F2182-11. ,www.astm.org.. Badea, C., Hedlund, L.W., Johnson, G.A., 2004. Micro-CT with respiratory and cardiac gating. Med. Phys. 31 (12), 3324 3329.

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Frederickson, J.O., Wegmuller, H., Herfkens, R.J., Pelc, N.J., 1995. Simultaneous temporal resolution of cardiac and respiratory motion in MR imaging. Radiology 195 (1), 169 175. Giambuzzi, M., Seitun, S., Salsano, A., Passerone, G., Ferro, C., Santini, F., 2015. Nongated vs electrocardiographygated CT imaging of blunt aortic root rupture in a trauma patient. J. Cardiovasc. Comput. Tomogr. 9 (2), 146 148. Gorcsan, J., Tanaka, H., 2011. Echocardiographic assessment of myocardial strain. J. Am. Coll. Cardiol. 58 (14), 1401 1413. Kolbitsch, C., Ahlman, M.A., Davies-Venn, C., Evers, R., Hansen, M., Peressutti, D., et al., 2017. Cardiac and respiratory motion correction for simultaneous cardiac PET/MR. J. Nucl. Med. 58 (5), 846 852. McFadden, J.T., 2012. Magnetic resonance imaging and aneurysm clips. J. Neurosurg. 117 (1), 1 11. Nitz, W.R., Oppelt, A., Renz, W., Manke, C., Lenhart, M., Link, J., 2001. On the heating of linear conductive structures as guide wires and catheters in interventional MRI. J. Magn. Reson. Imaging 13, 105 114. Pelgrim, G.J., Oudkerk, M., Vliegenthart, R., 2013. Computed tomography imaging of the coronary arteries. In: Baskot, B.G. (Ed.), What Should We Know About Prevented, Diagnostic, and Interventional Therapy in Coronary Artery Disease. IntechOpen. doi:10.5772/54044. ,https://www.intechopen.com/ books/what-should-we-know-about-prevented-diagnosticand-interventional-therapy-in-coronary-artery-disease/ computed-tomography-imaging-of-the-coronary-arteries.. Seibert, J.A., Boone, J.M., 2005. X-ray imaging physics for nuclear medicine technologists. Part 2: X-ray interactions and image formation. J. Nucl. Med. Technol. 33, 3 18.

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C H A P T E R

4

Geometric Modeling of Vasculature Christopher P. Cheng Division of Vascular Surgery, Stanford University, Stanford, CA, United States

When assessed by skilled eyes, medical images are useful for qualitative and semiquantitative inspections that can be effective for diagnosis, treatment planning, and evaluation. However, this assessment is not easily scalable or translatable to other people. In fact, the countless complex features in a medical image can slow down or even obfuscate analysis. In order to communicate how features in a medical image lead to certain clinical or product development decisions or conclusions, especially to people from different fields, this analysis must be repeatable and as objective as possible. Thus quantification is necessary. The first step in quantifying deformation, or geometric changes, is defining the anatomy with geometric modeling. There are four general flavors of models (Gerlee and Lundh, 2016):

particular task, e.g., a small physical model of a building for architectural planning. 3. Abstraction—A theoretical construct to describe phenomena, e.g., a mathematical equation to predict when a tree will grow to a certain height. 4. Conceptual model—A representation of a system to help explain phenomena, for example, Bohr diagram of an atom. In the strictest sense the geometric modeling covered in this chapter is about creating idealization models, specifically to quantify geometries and deformations for diagnostic, device development, and clinical surveillance purposes. However, archetypical and conceptual models of blood vessels are also valuable for teaching and explanation, and abstraction models can be used to predict vascular motion, growth, and remodeling. In other words, we will concentrate on building models for geometric measurements, but do not be surprised if some of the models that result are beautiful, prove useful for teaching concepts, and spur ideas for scientific or clinical predictions.

1. Archetype—An example, usually a typical or nearly perfect example, such as a runway model in a fashion magazine. 2. Idealization—A simplification containing only the most salient features for a

Handbook of Vascular Motion DOI: https://doi.org/10.1016/B978-0-12-815713-8.00004-8

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© 2019 Elsevier Inc. All rights reserved.

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IMAGING PROCESSING SOFTWARE A plethora of software packages is available to build vascular geometric models from medical imaging data. Each has its pluses and minuses in terms of features, userfriendliness, efficiency, accuracy, and precision. But they all have useful capabilities to capture geometries. Since geometric modeling of blood vessels is a relatively niche and technical field, the software packages tend to have relatively long learning curves, similar to any computer-aided modeling software. Over the past two decades, various packages have been developed to build geometric models of blood vessels from medical imaging data for use in running blood flow simulations. The following software packages, predominantly developed by academic groups, are open source and are either free or very inexpensive to purchase: SimVascular (simvascular.github.io, Stanford University, Stanford, California; University of California, Berkeley, California; Open Source Medical Software Corporation, Santa Monica, California). CRIMSON—CardiovasculaR Integrated Modeling and SimulatiON (crimson.software, University of Michigan, Ann Arbor, Michigan).

HemeLB (github.com/UCL/hemelb, University College London, London, United Kingdom). VMTKLab—Vascular Modeling ToolKit Lab (vmtk.org, Orobix, Bergamo, Italy). Historically, software packages were developed to construct geometric models of the vasculature and perform blood flow simulations with finite element analysis. Today, the richness in software functionality enables contributions to understanding hemodynamics and tissue-to-implant forces for disease research, disease diagnosis, treatment planning, and device design and evaluation. For the purpose of quantifying blood vessel deformations, only the first portion of the software workflow is needed (Fig. 4.1). These aforementioned software packages rely on other open-source software, including those that perform image segmentation. The following examples, along with others, specialize in two-dimensional (2D) and threedimensional (3D) image segmentation: ITK-SNAP—Imaging ToolKit-SNAP (itksnap.org, University of Pennsylvania, Philadelphia, Pennsylvania; University of Utah, Salt Lake City, Utah) MITK—Medical Imaging Interaction ToolKit (mitk.org, German Cancer Research Center

FIGURE 4.1 For most existing cardiovascular simulation software packages, the workflow consists of geometric model construction (top row) and finite element simulation (bottom row). For the purposes of geometric analysis for deformation quantification, only the first half of the workflow is needed.

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IMAGE FORMAT AND VIEWING

Division of Medical Image Computing, Heidelberg, Germany) 3D Slicer (slicer.org, Harvard University, Cambridge, Massachusetts) There are also a large number of commercial software packages that provide various features for image viewing, digital measurements, geometric modeling, surgical planning, and clinical decision-making. These are produced either by medical imaging equipment companies (e.g., General Electric, Siemens, Toshiba, and Philips) or stand-alone image processing software companies (e.g., TeraRecon, Vital Images, OsiriX, and Materialize). For basic vascular geometric and deformation measurements, such as performing crosssectional measurements where the exact location of the measurement is not important (e.g., approximate radial pulsatility), only viewer and ruler tools are needed, and geometric modeling is not necessary. The remainder of this chapter focuses on 3D geometric model

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construction, which is needed for more precise and complex quantification. In addition, note that the following workflow is just an example, and there may be variations between software packages and personal preferences.

IMAGE FORMAT AND VIEWING Before beginning the geometric modeling process, medical images need to be imported into the software package of choice. The standard format is DICOM (Digital Imaging and Communications in Medicine), and in order to maintain patient confidentiality, the patient identifying information is commonly stripped from the image header. The art of viewing 3D medical images can be finicky and may require postprocessing and various viewpoints to correctly identify precise geometries. Thus the image viewing software must be capable of brightness and contrast control (Fig. 4.2), as

FIGURE 4.2

Example of computed tomography images of the thorax with poor contrast and brightness (left) and good contrast and brightness (right) for visualizing the thoracic aorta and branch arteries.

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well as multiple simultaneous imaging cut planes (Fig. 4.3).

FIGURE 4.3 Example of 3D computed tomography image of the thorax with simultaneous 2D cuts in the coronal and sagittal planes. 2D, Two-dimensional; 3D, three-dimensional.

IMAGE SEGMENTATION AND EDITING There are two main approaches to image segmentation for vascular structures: (1) 2D cross-sectional lumen segmentations along approximate vessel centerlines and (2) direct 3D volumetric lumen segmentation. For the first technique, approximate lumen centerlines are manually digitized, and then 2D cross-sectional segmentations are performed perpendicular to those centerlines (Wang et al., 1999; Wilson et al., 2001; Choi et al., 2009; Suh et al., 2014). To manually select the approximate centerline, all three cut planes (coronal, sagittal, and axial) may need to be utilized to best track the path of the blood vessel of interest from one end to the other (Fig. 4.4). The manual centerline needs to be relatively smooth for robust perpendicular cross-sectional segmentation, so this step may require manual adjustment of particular path points and smoothing functions (Fig. 4.5). In

FIGURE 4.4 Depiction of approximate centerline of the thoracic aorta being manually digitized. The initial centerline path is initiated at the aortic valve (left), extended across the aortic arch (middle), and continued down the descending aorta (right).

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FIGURE 4.5 The vessel centerline paths need to be relatively smooth for proper cross-sectional slicing, so a crooked path (left) can have its control points manually adjusted (middle) to yield a smoother centerline path (right).

addition, in order to query a perpendicular cross section on any arbitrary position along the centerline, the path can be populated with interpolated points with techniques such as cubing splining. If the anatomy of interest encompasses multiple blood vessels, then multiple manual centerlines need to be created. For daughter vessels that branch off of the main vessel, it is not critically important to find the exact location of the branch ostium at this point. The branch path will merely be used as a reference path to guide cross-sectional segmentations for the branch vessel, so just make sure the branch vessel centerline has sufficient coverage to capture the branch vessel segment of interest. An arbitrary number of branch paths can be created, and first-generation branch vessels can have their own second-generation branches (Fig. 4.6). Now, using the individual manual centerline paths, cut planes perpendicular to those paths can be used for 2D segmentation of the lumen cross-sections (Fig. 4.7). 2D

FIGURE 4.6 Example of centerline paths of the thoracic aorta with right and left coronary, brachiocephalic, left common carotid, left subclavian, and distal intercostal artery branch paths. Note that the first-generation brachiocephalic branch path bifurcates into second-generation right subclavian and right common carotid branch paths.

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segmentation can be performed with a variety of methods, with the simplest ones based on signal threshold or active contours. Many more complex techniques exist that accommodate for multiple colors and context, such as clustering methods; however, these techniques are beyond the scope of this book.

FIGURE 4.7 Depiction of a cut plane perpendicular to the thoracic aorta centerline path at the ascending aorta.

Signal thresholding simply identifies the pixels that are above or below a certain threshold value and separates those pixels from the rest of the image. While thresholding is a very simple and efficient operation, it sometimes requires manual adjustment when multiple boundaries are generated. A common form of active contours is the level-set method, where a single closed curve is automatically generated and can be enhanced with geometric constraints in order to avoid segmentation “leaking” (Fig. 4.8). Manual adjustments to the cross-sectional segmentations and smoothing may be necessary when these automatic techniques make obvious mistakes. In the cases of complex geometry or noisy imaging data, it is often more efficient to manually define the lumen boundaries right off the bat. A sequence of 2D segmentations can then be created along a vessel and subsequently lofted into a solid model (Fig. 4.9, top row). After performing this set of operations for multiple vessel paths, the multiple solid models can be unioned to form a single geometric model (Fig. 4.9, bottom row).

FIGURE 4.8 Example of two-dimensional level-set segmentation without curvature constraint (left) and with curvature constraint (right). Curvature constraint is useful for preventing “leaking” into branch vessels. From Choi, G., Cheng, C.P., Wilson, N.M., Taylor, C.A., 2009. Methods for quantifying three-dimensional deformation of arteries due to pulsatile and nonpulsatile forces: implications for the design of stents and stent grafts. Ann. Biomed. Eng. 37 (1), 14 33, Figure 3.

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FIGURE 4.9 With a series of perpendicular cross-sectional contours defined along a thoracic aortic endograft (top left), the contours can be lofted together to form a surface encapsulating the entire endograft volume (top right). Analogously, complete sets of perpendicular cross-sectional contours defined along multiple blood vessels (bottom left) can be lofted and unioned to form a complete model of a dissected and aneurysmal thoracic aorta with implanted thoracic aortic endograft and arch branches (bottom right).

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FIGURE 4.10

Coronary artery geometric models generated by 3D level-set segmentation methods. Edge-based level set (left, red), threshold-based level set (middle, dark gray), and threshold-based level set with lower threshold value (right, light gray). 3D, Three-dimensional. Adapted from Choi, G., Xiong, G., Cheng, C.P., Taylor, C.A., 2014. Methods for characterizing human coronary artery deformation from cardiac-gated computed tomography data. IEEE Trans. Biomed. Eng. 61 (10), 2582 2592, Figure 11.

For direct 3D volumetric segmentation, the process can be much more automatic; however, it requires more complex and computationallyexpensive segmentation algorithms. In addition, due to image signal noise and imperfect lumen contrast, these techniques are usually less robust than 2D segmentation methods and still require varying levels of user intervention. As with 2D segmentation, the predominant 3D segmentation methods utilized for medical images are based on signal thresholding and active contours. To produce sufficiently smooth surfaces for precise quantification, active contour level-set segmentations,

including threshold- and edge-based methods, are preferable (Fig. 4.10) (Yushkevich et al., 2006; Choi et al., 2014). At present, these 3D segmentation techniques are not robust enough to be truly automatic for the segmentation of blood vessels due to image leaking and computational stability issues. Medical images are simply too noisy and contain too much variety in signal (e.g., blood, healthy wall, thrombus, and calcium) (Fig. 4.11). However, these 3D segmentation techniques can be utilized for visualization, approximate quantification, or even as the starting point for centerline extraction.

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CENTERLINE EXTRACTION

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FIGURE 4.11 Examples of inaccurate automatic image segmentation of the ascending aorta. From original computed tomography images (left), surrounding structures, including vessel wall tissue, connective tissue, and other blood vessels, may be inadvertently included (right).

CENTERLINE EXTRACTION Many vascular geometric features and deformations are quantified based on lumen centerline geometry. Several of the open-source and commercial imaging processing software packages include automatic centerline extraction

capabilities starting from 3D segmentations (Fig. 4.12). However, for precise centerlines that truly represent the geometric centerlines of the blood vessel lumens, some amount of intervention or additional steps are usually required. For example, if the blood vessel contains any

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FIGURE 4.12 Examples of automatic centerline extraction from geometric models created from 3D image segmentations. Note that there are perturbations to the centerline from branch vessel ostia (blue dots). 3D, Three-dimensional.

plaques or side branches and is not a perfectly smooth tubular structure, an automatically computed centerline may misrepresent the true centerline. To accommodate for these real-life perturbations, adjustments can be made either manually or algorithmically based on the 3D surface. Recalling from the previous section, the 2D segmentations that were computed on planes perpendicular to a manually-selected centerline can be free from the influence of perturbations (e.g., branches and plaques) by (1) using curvature constraint with level-set segmentation, (2) manually digitizing the contour with knowledge of the problem features, or (3) avoiding the regions with problem features during contour segmentation. With a clean set of perpendicular 2D contours, the mathematical centroids of these contours can be calculated and joined to form a true centerline path (Choi et al., 2009; Suh et al., 2014) (Fig. 4.13).

What if you want to compute true vessel lumen centerlines from direct 3D segmentations in a more automated fashion? In one described method, an initial path on the surface of the blood vessel is created using Dijkstra’s algorithm, which finds the shortest path between the proximal and distal ends on the 3D segmented surface (i.e., geodesic path) (Choi et al., 2014). Next, cross-sectional contours are created along that geodesic path oriented such that they contain minimum cross-sectional areas, which should approximate perpendicular cross-sections. The mathematical centroids of these contours are then connected to form a centerline path. In order to correct for centerline deviations based on vascular calcium or side branches, a cross-sectional circularity threshold can be established to exclude non-circular contours (Fig. 4.14). Regardless of the method for centerline path extraction, the centerlines are still subject to crookedness inherent to pixel size, partial

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FIGURE 4.13 Depiction of establishing the true centerline path of a thoracic aorta. From 3D computed tomography data of a thoracic aorta treated with an ascending aortic vascular graft (A), approximate centerlines can be manually created (B). Two-dimensional lumen contours perpendicular to the centerlines (C) can then be used to calculate contour centroids (D), which can then be joined to create true centerline paths (E). 3D, Three-dimensional. From Suh, G., Beygui, R.E., Fleischmann, D., Cheng, C.P., 2014. Aortic arch vessel geometries and deformations in patients with thoracic aortic aneurysms and dissections. J. Vasc. Interv. Radiol. 25 (12), 1903 1911, Figure 1.

FIGURE 4.14

Depiction of automatic centerline construction from a computer-generated 3D surface. First, initial centroids of cross-sectional contours are calculated based on a geodesic path on the surface (left); note the mismatch of the centroids (dots) from the true centerline (thin gray line) at the locations of plaque and branch vessel. Next, the centroids that originate from cross-sectional contours that have circularity ,0.9 are excluded (middle). Finally, the remaining centroids are smoothed to arrive at an automatically calculated centerline that matches the true centerline (right). 3D, Three-dimensional. From Choi, G., Xiong, G., Cheng, C.P., Taylor, C.A., 2014. Methods for characterizing human coronary artery deformation from cardiac-gated computed tomography data. IEEE Trans. Biomed. Eng. 61 (10), 2582 2592, Figure 4.

volume effects, and noisy medical imaging data. Fourier smoothing algorithms, which can remove spurious, high-frequency modes while maintaining accuracy of the centerline, have

been developed to compensate for these issues (Choi et al., 2009) (Fig. 4.15). The trick is systematically choosing the optimal number of Fourier frequency modes with

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FIGURE 4.15 High-frequency perturbations in the unsmoothed centerline path (left) can be eliminated with Fourier smoothing (right) on an example abdominal aorta. From Choi, G., Cheng, C.P., Wilson, N.M., Taylor, C.A., 2009. Methods for quantifying three-dimensional deformation of arteries due to pulsatile and nonpulsatile forces: implications for the design of stents and stent grafts. Ann. Biomed. Eng. 37 (1), 14 33, Figure 3.

which to smooth the centerline. For this technique, we want to choose the minimum number of Fourier modes that maintains a sufficient level of accuracy while eliminating spurious oscillations. In one study, increasing numbers of Fourier modes were used to reconstruct the centerline while comparing the reconstructed version to the original version (Choi et al., 2009). The number of Fourier modes was increased until the centerline points “converged” to an accurate solution, where the convergence rate value was defined as the maximum change in distance between corresponding smoothed and original centerline coordinates (Fig. 4.16). In this study, it was determined that 0.1 mm was a consistently tenable convergence rate stopping value, meaning that Fourier modes were increased until the

most sensitive point on the centerline path improved by less than 0.1 mm. The accuracy of the smoothed centerline can be confirmed by making sure that (1) the average distance between the smoothed and original centerline points is small, and (2) no centerline curvature values, as calculated by the Frenet curvature formula, are above the inverse of the blood vessel radius (Choi et al., 2009). For the first criterion, a maximum threshold value can be related back to the pixel size, for example, the smoothed centerline points are on average less than 25% of a pixel length shifted from their original positions. For the second criterion, a maximum curvature threshold is defined by the radius of the blood vessel because it does not make sense geometrically to have centerline radius of curvature

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FIGURE 4.16 Depiction of an algorithm to choose the optimal number of Fourier modes for superficial femoral artery centerline smoothing. The original centerline based on cross-sectional contour centroids includes noise-generated high-frequency perturbations (A). The centerline is constructed from increasing numbers of Fourier modes, using 10 modes (B), 20 modes (C), 30 modes (D), 40 modes (E), and 50 modes (F). As the number of Fourier modes increases, the centerline path gets more accurate. In the range of lower modes (B D), visual improvements in centerline path can be seen; however, in the range of higher modes, centerline differences are not visually detected (D F). Based on a convergence rate cost function that tracks the maximum change in distance between corresponding smoothed and original centerline coordinates, and selecting a maximum convergence rate threshold of 0.1 mm, the optimal number of Fourier modes in this case is 48 (bottom graph). From Choi, G., Cheng, C.P., Wilson, N.M., Taylor, C.A., 2009. Methods for quantifying three-dimensional deformation of arteries due to pulsatile and nonpulsatile forces: implications for the design of stents and stent grafts. Ann. Biomed. Eng. 37 (1), 14 33, Figure 4.

smaller than the radius of the vessel crosssection itself.

OPTIMIZATION OF GEOMETRIC MODELING At this point, it is probably obvious that constructing accurate and useful 3D geometric

models is a non-trivial procedure that takes specialized software and time-consuming manual intervention. Unfortunately, this is not yet the end of the story. In a study that investigated the impact of geometric model quality on quantification of blood vessel centerline arclength, centerline curvature, and crosssectional geometry, it was found that varying levels of model quality were required for

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capturing accurate vascular geometry, depending on the complexity of the anatomy (Cheng et al., 2018). This study utilized the technique of centerline construction and perpendicular cross-sectional 2D lumen segmentations. For this technique, the quality of the geometric model is determined by the (1) interval spacing between the 2D lumen segmentations and (2) number of iterations of perpendicular segmentation and centerline extraction (Fig. 4.17). The amount of user and computational effort it takes to construct a 3D geometric model is approximately proportional to the spatial sampling rate between 2D segmentations and the number of perpendicular

segmentation and centerline extraction iterations. For example, the effort required to construct a 3D vascular model with 0.25 cm segmentation spacing and 3 iterations of perpendicular segmentation and centerline extraction is approximately 24 3 that of constructing a model with 2 cm segmentation spacing and 1 iteration of perpendicular segmentation and centerline extraction. Considering the high cost of 3D geometric model refinement, it is crucial to determine the minimum amount of effort needed to capture the important geometric features required for deformation quantification. While more finely spaced cross-sectional contours may more precisely capture the

FIGURE 4.17 Perpendicular cross-sectional 2D lumen segmentations of a thoracic aorta were constructed at 2, 1, 0.5, and 0.25 cm intervals (top row). Centerline lumen paths can be formed from the mathematical centroids of these cross-sectional lumen contours, from which new perpendicular cross-sectional segmentations can be constructed. Three iterations of perpendicular lumen segmentation and centerline extraction are shown (bottom row). 2D, Two-dimensional. From Cheng, C.P., Zhu, Y.D., Suh, G., 2018. Optimization of 3D geometric modeling parameters for geometric precision and modeling efficiency for healthy and diseased aortas. Comput. Methods Biomech. Biomed. Eng. 21 (1), 65 74, Figure 2.

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FIGURE 4.18 Examples of four major types of thoracic aortic morphology, derived from computed tomography angiography, including healthy aorta without cross-sectional variation (left), tortuous aorta without cross-sectional variation (second from left), aneurysmal aorta with diametric variation (second from right), and dissected aorta with cross-sectional variation of the true lumen shown in dark gray (right). Adapted from Cheng, C.P., Zhu, Y.D., Suh, G., 2018. Optimization of 3D geometric modeling parameters for geometric precision and modeling efficiency for healthy and diseased aortas. Comput. Methods Biomech. Biomed. Eng. 21 (1), 65 74, Figure 3.

vascular anatomy, it is time consuming and completely unnecessary in straight tubular blood vessels. In addition, extra contours that are too closely spaced may add spurious oscillations to the centerline path, and need to be removed during post-processing anyway (Choi et al., 2009). For cross-sectional geometry quantification, the required amount of precision of cross-section perpendicularity is paramount. This potentially motivates multiple iterations of perpendicular lumen segmentation and centerline extraction. Experiments with varying crosssectional contour intervals and varying number of iterations of perpendicular lumen segmentation and centerline extraction were conducted on examples of four types of thoracic aortic morphology: (1) healthy, smooth aorta without cross-sectional variation, (2) tortuous aorta

without cross-sectional variation, (3) aneurysmal aorta with diametric variation, and (4) dissected aorta with cross-sectional variation of the true lumen (Cheng et al., 2018) (Fig. 4.18). All four anatomies underwent 3D geometric model construction with 2, 1, 0.5, and 0.25 cm cross-sectional interval spacings, and 1, 2, and 3 iterations of perpendicular lumen segmentation and centerline extraction (Cheng et al., 2018). It was found that the requirements for interval spacing of cross-sectional contours and number of iterations of perpendicular lumen segmentation and centerline extraction were highly dependent on the aortic morphology and the geometric quantity of interest. Table 4.1 shows the recommended refinement of modeling parameters that result in converged solutions.

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TABLE 4.1 Recommended Intervals of Cross-Sectional Contour Spacing and Iterations of Perpendicular Lumen Segmentation and Centerline Extraction for Accurate and Efficient 3D Geometric Model Construction of Four Major Thoracic Aortic Morphologies (Interval, Iteration)

Centerline Arclength

Centerline Curvature

Cross-Sectional Geometry

Healthy aorta

2 cm, 1 iteration

2 cm, 1 iteration

1 cm, 1 iteration

Tortuous aorta

1 cm, 1 iteration

1 cm, 1 iteration

1 cm, 2 iterations

Aneurysmal aorta

1 cm, 1 iteration

1 cm, 2 iterations

1 cm, 3 iterations OR 0.5 cm, 2 iterations

Dissected aorta

1 cm, 1 iteration

1 cm, 2 iterations

0.5 cm, 2 iterations

Healthy—Smooth, healthy aorta without cross-sectional variation. Tortuous—Tortuous aorta without cross-sectional variation. Aneurysmal—Aneurysmal aorta with diametric variation. Dissected—Dissected aorta with cross-sectional variation of the true lumen. Interval—Interval spacing of cross-sectional contours. Iteration—Number of iterations of perpendicular lumen segmentation and certerline extraction.

IDENTIFYING BRANCH VESSEL OSTIA The geometric models resulting from the techniques outlined in this chapter can be utilized for visual inspection, creating 3D meshes for finite element modeling, constructing physical models of the vasculature for benchtop testing or educational purposes, and of course, geometric quantification. To define deformations, that is, change in geometric features, multiple geometric models at different physiologic states are necessary. In addition, it is important to establish fiducial markers in order to define the locations where the deformations are occurring. As described in the chapter on medical imaging, useful fiducial markers include branch vessels, bifurcations, embedded calcium from atherosclerosis, discrete diametric transitions (e.g., aneurysm or sinus), and

features created by extravascular structures (e.g., ligamentum arteriosum at the aortic isthmus). The most readily available of these markers, and perhaps the most difficult to define precisely, is the exact point of vessel branching or bifurcation. The identification of this point is especially tricky when the branch ostium is large, non-circular, and/or its location is somewhat ambiguous. When surface geometry of the vasculature is of interest, then the boundary of the ostium is important, whereas when centerline geometry is of interest, the centroid of the ostium needs to be determined. To identify the surface boundary of the ostium, one reliable method is to track along the centerline of the main vessel path with very fine steps, and to find the perpendicular crosssectional slice on which the branch vessel just connects to the main vessel (Fig. 4.19).

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FIGURE 4.19 Pictorial depiction of identifying the surface boundary of the LCCA branch vessel ostium. Crosssectional slices (green squares) are tracked perpendicular to the centerline of the thoracic aorta (red line). Cross-sections are shown proximal to the LCCA (A), sliced through the LCCA (B), just at the surface boundary of the LCCA ostium [(C), white arrow and δ symbol], and distal to the LCCA (D). LCCA, Left common carotid artery. Adapted from Lundh, T., DiGiacomo, P., Suh, G., Cheng, C.P., 2018. A Lagrangian cylindrical coordinate system for characterizing dynamic surface geometry of tubular anatomic structures. Med. Biol. Eng. Comput. 56 (9), 1659 1668, Figure 2.

When vessel centerlines are the geometric structures of interest, then the centroid of the branch ostium must be determined. There are many ways to accomplish this task, and they all require careful inspection of multiple 2D planes oriented in 3D space. For example, an axial slice perpendicular to the main vessel centerline is selected at the level of a branch vessel (Fig. 4.20A). On that axial slice, two lines are selected, one cutting across the branch vessel (sagittal guide), and another perpendicular to the sagittal guide cutting

through the midpoint of the ostium (coronal guide). Next, slices are taken perpendicular to the sagittal guide, and the one best representing the middle of the branch ostium is selected (Fig. 4.20B). Slices perpendicular to the coronal guide are then used to identify the best branch vessel lumen contour that represents the ostium (Fig. 4.20C). Finally, the centroid of that ostium contour is projected onto the main vessel centerline to mark the axial location of the branch ostium (Fig. 4.20D).

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FIGURE 4.20 Depiction of the process of identifying the centroid of a branch vessel ostium. On an axial plane perpendicular to the main vessel, “sagittal” and “coronal” guidelines were chosen that cut across and through the midpoint of the branch vessel, respectively (A). Along the sagittal guideline, contours are used to identify the midpoint of the branch ostium (B). With the “sagittal” slice through the midpoint of the branch ostium, perpendicular “coronal” slices in relation to that “sagittal” slice are then used to identify the location best representing the branch ostium (C). Finally, the centroid of the branch ostium is then projected onto the main vessel centerline to identify the axial location of the branch ostium (D). From Choi, G., Cheng, C.P., Wilson, N.M., Taylor, C.A., 2009. Methods for quantifying three-dimensional deformation of arteries due to pulsatile and nonpulsatile forces: implications for the design of stents and stent grafts. Ann. Biomed. Eng. 37 (1), 14 33, Figure 5.

MODEL COREGISTRATION Coregistration is sometimes a necessary preliminary step for quantifying relative motion of structures with respect to the coregistered structure. Vessel ostia, as described in the

previous section, are good material points of coregistration. For example, with careful coregistration of the celiac artery on the abdominal aorta in abdominal aortic aneurysm patients, it is possible to visualize and quantify how respiration displaces the visceral arteries (Fig. 4.21).

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FIGURE 4.21 Visualization of celiac, superior mesenteric, and renal artery deflection from expiration (red) to inspiration (yellow) phases during the respiratory cycle in small abdominal aortic aneurysm patients. The abdominal aorta from the two respiratory phases is coregistered at the celiac artery ostium such that deflection of the visceral arteries can be intuitively visualized.

These types of images are also extremely powerful for communicating concepts of vessel motion for product development and regulatory submission. Another reason for image coregistration is to glean 3D data from multiple 2D images. The reason for this is that it is often better or easier to acquire 2D images than 3D images. For example, a 3D computed tomography image requires 10 100 3 the X-ray radiation as compared to a 2D plain film. Or, if a patient is undergoing a minimally invasive procedure in a catheterization lab, then they are already in position for 2D X-ray fluoroscopy as compared to needing a separate appointment and imaging session to get a 3D computed tomography scan. It turns out that if two 2D projection images of the same object are from sufficiently different view angles, and the two images can be coregistered, then extracting 3D information is possible via epipolar geometry.

For example, in the case of superficial femoral artery stents imaged with 2D X-ray fluoroscopy from two orthogonal views (coronal and sagittal), the centerline in 3D space can be reconstructed (Fig. 4.22). The evenly spaced strut rings and bridge elements on the stents can be used as periodic fiducial markers for coregistration of the two image views (Robertson et al., 2008). First, the bridge gaps between the strut rings are digitized on each of the two stent edges for both the coronal and sagittal views. Next, centerline points are computed as the midpoint between paired edge points such that there are two complete centerlines, one each from the coronal and sagittal views. Finally, the two centerlines from the two orthogonal views are combined in 3D space using epipolar geometry techniques to reconstruct a 3D centerline. This 3D centerline can then be used to quantify geometry and be compared with other reconstructed 3D centerlines to quantify deformation.

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FIGURE 4.22 Reconstruction of stent centerline in 3D space from two orthogonal (coronal and sagittal) 2D projection images. After scaling the two images, stent edge lines from each view are created from digitized points between stent rings. The pairs of edge line points are averaged to calculate centerline points, and then the centerlines from the two orthogonal views are used to reconstruct the true centerline in 3D space using epipolar geometry techniques. 2D, Twodimensional; 3D, three-dimensional.

VESSEL SURFACE MODELING While the majority of this chapter has described the process of 3D geometric modeling, and how to extract fiducial markers and perform coregistration from these models, these 3D geometric models do not enable full characterization of the surface geometry and deformation. The centerlines, on the other hand, are described analytically with cubic splines and can be used to easily calculate curvature and bending deformation. In order to enable robust surface geometry and deformation quantification, the surface must be described explicitly. Extensive research has been performed in this area, and robust

methods have been developed to automatically model blood vessel surfaces (Fig. 4.23) (Shum et al., 2011). Specific attention to material points on the vessel surface must be paid in order to quantify deformation at precise locations. To achieve this, a Lagrangian cylindrical coordinate system can be used to characterize arbitrary tubular structures. Creating a Lagrangian cylindrical coordinate system requires defining continuous coordinates in the longitudinal and angular directions which are referenced to material points on the blood vessel surface (Lundh et al., 2018). This can be accomplished by taking longitudinally sampled cross-sectional contours of a blood vessel,

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FIGURE 4.23

From cross-sectional image segmentations (left), interpolation is used to populate points on the surface (second from left). From these surface points a coarse mesh topology is created (second from right), and after polygon smoothing operations, a final topology is constructed (right). From Shum, J., Xu, A., Chatnuntawech, I., Finol, E.A., 2011. A framework for the automatic generation of surface topologies for abdominal aortic aneurysm models. Ann. Biomed. Eng. 39 (1), 249 259, Figure 1.

FIGURE 4.24 Defining a Lagrangian cylindrical coordinate system to characterize the surface of a tubular structure. Cross-sectional contours, Si, are used to define contour centroids, Ci, which in turn are used to define the longitudinal dimension, σ (left). The circumferential points around the contours are used to define the angular dimension, θ, with respect to reference points, Yi, as derived from the branch vessel ostium, δ (right). The surface function, r(σ, θ), is defined as the radial position of the vessel surface at every longitudinal and angular combination. From Lundh, T., DiGiacomo, P., Suh, G., Cheng, C.P., 2018. A Lagrangian cylindrical coordinate system for characterizing dynamic surface geometry of tubular anatomic structures. Med. Biol. Eng. Comput. 56 (9), 1659 1668, Figure 1.

as described in the “Image Segmentation and Editing” section, and using the centerline points of the contours to define the longitudinal dimension (σ) in the cylindrical coordinate system (Fig. 4.24). Next, the points around the circumference of each of the contours are used to define the angular dimension (θ). To provide an initial reference point with which to define a material point in the angular direction, a fiducial marker, such as a branch artery ostium, can be used (Fig. 4.19). This reference point is then projected proximally and distally

so that each contour has its own reference point, thus creating a reference curve that spans the length of the blood vessel on its surface. Using the longitudinal σ and angular θ dimensions, the cylindrical surface function r (σ, θ) is defined as the radius position of the vessel surface at every longitudinal and angular combination. Interpolation is used in both longitudinal and angular directions to provide a continuous Lagrangian description of the entire surface. In the context of characterizing vessel surface deformations with respect to

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time, a time variable is added to the surface function r(σ, θ, t).

CONCLUSION From medical imaging data a variety of image processing, image segmentation, and optimization methods can be utilized to generate accurate geometric models of the vasculature. Many software packages are available for geometric model construction, with extensive capabilities in image viewing, 2D and 3D lumen segmentation methods, and centerline extraction. To leverage these geometric models for geometric and deformation quantification, supplemental methods for modeling optimization, branch vessel ostium identification, image coregistration, and surface modeling may be necessary.

References Cheng, C.P., Zhu, Y.D., Suh, G., 2018. Optimization of 3D geometric modeling parameters for geometric precision and modeling efficiency for healthy and diseased aortas. Comput. Meth. Biomech. Biomed. Eng. 21 (1), 65 74. Choi, G., Cheng, C.P., Wilson, N.M., Taylor, C.A., 2009. Methods for quantifying three-dimensional deformation of arteries due to pulsatile and nonpulsatile forces: implications for the design of stents and stent grafts. J. Endovasc. Ther. 16 (5), 531 538. Choi, G., Xiong, G., Cheng, C.P., Taylor, C.A., 2014. Methods for characterizing human coronary artery

deformation from cardiac-gated computed tomography data. IEEE Trans. Biomed. Eng. 61 (10), 2582 2592. Gerlee, P., Lundh, T., 2016. Scientific Models: Red Atoms, White Lies and Black Boxes in a Yellow Book. Springer International Publishing, Switzerland. Lundh, T., DiGiacomo, P., Suh, G., Cheng, C.P., 2018. A Lagrangian cylindrical coordinate system for characterizing dynamic surface geometry of tubular anatomic structures. Med. Biol. Eng. Comput. 56 (9), 1659 1668. Robertson, S.W., Cheng, C.P., Razavi, M.K., 2008. Biomechanical response of stented carotid arteries to swallowing and neck motion. J. Endovasc. Ther. 15, 663 671. Shum, J., Xu, A., Chatnuntawech, I., Finol, E.A., 2011. A framework for the automatic generation of surface topologies for abdominal aortic aneurysm models. Ann. Biomed. Eng. 39 (1), 249 259. Suh, G., Beygui, R.E., Fleischmann, D., Cheng, C.P., 2014. Aortic arch vessel geometries and deformations in patients with thoracic aortic aneurysms and dissections. J. Vasc. Interv. Radiol. 25 (12), 1903 1911. Wang, K.C., Dutton, R.W., Taylor, C.A., 1999. Improving geometric model construction for blood flow modeling: geometric image segmentation and image-based model construction for computational hemodynamics. IEEE Eng. Med. Biol. 18, 33 39. Wilson, N., Wang, K., Dutton, R.W., Taylor, C.A., 2001. A software framework for creating patient specific geometric models from medical imaging data for simulation based medical planning of vascular surgery. Lect. Notes Comput. Sci. 2208, 449 456. Yushkevich, P.A., Piven, J., Hazlett, H.C., Smith, R.G., Ho, S., Gee, J.C., et al., 2006. User-guided 3D active contour segmentation of anatomic structures: Significantly improved efficiency and reliability. NeuroImage 31, 1116 1128.

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C H A P T E R

5

Quantifying Vascular Deformations Christopher P. Cheng Division of Vascular Surgery, Stanford University, Stanford, CA, United States

and surface curvature. As explained in Chapter 3, Medical Imaging Modalities and Protocols, different imaging modalities and techniques are suited to capture different types of motion and deformation. Similarly, there are different techniques for separating and quantifying these different types of deformation. This chapter heavily leverages the concepts described in Chapter 4, Geometric Modeling of Vasculature.

Do you have a favorite meal? Mine is lobster bisque with truffle oil, duck confit with a side of saute´ed pea sprouts, and foie gras with drizzled honey. These courses would be paired with a vintage Champagne, Grand Cru red Burgundy, and a 10- to 15-year-old Premier Cru Sauternes, respectively. But does that mean I would like all these ingredients to be put into a blender and made into a brown smoothie? While blood vessels move and deform in complex, multimodal ways, it is very difficult to quantify and utilize these motions simultaneously, just like it would be pretty gross to drink a shellfish
meat
veggie
liver
wine smoothie. In fact, it is often much more instructive to separate the modes of motion so that they can be used to query specific physiological phenomena or help understand how device durability is related to a particular type of motion. The primary types of vascular deformations fall into the categories of cross-sectional, axial length, bending, branch angulation, axial twist,

Handbook of Vascular Motion DOI: https://doi.org/10.1016/B978-0-12-815713-8.00005-X

DEFINING AND UTILIZING FIDUCIAL MARKERS Branch vessel ostia are the most useful fiducial markers in the vasculature because they are relatively plentiful and represent material points of tissue. The easiest way to define a branch ostium is either by the centroid of the ostium itself, or by the projection of that ostium centroid onto the main vessel centerline (Fig. 5.1).

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FIGURE 5.1 A branch ostium can be defined either as the branch starting point on the branch vessel centerline (left) or that point projected onto the main vessel centerline path (right). From Cheng, C.P., Choi, G., Herfkens, R.J., Taylor, C.A., 2010. The effect of aging on deformations of the superficial femoral artery due to hip and knee flexion: potential clinical implications. J. Vasc. Interv. Radiol. 21 (2), 195
202, Figure 3.

In some situations the centroid data at a branch ostium, or other fiducial marker, can contain error due to noise from medical imaging and/or geometric model construction. In these cases, it may make sense to use the adjacent surface data of the geometric model to define the fiducial marker. For example, a three-dimensional (3D) shape-matching algorithm can be used to compare a particular fiducial marker from two geometric models representing two anatomic states, thus coregistering the two models at that fiducial marker (Fig. 5.2). The process involves translational and rotational transformations of the fiducial feature to achieve optimal coregistration (Choi et al., 2014). This optimization utilizes the conjugate gradient method based on a cost function defined by the average distance deviation between the reference and deformed configurations. With fiducial markers defined and coregistered, vascular deformations between two anatomic states can be calculated. These include

axial length and axial twist deformations. In addition, the identification of fiducial markers aids in the localization of cross-sectional, bending, and branch angle deformations. Another powerful use for fiducial markers is to define vessel segments for averaging. There are dramatic variations in blood vessel deformation among patients and even along the length of a single vessel in an individual person. There is also highly variable anatomy in terms of number of branch vessels, location of branch vessels, and distance between branch vessels. Thus in order to enable statistical analysis of deformation metrics in a population, a consistent method of parsing vessel segments must be created. For example, if deformation variation along a vessel is desired, the vessel can be broken into proximal, middle, and distal thirds. However, since patients have varied branch anatomy, the deformations need to be computed for these thirds using a method such as arclength-based, linear-weighted averages

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CROSS-SECTIONAL DEFORMATION

FIGURE 5.2 Example of a 3D shape-matching algorithm minimizing the average distance between reference and deformed configurations on a branching coronary artery. The method is able to coregister complex nontubular shapes, such as bifurcations and branch ostia. 3D, Three-dimensional. Adapted from Choi, G., Xiong, G., Cheng, C.P., Taylor, C.A., 2014. Methods for characterizing human coronary artery deformation from cardiac-gated computed tomography data. IEEE Trans. Biomed. Eng. 61 (10), 2582
2592, Figure 11.

(Cheng et al., 2010). Specifically, average deformation values for the proximal, middle, and distal thirds of the blood vessel can be computed by weighting the regional deformations between branch points by their respective arclengths (Fig. 5.3). Note that as vessel segments get shorter, that is, the fiducial markers get closer together, the limitations of image signal and resolution make the measurements noisier. Thus, a good rule of thumb is to exclude vessel segment lengths that are less than the diameter of the blood vessel of interest, or less than 5
10 pixels wide.

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FIGURE 5.3 For deformation metrics that require proximal and distal fiducial markers, regional averages can be approximated by using weighted averaging based on arclengths between blood vessel segments. In this example the deformation values εn for individual vessel segments can be averaged by weighting their values based on respective segment arclengths, and then regionalizing them into top, middle, and bottom thirds. From Cheng, C.P., Choi, G., Herfkens, R.J., Taylor, C.A., 2010. The effect of aging on deformations of the superficial femoral artery due to hip and knee flexion: potential clinical implications. J. Vasc. Interv. Radiol. 21 (2), 195
202, Figure 5.

CROSS-SECTIONAL DEFORMATION Cross-sectional geometries and deformations are generally quantified from perpendicular two-dimensional (2D) planar images and lumen contours. The locations of these cross sections can be indexed to fiducial marker locations such as the distal edge of an aneurysm (Fig. 5.4). In the cases where the location of quantification only needs to be approximate, such as when the deformation is assumed to be relatively

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FIGURE 5.4 Cut plane location precision is dependent on the anatomy and physiology. For a smooth, healthy descending aorta, the location of cross-sectional localization can be approximate (left); however, for an aneurysmal descending aorta with varying diameter and tissue properties, localization should be indexed by a particular distance from a fiducial marker, such as the distal edge of the aneurysm (right).

FIGURE 5.5 Effective radius and diameter can be calculated directly from the contour area assuming a circular shape (left), while circumferentially-varying radii and diameters can be calculated for each angular position (right, dotted line).

consistent along a certain region, fiducial marker indexing is less important. Cross-sectional deformations are usually defined as percent changes and are thus unitless. From the lumen contour coordinates, crosssectional area can be found and effective radius and diameter are simply calculated assuming a circular shape. To capture circumferential variation, radii and diameters can be quantified at any arbitrary angular position (Fig. 5.5). Once the circumferential variation in diameter is tracked, then the maximum diameter (i.e., major diameter) and minimum diameter (i.e.,

minor diameter) can be found. From these values, as well as the lumen contour area and circumference, the roundness (or non-roundness) of the lumen cross-section can be calculated by several methods, including circularity, major/minor diameter ratio, and elliptical eccentricity (Fig. 5.6). Rather than quantifying the diameter of the lumen at all angular positions, a shortcut to estimating the major and minor diameters of an elliptical cross-section can be achieved with knowledge of the cross-sectional contour area and circumference. The lumen area and

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FIGURE 5.6 Calculation of metrics that describe the level of roundness or non-roundness of the lumen cross-section, including circularity, minor/major diameter ratio, and elliptical eccentricity.

FIGURE 5.7 Example of cross-sectional shape change from one state to another. From native vessel (left) to after angioplasty and stenting (middle), this lumen cross section has increased in effective diameter, minor/major diameter ratio, and perimeter (right).

perimeter can be computed directly from the coordinates of the cross-sectional contour. Then, by setting equations for cross-sectional area and perimeter equal to these computed values of area and circumference, respectively, the major and minor radii can be solved by assuming an elliptical cross-section. The area of an ellipse is simply πab, where a and b are the minor and major radii, respectively. Interestingly, there is no perfect analytic solution for calculating the perimeter of an ellipse (if you want an exact calculation of ellipse circumference, you actually need an infinite series), but there are a number of ways to approximate it (www.ebyte.it/library/docs/ math05a/EllipsePerimeterApprox05.html). In

other words, armed with a system of two equations (one for area and one for circumference), and the computed values for area and circumference, minor and major radii can be solved. With paired cross-sectional metrics from two different physiological states, deformations can be quantified. The most relevant for the vasculature are radial or diametric expansion/contraction, cross-sectional rounding/flattening, and perimeter lengthening/ shortening. Diametric expansion/contraction is useful for quantifying the effects of pulsatile pressure, stent outward radial force, and other pressure-related phenomenon such as respiration and Valsalva maneuver. Cross-sectional

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rounding/flattening is useful for determining the effects of stent outward radial force, respiratory or Valsalva pressure changes, and musculoskeletal impingement. Perimeter lengthening/shortening is a good way to measure the vessel wall strain and circumferential deformation of an implanted stent or stent graft. For example, after angioplasty and stenting with a stent with high radial force, the lumen cross-section will increase in effective diameter, roundness, and circumference as compared to the native vessel (Fig. 5.7).

AXIAL LENGTH DEFORMATION To quantify length deformations of blood vessels, centerline arclengths of the blood vessel first need to be quantified in three dimensions. The arclength of the centerline path of a

blood vessel, as described in Chapter 4, Geometric Modeling of Vasculature, can be quantified in two different physiological states, and the difference between the arclengths is the axial length deformation (Fig. 5.8) (Cheng et al., 2006). Note that this type of deformation requires fiducial markers at the proximal and distal ends of the segment of interest, and that the markers must be consistent for both physiological states. Axial strain percentage is defined as the length change divided by the reference length, so it is unitless. Looking more closely at the example in Fig. 5.8, it appears that the straight distance of the superficial femoral artery, between the profunda femoris artery and descending genicular artery branches, is nearly identical to the arclength of the superficial femoral artery in both the straight leg and fetal leg positions. What this means is that the superficial femoral

FIGURE 5.8 The axial length change or axial strain experienced by a blood vessel can be calculated as the proportion change from one state to another (left). In an example of the SFA, the artery arclength is quantified between the PF and the DG arteries in the supine and fetal positions (right). The arclength change is 28%, indicating an 8% shortening of the SFA with maximum hip and knee flexion. Note that the straight length between the PF and DG branches is very close to the SFA arclength in both body positions, indicating nearly straight SFA segments in both positions. DG, Descending genicular; PF, profunda femoris; SFA, superficial femoral artery. Adapted from Cheng, C.P., Wilson, N.M., Hallett, R.L., Herfkens, R.J., Taylor, C.A., 2006. In vivo MR angiographic quantification of axial and twisting deformations of the superficial femoral artery resulting from maximum hip and knee flexion. J. Vasc. Interv. Radiol. 17 (6), 979
987, Figure 4; and Cheng, C.P., Choi, G., Herfkens, R.J., Taylor, C.A., 2010. The effect of aging on deformations of the superficial femoral artery due to hip and knee flexion: potential clinical implications. J. Vasc. Interv. Radiol. 21 (2), 195
202, Figure 2.

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artery remains straight and does not appear to exceed the point of slack during maximum hip and knee flexion in this particular subject’s leg. If it did exceed the point of slack, the vessel would curve and the arclength would significantly exceed the straight distance between the profunda femoris and descending genicular arteries. In other words, since the superficial femoral artery is not past the point of slack in the fetal leg position, it must be under at least 8% tension in the straight leg position.

BENDING DEFORMATION Blood vessel bending is a critical deformation metric that is useful for quantifying the effects of pulsatile hemodynamics, respiration, musculoskeletal movement, and deviceinduced anatomic change. Bending can be measured in many ways, but the ones considered here predominantly revolve around (1) deviation from a straight line and (2) curvature. Note that bending can also be defined as a change in angulation along the vessel centerline, although this requires careful consideration of vector lengths for angulation calculation. Refer to the section “Branch Angle Deformation” later in this chapter for more details about defining centerline vectors. Deviation from a straight line is a simple metric that can be quantified using linear measurements. Blood vessel “straightness” can be simply defined as the straight distance between two fiducial points divided by the arclength of the vessel centerline between those same two points (Fig. 5.9). This means that the greater the path deviates from the straight path, the lower the straightness metric. Another way to define deviation from a straight line is off-axis deflection (Fig. 5.9). This metric is defined as the maximum perpendicular distance between the

FIGURE 5.9 To calculate a centerline path’s deviation from a straight line, metrics such as “straightness” and “off-axis deflection” can be used. The straightness metric is defined as the ratio of the straight path distance between two fiducial points (AB), and the arclength of the centerline path between those same two points [arclengthðABÞ]. The off-axis deflection metric is defined as the ratio between the maximum perpendicular distance between the centerline path and the straight path (PQ) and the straight path distance (AB). From Cheng, C.P., Choi, G., Herfkens, R.J., Taylor, C.A., 2010. The effect of aging on deformations of the superficial femoral artery due to hip and knee flexion: potential clinical implications. J. Vasc. Interv. Radiol. 21 (2), 195
202, Figure 7.

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centerline path and the associated straight path, divided by the length of the straight path. Not only is this metric an analogue for curvature, it can also be used as a cost function to define the optimal window size with which to calculate curvature (Cheng et al., 2010). These metrics are ratios of lengths and are thus unitless. Curvature of a curvilinear path is another quantity that measures how much a path deviates from a straight line. Even though curvilinear paths exist in three dimensions, the curvature at any point on the path can be defined in two dimensions since the curve is in a single plane locally. Geometrically, curvature is defined as the inverse of the radius of the osculating circle at a certain point; and mathematically, curvature is defined as how fast a curve is changing direction at a certain point (Fig. 5.10). Curvature has units of inverse length, for example mm21 or cm21. Note that the mathematical definition includes second derivatives with respect to t, the variable resulting from the parameterization of the curve. This means that the x and y functions need to be C2 continuous, which means that both the first and second derivatives need to exist and be continuous. Considering the complexity of blood vessel anatomy, noise in medical imaging data, and imperfections in geometric modeling, C2 continuous centerline paths cannot be guaranteed. Thus the geometric definition of curvature, where osculating circles are fit onto points along the centerline path, is usually more useful. The simplest way to do this is to choose three evenly spaced points along the centerline and compute the radius of the circle that fits through them. The inverse of that radius is the curvature at the middle point (Fig. 5.11). In the cases where the centerline coordinates may be locally noisy, the 3D surface of the blood vessel can be used for fitting optimization. In other words, rather than fitting a circle onto a vessel

centerline, this is equivalent to fitting a torus onto the vessel surface (Fig. 5.11) (Choi et al., 2014). One of the keys to calculating accurate curvature values is choosing an appropriate window size. In the case of circle fitting on a centerline, the window size is the arclength span on which the three points are evenly sampled on the centerline path. Larger window sizes have a tendency to underestimate local maximum curvatures and overestimate local minimum curvatures because they do not provide enough spatial resolution. Smaller window sizes theoretically provide more accurate curvature values, however, they may generate spurious spatial variations in curvature due to noise and errors from medical imaging and geometric model construction. In general a good compromise is a window size of approximately the length of the vessel diameter because assuming a smooth vessel centerline path, and consistent lumen diameter along the length, the minimum possible radius of curvature should be the vessel radius itself (Fig. 5.12). The window can then be incrementally shifted along the centerline in order to calculate the pointwise curvature along the length of the vessel. To determine bending deformation, the difference in curvature between two geometric states must be calculated. If the general change in average curvature is desired, mean curvatures of a vessel segment (between two fiducial markers) at two different anatomic states can be subtracted from each other. Similarly, peak curvatures can be calculated for a vessel segment at two different states in order to understand how much the maximum curvature changes. However, neither of these methods describes the bending deformation of a discrete material point. If exact localization of curvature change is desired, the centerline of a vessel from two different anatomic states must be paired, indexed, and subtracted to find pointto-point curvature deformation. Fig. 5.13

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FIGURE 5.10 Curvature of a planar curve is geometrically defined as the inverse of the radius of the osculating circle at a point (left) and mathematically defined as the rate of change that the curve is changing direction at a point (right). The primes and double primes in the equation refer to first (d/dt) and second (d2/dt2) derivatives, respectively, where t is the variable resulting from parameterization of the curve. Adapted from https://en.wikipedia.org/wiki/Curvature#/media/File:Osculating_circle.svg.

FIGURE 5.11 With circle fitting, curvature is calculated as the inverse of the radius of the circle that fits onto three evenly spaced points on the vessel centerline (left). With torus fitting, an optimization algorithm is used to fit a torus onto the local vessel surface, improving from the initial centroid (Cinitial) and radius of curvature (ρinitial) (light gray circle) to the optimal centroid (Coptimal) and radius of curvature (ρoptimal) (dark gray circle). Created by author and adapted from Cheng, C.P., Choi, G., Herfkens, R.J., Taylor, C.A., 2010. The effect of aging on deformations of the superficial femoral artery due to hip and knee flexion: potential clinical implications. J. Vasc. Interv. Radiol. 21 (2), 195
202, Figure 4.

FIGURE 5.12 If a vessel maintains the same diameter and curves until it touches itself, the minimum radius of curvature of the centerline (ρ) is the vessel radius itself (r). The solid lines represent the lumen boundaries and the dotted line represents the centerline.

graphically depicts the deformation of an artery due to respiratory influence, with changes in mean and peak curvatures, and maximum pointwise change in curvature identified for a defined vessel segment (Fig. 5.13). If fiducial markers are not available in the exact locations of interest (they rarely are), then interpolating between and extrapolating beyond fiducial markers can be a useful tactic. If there is no axial length change between two states, this method will work perfectly. In fact, even if there is axial length deformation, but

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FIGURE 5.13 Depiction of curvature deformation metrics for a vessel centerline. The yellow and red curves represent pointwise centerline curvature of an artery during inspiration and expiration, respectively. The horizontal yellow and red lines represent the mean curvatures for this artery segment and can be subtracted to determine the change in mean curvature. The blue triangle and circle represent the peak curvatures for this artery segment during inspiration and expiration, respectively, and can be subtracted to determine the change in peak curvature. The dotted black line represents the pointwise difference in curvature between inspiration and expiration, and the blue star indicates the magnitude and location of the maximum bending deformation at a material point.

the axial strain is evenly distributed, the pointwise pairing of centerline points will produce accurate results. A problem arises only when axial length change is non-uniform along the length. Since this cannot be detected for the very reason that there are not enough fiducial markers to resolve the axial deformation, a certain amount of misregistration between the two anatomic states can be assumed to more conservatively approximate maximum pointwise curvature change (Choi et al., 2009). For example, for a single point on the centerline, if 6 one vessel radius misregistration is allowed, then the curvature difference is calculated for all locations within one radius vicinity in the second anatomic configuration (Fig. 5.14). The largest curvature difference is determined and used to define the curvature deformation at that material point, and this method is repeated pointwise for the entire length of the

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FIGURE 5.14 If there is some misregistration between the centerlines of a vessel in two different anatomic states, an allowance can be given to account for this misregistration. When calculating the change in centerline curvature in a blood vessel between inspiration and expiration, instead of just comparing the expiration state at a particular point (black dot) to that of the exact corresponding location of the inspiration state (black arrow), an allowance of 6 1 radius (B2 mm) can be used to allow comparison within a range of inspiration locations (between green arrows). A conservatively high curvature change curve (dotted black line) can then be iteratively constructed for the entire centerline length.

centerline. Note that regardless of calculation method, reduction in noise for curvatures and curvature changes can be achieved by giving up some precision by averaging over segment lengths. Another method to coregister material points together is by creating fictitious landmarks out of local curvature maxima and minima locations (Choi et al., 2014). This technique relies on the assumption that the locations of curvature maxima and minima are preserved during blood vessel bending motion since the locations of high curvature are the fulcrums of regional moment arms and should remain highly curved. The coregistration of curvature maxima can be performed by dynamic time warping techniques, where a cost function is defined by the curvature function and its spatial derivative, and the cost function is minimized to coregister curvature peaks (Wang and Gasser, 1997). After the coregistration of

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local peak curvatures, curvature values are interpolated between these fictitious landmarks based on arclength to enable computing curvature deformation between two anatomic states.

BRANCH ANGLE DEFORMATION The most consistent way to quantify branch angulation is to compute the angle between two vectors, one representing the centerline of the parent vessel, and the other the centerline of the branch vessel (Fig. 5.15). When the origins of these vectors are brought together, they are contained in a single plane; however, 3D imaging data is still typically required to accurately capture the centerlines of the parent and branch vessel. These vectors can be defined either by two centerline points of a particular distance apart or by performing a linear fit upon a set of centerline points that span a particular distance (Choi et al., 2014). Moreover, the branch angulation can be calculated with varying lengths for the branch vector, which

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then provides a measure of branch curvature direction (Fig. 5.15) (Suh et al., 2014). With increasing branch vector lengths, increasing angulation means that the branch vessel is curving away from the parent vessel distally, while decreasing angulation indicates that the branch is curving toward the parent distally. Branch angle deformation is simply defined as the change in branch angulation with respect to the main parent vessel in units of degrees or radians. For example, from diastole to systole, coronary artery branch angles tend to decrease since contraction of the heart volume brings the vessels closer together and more parallel with each other.

AXIAL TWIST DEFORMATION Quantifying axial twist in a blood vessel is one of the trickier operations. It requires at least two circumferentially-distinct fiducial markers and an accurate centerline path between them. Conceptually, in a straight

FIGURE 5.15 Calculation of branch angle between parent vessel (v1) and branch vessel (v2) (left). In an example of the thoracic arch, branch angles are calculated for the BA, LCCA, and LSA arteries using 10 (gray), 20 (red), and 30 (green) mm vector lengths for each branch vessel (right). BA, Brachiocephalic; LCCA, left common carotid; LSA, left subclavian. Adapted from Suh, G., Beygui, R.E., Fleischmann, D., Cheng, C.P., 2014. Aortic arch vessel geometries and deformations in patients with thoracic aortic aneurysms and dissections. J. Vasc. Interv. Radiol. 25 (12), 1903
1911, Figure 2.

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tubular structure, axial twist is the amount of change in angular separation of one circumferentially-distinct fiducial marker in relation to another circumferentially-distinct marker over a defined axial length. In practice the simplest way to calculate axial twist is to measure the angle of separation between two fiducial markers in one geometric configuration and then find the change in angle of separation when transitioning to another configuration. For example, in a relatively straight superficial femoral artery, the angle of separation is calculated between the profunda femoris and descending genicular branches by looking down the barrel of the superficial femoral artery and measuring the angle between the two branch normal vectors (Fig. 5.16), similar to measuring the angle between two hands of an analogue clock (Fig. 5.17). Recall that branch vectors are defined by centerline points of appropriate distance apart along the branch artery, and normal branch vectors are the normal components with respect to the main

artery axis. This operation is performed for two anatomic positions, for example, supine and fetal positions, and then the change in angle of separation is defined over the arclength between the two branch arteries. However, axial twist deformation cannot be easily calculated in blood vessel paths that do not remain straight as in the previous example, specifically when bending and twisting deformations are superimposed. This necessitates a quantification technique that can separate bending and axial twist in the context of multimodal deformation. For planar curvatures, this can be done simply by tracking a parallel curve on the surface of the vessel with respect to the centerline, and projecting the vector of one branch onto the same plane as the second branch prior to calculating the angle of separation. In the case of more complex morphology where the curvature is nonplanar, the vessel can be divided along its length into short segments such that each segment can be considered to be planar

FIGURE 5.16 Process of calculating the normal branch vector of the PF artery with respect to the SFA. From closelyspaced axial slices (A), the slice where the PF just separates from the SFA (B) is selected to define the PF branch vector (C). The PF normal (PFn) branch vector is then defined as the normal component of the PF branch vector with respect to the SFA vector (D). PF, Profunda femoris; SFA, superficial femoral artery. From Cheng, C.P., Wilson, N.M., Hallett, R.L., Herfkens, R.J., Taylor, C.A., 2006. In vivo MR angiographic quantification of axial and twisting deformations of the superficial femoral artery resulting from maximum hip and knee flexion. J. Vasc. Interv. Radiol. 17 (6), 979
987, Figure 3.

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FIGURE 5.17 Depiction of calculation of axial twist in a SFA between PF and DG branch arteries. The angle of separation between the normal components of the PF and DG vectors is 183 degrees in the supine position (left) and 267 degrees in the fetal position (right). Since the SFA is relatively straight in both body positions, as revealed by the nearly identical arclength and straight length measurements for each body position, the angles of separation of the normal vectors between the two body positions can simply be subtracted to calculate an axial twist of 84 degrees in the CCW direction, or 84 degrees/20.5 cm 5 4.1 degrees/cm CCW. CCW, Counterclockwise; DG, descending genicular; PF, profunda femoris; SFA, superficial femoral artery. From Cheng, C.P., Wilson, N.M., Hallett, R.L., Herfkens, R.J., Taylor, C.A., 2006. In vivo MR angiographic quantification of axial and twisting deformations of the superficial femoral artery resulting from maximum hip and knee flexion. J. Vasc. Interv. Radiol. 17 (6), 979
987, Figure 4.

(Choi et al., 2009). Then, the first branch can be iteratively projected distally until it is on the same plane as the second branch, and the angle of separation between the two branches can be quantified (Fig. 5.18). This method of vessel division into planar segments has been demonstrated to be very robust for computing angle of separation and axial twist for multimodal deformations in validation studies (Choi et al., 2009). To enable intuitive visualization of axial length and axial twist deformations, a vessel straightening transformation can be applied to extract the curvature from a blood vessel centerline while preserving longitudinal and angular position. This method is similar to the “straightened curved planar reformat” method (two direction projection equivalent of the single direction “curved planar reformat”) which is available on standard medical image processing software. However, while straightened

curved planar reformat only preserves longitudinal and radial information (2D), it loses angular position fidelity, so it cannot be used for angle of separation and axial twist quantification. To preserve the angular position as well, a parallel path to the centerline on the vessel surface (typically indexed to a branch vessel) is used to transform the vessel surface mesh geometry from curvilinear coordinates to cylindrical coordinates with a straightened centerline (Fig. 5.19) (Choi et al., 2014). Note that the transformation of longitudinal coordinates requires special attention (parameterized projection) to preserve smoothness of the transformed surface geometry. In an example of a left anterior descending coronary artery, the artery undergoes the straightening transformation in both diastolic and systolic states, so that lengthening and twist deformations can be more intuitively measured (Fig. 5.20) (Choi et al., 2014).

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FIGURE 5.18 Depiction of methods for quantifying axial twist in a straight vessel (left) and a vessel with nonplanar curvature (right). In a straight vessel the twist angle is simply the change in the angle of separation between the proximal and distal branch vessels from the reference state to the current state (left). In a vessel that is curved in a plane, a parallel path to the centerline on the surface of the vessel (datum curve) is used to project the two branches onto the same plane prior to calculating angle of separation (right). Even if the vessel is curved and is non-planar, the vessel can be divided into short segments that can be considered planar, and the proximal branch vector can be iteratively projected from segment to segment and eventually onto the same plane as the distal branch. Adapted from Choi, G., Cheng, C.P., Wilson, N.M., Taylor, C.A., 2009. Methods for quantifying three-dimensional deformation of arteries due to pulsatile and nonpulsatile forces: implications for the design of stents and stent grafts. Ann. Biomed. Eng. 37 (1), 14
33, Figure 8.

FIGURE 5.19 Straightening transformation of a curvilinear coordinate system (left) to a straightened cylindrical coordinate system (right) using straightened curved planar reformat in combination with an indexed surface path parallel to the centerline. For more details, see Choi et al. (2014). From Choi, G., Xiong, G., Cheng, C.P., Taylor, C.A., 2014. Methods for characterizing human coronary artery deformation from cardiac-gated computed tomography data. IEEE Trans. Biomed. Eng. 61 (10), 2582
2592, Figure 5.

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FIGURE 5.20 Depiction of the straightening transformation performed on surface meshes of a left anterior descending coronary artery in the diastolic (light gray) and systolic (dark gray) states. After transitioning from the curvilinear geometries (left) to the straightened geometries (right), the axial length and axial twist deformations can be easily deciphered. From Choi, G., Xiong, G., Cheng, C.P., Taylor, C.A., 2014. Methods for characterizing human coronary artery deformation from cardiac-gated computed tomography data. IEEE Trans. Biomed. Eng. 61 (10), 2582
2592, Figure 12.

There are two more important things to note here. Axial twist should be defined as the rate of axial twist, which is in units of angle change over an axial arclength distance, for example, degrees/cm. Moreover, thus far we have only discussed axial twist with respect to a straight or straightened centerline. When axial twist is combined with shortening a vessel past the point of slack, the vessel will tend to form a helical corkscrew shape. In mathematical nomenclature the magnitude of helicity is called “torsion,” which can also be described as the rate of change of the curve’s osculating plane (i.e., out-of-plane curvature). Thus, torsional deformation can be quantified between two anatomic states with units of inverse length, just like planar curvature.

Recall that Chapter 4, Geometric Modeling of Vasculature, described how to use 3D geometric models to generate explicit mesh representations of the 3D surface. These surface meshes can subsequently be leveraged to calculate geometric features such as longitudinal and circumferential curvature, using either discrete or analytical methods. From these principal curvatures, derivative curvature metrics such as Gaussian and mean curvatures can be calculated (Shum et al., 2011). Practically, these curvature metrics have been shown to be strongly correlated to abdominal aortic aneurysm rupture risk when combined with sophisticated machine learning techniques (Lee et al., 2013). In the presence of a fiducial marker, these curvature metrics can be indexed to a material point, meaning that they can be compared between different anatomic states. Fig. 5.21 pictorially depicts the quantification of longitudinal curvature on the inner and outer curves of a curved tube, circumferential curvature on circular and irregularly-shaped cross-sections, cross-sectional eccentricity, and orientation of eccentricity indexed to a fiducial marker (Fig. 5.21) (Lundh et al., 2018). The window sizes for calculating the longitudinal and circumferential curvatures have been found to be optimal as the average diameter of the tubular structure and π/4 radians, respectively. To demonstrate the accuracy of these techniques, they were validated on a software phantom with non-circular crosssections and two bends in different planes in 3D space, exhibiting spatially-varying longitudinal and circumferential curvatures, cross-sectional eccentricity, and orientation of eccentricity (Fig. 5.22) (Lundh et al., 2018). Surface deformations between two anatomic states are often subtle to the naked eye and

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FIGURE 5.21 Depiction of quantifying longitudinal curvature on the inner (red dotted line) and outer (blue dotted line) curves of a tubular structure (left), longitudinally and angularly varying circumferential curvature (middle), and crosssectional eccentricity (based on “d” minimum diameter and “D” maximum diameter) and orientation of eccentricity θe relative to a fiducial index point γi (right). From Lundh, T., DiGiacomo, P., Suh, G., Cheng, C.P., 2018. A Lagrangian cylindrical coordinate system for characterizing surface geometry of tubular anatomic structures. Med. Biol. Eng. Comput. 56 (9), 1659
1668, Figure 3.

FIGURE 5.22 Validation of quantification of surface geometry on a complex software phantom with curvature in two different planes and non-circular cross-sections. From the software phantom, 2D cross-sectional contours (blue loops), main and branch vessel centerlines (yellow lines), and a surface reference line indexed from the branch vessel (black line) were created (A). From a Lagrangian cylindrical coordinate system, longitudinal curvature (B), circumferential curvature (C), crosssectional eccentricity (D), and cross-sectional orientation of eccentricity (E) were quantified and validated to their analytic solutions. 2D, Two-dimensional. From Lundh, T., DiGiacomo, P., Suh, G., Cheng, C.P., 2018. A Lagrangian cylindrical coordinate system for characterizing surface geometry of tubular anatomic structures. Med. Biol. Eng. Comput. 56 (9), 1659
1668, Figure 8.

REFERENCES

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FIGURE 5.23 From systole (top row) to diastole (bottom row), it is difficult to identify qualitative changes in geometry from high-resolution computed tomography images (left column) or 3D models of the cylindrical coordinate system (middle column). However, with color maps of longitudinal curvature of the endograft surface where blue indicates low curvature and red indicates high curvature (right column), it is visually apparent that there is a larger region of high curvature along the inner curve of the proximal descending aorta in diastole (bottom) as compared to systole (top). This makes sense since the high pressure pulse of systole should straighten the thoracic aorta slightly and lessen the inner curvature. 3D, Three-dimensional. Adapted from Lundh, T., DiGiacomo, P., Suh, G., Cheng, C.P., 2018. A Lagrangian cylindrical coordinate system for characterizing surface geometry of tubular anatomic structures. Med. Biol. Eng. Comput. 56 (9), 1659
1668, Figure 10.

require quantification, otherwise they may go unnoticed. For example, in a thoracic aortic endograft, which is subject to deformation from cardiac pulsatility, even time-resolved high-resolution computed tomography images do not readily reveal geometric variation between diastole and systole. However, with surface geometry quantification, alterations in longitudinal curvature can be visually identified (Fig. 5.23).

methods since the same blood vessel segment must be compared in two anatomic states in order to quantify deformation. While deformations usually occur in a multimodal fashion, they need to be separated for ease of quantification, utilization for analysis and testing, and improvement of fundamental understanding of physiological phenomenon.

References CONCLUSION This chapter has reviewed methods to quantify cross-sectional, axial length, bending, branch angulation, axial twist, and surface curvature deformations of blood vessels. Fiducial markers are an important aspect of these

Cheng, C.P., Choi, G., Herfkens, R.J., Taylor, C.A., 2010. The effect of aging on deformations of the superficial femoral artery due to hip and knee flexion: potential clinical implications. J. Vasc. Interv. Radiol. 21 (2), 195
202. Cheng, C.P., Wilson, N.M., Hallett, R.L., Herfkens, R.J., Taylor, C.A., 2006. In vivo MR angiographic quantification of axial and twisting deformations of the superficial femoral artery resulting from maximum hip and knee flexion. J. Vasc. Interv. Radiol. 17 (6), 979
987.

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Choi, G., Cheng, C.P., Wilson, N.M., Taylor, C.A., 2009. Methods for quantifying three-dimensional deformation of arteries due to pulsatile and nonpulsatile forces: implications for the design of stents and stent grafts. Ann. Biomed. Eng. 37 (1), 14
33. Choi, G., Xiong, G., Cheng, C.P., Taylor, C.A., 2014. Methods for characterizing human coronary artery deformation from cardiac-gated computed tomography data. IEEE Trans. Biomed. Eng. 61 (10), 2582
2592. Lee, K., Zhu, J., Shum, J., Zhang, Y., Muluk, S.C., Chandra, A., et al., 2013. Surface curvature as a classifier of abdominal aortic aneurysms: a comparative analysis. Ann. Biomed. Eng. 41 (3), 562
576.

Lundh, T., DiGiacomo, P., Suh, G., Cheng, C.P., 2018. A Lagrangian cylindrical coordinate system for characterizing surface geometry of tubular anatomic structures. Med. Biol. Eng. Comput. 56 (9), 1659
1668. Shum, J., Martufi, G., Di Martino, E., Washington, C.B., Grisafi, J., Muluk, S.C., et al., 2011. Quantitative assessment of abdominal aortic aneurysm geometry. Ann. Biomed. Eng. 39 (1), 277
286. Suh, G., Beygui, R.E., Fleischmann, D., Cheng, C.P., Grisafi, J., Muluk, S.C., et al., 2014. Aortic arch vessel geometries and deformations in patients with thoracic aortic aneurysms and dissections. J. Vasc. Interv. Radiol. 25 (12), 1903
1911. Wang, K., Gasser, T., 1997. Alignment of curves by dynamic time warping. Ann. Stat. 25 (3), 1251
1276.

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C H A P T E R

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Coronary Arteries and Heart G. Choi1,2, J. Chen3, J. Carroll3 and Christopher P. Cheng1 1

Division of Vascular Surgery, Stanford University, Stanford, CA, United States 2HeartFlow, Inc., Redwood City, CA, United States 3Department of Medicine, Division of Cardiology, University of Colorado, Aurora, CO, United States

of life, or approximately 400 million duty cycles. Unfortunately, the harsh dynamic in vivo environment can cause mechanical fracture of stents from as early as 7 days to several years after implantation (Lee et al., 2007). The incidence of coronary stent fractures, reported to occur between 0.8% and 8.0% (Chakravarty et al., 2010), provides insight into the severity of the biomechanical environment that stents are exposed to during their lifetime. More concerning, autopsy studies have reported fracture rates as high as 29% (Nakazawa et al., 2009). In this chapter, we will review the anatomy and deformations of the coronary arteries and myocardium, and discuss the implications on stent design and durability evaluation.

The heart is the most dynamic organ in the body. It pumps 5 L of blood per minute— 7500 L along 12,000 miles of travel per day— which equates to transporting more than 200 million liters of blood via 2.5 billion heart beats in a lifetime (Topol, 2000). The myocardial muscle is the actuator that enables the contraction and relaxation of the heart chambers by its longitudinal, radial, circumferential, and rotational deformation. The coronary (derived from the Latin word corona, meaning crown) arteries, tethered to the myocardium, are the main conducting vessels supplying oxygen and nutrition to this hardworking muscle. Thus coronary arteries are destined to experience significant dynamic biomechanical forces due to cardiac deformation, and any implanted devices within these arteries will undergo cyclic loads. The degree of deformation depends on the mechanical properties of the arteries and implanted stents, geometric configuration, and the amount of external mechanical or hemodynamic forces exerted on the arteries and stents. Regulatory guidance requires that coronary stents need to survive safely for at least 10 years

Handbook of Vascular Motion DOI: https://doi.org/10.1016/B978-0-12-815713-8.00006-1

CORONARY ANATOMY The coronary system comprises arteries, arterioles, capillaries, venules, and veins. The coronary arteries supply oxygen-rich blood to the heart muscle, and the venous system carries oxygen-depleted blood back to the heart

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FIGURE 6.1 Anterior view of coronary artery system. Right dominant (A) and left dominant (B) coronary arteries. Adapted from Drake, R.L., 2018. Gray’s Basic Anatomy. pp. 57 132, Figures 3.76 and 3.77.

chambers for oxygenation (Fig. 6.1). The right and left coronary arterial trees originate from the ascending aorta just above the aortic valve and supply blood to the left and right ventricles, respectively. These two major arteries subdivide and course over the surface of the heart (epicardium) as they traverse away from the aorta and divide into progressively smaller branches that go inward to penetrate the epicardium and supply blood to the transmural myocardium. There are three types of circulation dominance: right, left, and codominant (i.e., balanced). When the arteries supplying the posterior interventricular septum originate from the posterior descending artery and posterior lateral right coronary artery (RCA), it is called “right dominant.” The term “left dominant” refers to origination of the arteries supplying the posterior interventricular septum from the left circumflex artery (LCX). In codominant circulations the branches that run to the interventricular septum originate both from the RCA and LCX. Approximately 87% 89% of the general population are right dominant, 7% 8% are left dominant, and 4% 5% are codominant. Understanding the anatomy of the major epicardial coronary arteries and their major branches is clinically important in the management of cardiovascular diseases and

accompanying complications such as myocardial ischemia and sudden cardiac death. The coronary veins return deoxygenated blood from the myocardium back to the right atrium. Most venous blood returns via the coronary sinus. Coronary venous anatomy is highly variable, but generally comprises three groups of veins: (1) cardiac veins that drain into the coronary sinus, (2) anterior cardiac veins that drain directly into the right atrium, and (3) the smallest cardiac veins (thebesian veins) that also drain directly into the right atrium.

CORONARY ARTERY CROSSSECTIONAL DEFORMATIONS Like all other arterial systems in the body, the coronary arterial wall is composed of three layers: the intima, media, and adventitia. The layers of the coronary arteries provide the mechanical strength and compliance to accommodate the pressure and geometric changes generated by left ventricular contraction and relaxation. In this section, we will review the deformation of the coronary arteries in the crosssectional plane (diameter, area, and compliance). The coronary circulation exhibits different phasic flow compared to the systemic circulation,

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CORONARY ARTERY CROSS-SECTIONAL DEFORMATIONS

with more flow during diastole than systole. Changes in coronary flow and pressure, along with myocardial contraction, result in crosssectional deformation according to the compliance of the artery, typically measured by the ratio of cross-sectional area change divided by the pulse pressure (i.e., difference between systolic and diastolic blood pressure). Since the atherosclerotic process of the arteries involves an abnormal accumulation of fatty materials (e.g., macrophage, lipids, or calcium) in the arterial wall and sclerotic changes, diametric compliance has been considered an alternate way of predicting the extent of atherosclerotic progression of coronary arteries. Using magnified cine coronary angiograms, Shimzu et al. assessed the pressure diameter relationships of the left main and the proximal portion of the left anterior descending (LAD) and LCX coronary arteries from 46 patients (Shimazu et al., 1986). As an index of vascular wall stiffness, this group introduced a dynamic incremental elastic modulus defined as ΔP/ (ΔD/Dmean), where ΔP and ΔD represent the pulse pressure and corresponding pulse

89

diameter, and Dmean is the mean inner diameter during a cardiac cycle. Fig. 6.2 illustrates a representative case [56-year-old male, singlevessel disease (SVD)] of the pressure diameter relationship before and after administration of nitroglycerin, showing the viscoelastic properties of the vascular wall depicted by the narrow clockwise loops. The administration of nitroglycerin minimizes the individual variation of vascular muscle tone, and allows assessment of vascular stiffness for comparison between different groups. Table 6.1 shows the incremental elastic modulus and the coronary diameter in left main coronary trunk in groups of normal coronaries (NC), SVD, double-vessel disease (DVD), and triple-vessel disease (TVD) subjects. With increasing numbers of diseased locations, the angiographically normal segments of LAD and LCX proximal to the lesions exhibited stiffer wall properties (Fig. 6.3). Nakatani et al. (1995) performed a detail analysis on the effect of nitroglycerin administration on cross-sectional deformation using a slightly different definition of distensibility FIGURE 6.2 Example pressure diameter curves of the left main coronary artery before and after nitroglycerin administration. From Shimazu, T., Hori, M., Mishima, M., Kitabatake, A., Kodama, K., Nanto, S., et al., 1986. Clinical assessment of elastic properties of large coronary arteries: pressure diameter relationship and dynamic incremental elastic modulus. Int. J. Cardiol. 13 (1), 27 45. PubMed PMID: 3771000, Figure 3.

II. HOW THE BLOOD VESSELS MOVE

TABLE 6.1

Changes in the Elasticity of Coronary Arteries According to the Number of Diseased Locations

Blood Pressure (mm Hg)

LMCA

Syst.

Diast.

n

NC

114 6 14

78 6 8

13 0.097 6 0.04

14.0 6 6.8

12 0.12 6 0.04

21.4 6 8.4

11 0.10 6 0.03

30.0 6 9.7

SVD

120 6 19

77 6 10

10 0.12 6 0.08

15.2 6 5.9

9

0.14 6 0.05

15.8 6 9.7

10 0.13 6 0.04

19.2 6 12.2

DVD

132 6 18

80 6 9

6

0.26 6 0.05

13.7 6 6.0

5

0.24 6 0.12

12.3 6 9.8

5

0.20 6 0.13

18.0 6 12.1

TVD

117 6 13

74 6 9

5

0.22 6 0.12

7.4 6 6.1

5

0.28 6 0.09

16.3 6 7.8

5

0.31 6 0.08

15.4 6 9.2

P , .01

P , .01

P , .01

NS

P , .01

P , .01

Group

P value NS

NS

LAD 22

Ep(dyn) 3 10 Nm 6

% ΔD100% n

LCX 22

Ep(dyn) 3 10 Nm 6

% ΔD100% n

Ep(dyn) 3 106 Nm22 % ΔD100 %

Syst. and diast., systolic and diastolic blood pressure; LMCA, left main coronary artery; LAD, left anterior descending artery; LCX, left circumflex artery; Ep(dyn), dynamic incremental elastic modulus; % ΔD100, percent change in the inner diameter at 100 mm Hg of aortic pressure; n, number of patients; for groups NC, SVD, DVD, and TVD, see text. Data from Shimazu, T., Hori, M., Mishima, M., Kitabatake, A., Kodama, K., Nanto, S., et al., 1986. Clinical assessment of elastic properties of large coronary arteries: pressure diameter relationship and dynamic incremental elastic modulus. Int. J. Cardiol. 13 (1), 27 45. PubMed PMID: 3771000, Table 2.

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CORONARY ARTERY CROSS-SECTIONAL DEFORMATIONS

FIGURE 6.3 Dynamic incremental elastic modulus of the LMCA, LAD, and LCX arteries after nitroglycerin administration for patients with NC, SVD, DVD, and TVD. DVD, Double-vessel disease; LAD, left anterior descending; LCX, left circumflex; LMCA, left main coronary; NC, normal coronaries; SVD, single-vessel disease; TVD, triple-vessel disease. From Shimazu, T., Hori, M., Mishima, M., Kitabatake, A., Kodama, K., Nanto, S., et al., 1986. Clinical assessment of elastic properties of large coronary arteries: pressure diameter relationship and dynamic incremental elastic modulus. Int. J. Cardiol. 13 (1), 27 45. PubMed PMID: 3771000, Figure 5.

TABLE 6.2 Effects of Nitroglycerin on Coronary Distensibility Diastole

Systole

Distensibility Index (mm2/mm Hg)

Change

Pre

Post

Pre

Post

Pre

Post

Area (mm )

10.2 6 4.7

11.4 6 5.2

11.0 6 5.2

12.6 6 5.7

0.9 6 0.5

1.2 6 0.9

Pressure (mm Hg)

72 6 30

65 6 27

114 6 50

93 6 40

43 6 24

29 6 16

2

Pre

Post

Change

0.20 6 0.12

0.39 6 0.27

71 6 46%

Pre, before nitroglycerin; post, after nitroglycerin; distensibility index 5 ΔA/ΔP 3 10, where ΔA is the difference between the largest and the smallest areas, and ΔP is the difference between systolic and diastolic pressures. Data from Nakatani, S., Yamagishi, M., Tamai, J., Goto, Y., Umeno, T., Kawaguchi, A., et al., 1995. Assessment of coronary artery distensibility by intravascular ultrasound. Application of simultaneous measurements of luminal area and pressure. Circulation. 91 (12), 2904 2910. PubMed PMID: 7796499.

index as 10 3 the ratio of luminal area change (ΔA) to intracoronary pressure change (ΔP) during a cardiac cycle (i.e., ΔA/ΔP 3 10). This group reported the distensibility index for 7 patients pre- and postintracoronary nitroglycerin injection (Table 6.2). More recently, Jeremias et al. (2000) evaluated the pulsatile deformation of coronary artery lesions from 23 patients with unstable

coronary syndromes and 23 propensitymatched patients with stable angina using intravascular ultrasound imaging (Table 6.3). They concluded that patients with unstable angina exhibited greater compensatory vessel enlargement than those with stable angina, and that compensatory vessel enlargement is associated with increased coronary artery distensibility (Jeremias et al., 2000).

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6. CORONARY ARTERIES AND HEART

TABLE 6.3 Coronary Artery Compliance at the Proximal Reference Segment of Lesions Metric

Unstable Patients

Stable Patients

P Value

PS (mm Hg)

124 6 25

130 6 20

.544

PD (mm Hg)

67 6 11

68 6 11

.892

8.28 6 2.68

8.57 6 3.46

.921

2

LAS (mm )

7.29 6 2.56

8.18 6 3.40

.386

2

LAS 2 LAD (mm )

0.99 6 0.66

0.39 6 0.30

, .001

Distensibility index (per mm Hg)

3.09 6 2.68

0.94 6 0.83

, .001

LDS (mm)

3.52 6 0.53

3.49 6 0.69

.895

LDD (mm)

2.63 6 0.50

2.88 6 0.63

.158

LDS 2 LDD (mm)

0.88 6 0.26

0.62 6 0.15

, .001

β, stiffness index

1.95 6 0.94

3.10 6 0.96

, .001

2

LAD (mm )

LAD, Diastolic lumen area; LAS, systolic lumen area; LDD, diastolic lumen diameter; LDS, systolic lumen diameter; PD, diastolic arterial pressure; PS, systolic arterial pressure; distensibility index [(LAS 2 LAD)/LAD/(PS 2 PD)] 3 103/mm Hg; stiffness index ([ln(PS/PD)]//((LDS 2 LDD)/LDD)). Data from Jeremias, A., Spies, C., Herity, N.A., Pomerantsev, E., Yock, P.G., Fitzgerald, P.J., et al., 2000. Coronary artery compliance and adaptive vessel remodelling in patients with stable and unstable coronary artery disease. Heart. 84 (3), 314 319. PubMed PMID: 10956298, Table 2.

CORONARY ARTERY AXIAL, BENDING, TWISTING, AND BIFURCATION ANGLE DEFORMATIONS In addition to cross-sectional deformation, cardiac contractions create complex threedimensional (3D) deformations of the coronary arteries in the axial curvilinear direction. Among many geometric descriptors, length and curvature are the most commonly used terms in clinical situations, partly due to the ubiquity of coronary angiography. The length change of arteries or stents provides a measure of longitudinal deformation, resulting in axial shortening or lengthening. Curvature measures the rate of change in the tangential direction of the vessel centerline and represents the degree of bending. With the introduction of 3D imaging techniques [e.g., computed tomography (CT) or magnetic resonance imaging (MRI)] (Tuncay et al., 2018), torsion has become another popular parameter to describe the degree of twisting out of plane as the arteries

surround the epicardial surface of the heart. Coronary bifurcation angle is also an important metric to measure. Indeed, bifurcation lesions account for approximately 20% of percutaneous coronary interventions (PCI), and procedural and clinical outcomes associated with the treatment of coronary bifurcation lesions are often suboptimal due to the complexity of anatomy and the dynamic changes that occur during PCI. Chen et al. developed an algorithm that produces accurate 3D models from single-plane, biplane, or rotational angiography to quantify vessel curvature, segment length, and radiographic foreshortening (Chen et al., 2002; Chen and Carroll, 2003). Briefly, the first crucial step is to create accurate patient-specific 4D (i.e., 1D for time-varying space plus 3D geometry) coronary tree models as a foundation for the subsequent dynamic motion analysis. A 3D reconstruction technique is employed to accurately reconstruct the moving coronary arterial trees throughout the cardiac cycle based on two sequences of planar cine angiograms

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CORONARY ARTERY AXIAL, BENDING, TWISTING, AND BIFURCATION ANGLE DEFORMATIONS

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FIGURE 6.4 Iterative process of identifying the coronary tree on time-resolved planar images. (A) Coronary arterial tree centerlines in dark curves superimposed on a planar image. (B) Initially estimated coronary tree centerlines in white curves superimposed onto the image at the next time point. (C) Resultant coronary arterial tree centerlines on the second time point after a deformation and editing process. From Chen, S.Y., Carroll, J.D., 2003. Kinematic and deformation analysis of 4-D coronary arterial trees reconstructed from cine angiograms. IEEE Trans. Med. Imaging 22 (6), 710 721. PubMed PMID: 12872946, Figure 1.

acquired from single-plane or biplane imaging systems. To efficiently model all time points, a 2D coronary tree model (for each planar image from the pair) is constructed for a single time point, and then used as a starting point and “deformed” iteratively for all subsequent cardiac phases (Fig. 6.4). With this iterative process of constructing the coronary tree architecture for each cardiac phase, the entire cardiac cycle can be described, and multiple frames can be compared. Fig. 6.5 shows an example of a pair of time-resolved left coronary cine angiograms acquired between end-diastole and end-systole using a single-plane imaging system (Fig. 6.5, top), and the results of overlaying six cardiac time points for the LAD and LCX arteries from two different views (Fig. 6.5, bottom). These time-resolved geometric models can then be queried to provide 3D geometric properties and deformations. For example, Table 6.4 shows the curvature, torsion, and cross-sectional diameter of coronary bypass grafts, and Table 6.5 shows the curvature and torsion deformations of the RCA between end-diastole and end-systole phases (Chen et al., 2002).

In addition, these techniques can be used to reveal deformations as a result of stent implantation. For example, the distal left circumflex and proximal obtuse marginal branches in the left coronary artery tree can be straightened, and the native artery segment distal to the stent can be kinked from pre- to post-stenting (Fig. 6.6) (Chen et al., 2010). Based on the aforementioned analyses, stent-induced changes in vessel geometry were queried on three types of stent designs (i.e., closed cell, open cell, and slotted tube) that were implanted at RCA (n 5 38), LAD artery (n 5 32), LCX (n 5 13), obtuse marginal branch (n 5 10), diagonal branch (n 5 3), posterolateral branch (n 5 2), and ramus intermedius artery (n 5 2) (Table 6.6). As expected, one key finding was that vessels with greater baseline curvature had more pronounced straightening after stent implantation than did straighter vessels. Furthermore, buckling of the vessel at the proximal and distal ends of the stent shows marked changes in curvature due to stenting. In Table 6.7 the frequency and magnitude of the straightening and flexion effects are summarized, which demonstrates the fact that stent implantation frequently results in straightening

II. HOW THE BLOOD VESSELS MOVE

FIGURE 6.5 A pair of cine left coronary angiograms acquired from ED to ES by a single-plane imaging system (top two rows). Results of overlaying the left anterior descending and left circumflex arteries from two different viewing angles (bottom two images), where the moving trajectory of each vessel centerline point is represented by short green line segments connecting the vessel centerline points from ED to ES, and where the dark vessels denote the artery positions between ED and ES. ED, End-diastole; ES, end-systole. Adapted from Chen, S.Y., Carroll, J.D., 2003. Kinematic and deformation analysis of 4-D coronary arterial trees reconstructed from cine angiograms. IEEE Trans. Med. Imaging 22 (6), 710 721. PubMed PMID: 12872946, Figure 8. TABLE 6.4 Average Curvature, Torsion, and Diameter of Coronary Bypass Grafts

Average curvature (cm21) 21

All

Proximal

Mid

Distal

0.8 (range: 0 2.4)

0.9

1.1

0.3

Average torsion (cm )

1.5 (range: 27.40 9.6)

1.8

2.1

0.4

Average diameter (mm)

5

4.8

4.5

5.7

Data from Chen, S.Y., Carroll, J.D., Messenger, J.C., 2002. Quantitative analysis of reconstructed 3-D coronary arterial tree and intracoronary devices. IEEE Trans. Med. Imaging. 21 (7), 724 740. PubMed PMID: 12374311.

TABLE 6.5 Average Curvature, Torsion, and Diameter, and Changes in Curvature and Torsion of Right Coronary Arteries Due to Cardiac Pulsatility End-Diastole

End-Systole

Range of Absolute Difference

1.28

0.84

0 2.1

Average torsion (cm )

0.74

0.19

0 3.37

Average diameter (mm)

2.6

2.6

NA

21

Average curvature (cm ) 21

Data from Chen, S.Y., Carroll, J.D., Messenger, J.C., 2002. Quantitative analysis of reconstructed 3-D coronary arterial tree and intracoronary devices. IEEE Trans. Med. Imaging. 21 (7), 724 740. PubMed PMID: 12374311.

FIGURE 6.6 Angiograms of left coronary arterial tree with two stenotic lesions on the left circumflex and obtuse marginal arteries before (left) and after (right) stent implantation. The stented segments are straightened while the native artery just distal to the stents exhibit kinking. From Chen, S.J., Messenger, J.C., Carroll, J.D., 2010. A methodology for quantifying deformations in stented coronary arteries based on threedimensional angiography. J. ASTM Int. 7 (1), Paper ID JAI101873, Figure 1.

TABLE 6.6 Pre- and Post-stenting Change in Curvature, by Stent and Stent Type Closed Cell

Open Cell

Slotted Tube

Total

NIR

NIRoyal

S670

S7

TriStar

Ultra

n 5 24

n 5 11

n 5 35

n 5 19

n 5 13

n 5 32

n 5 25

n58

n 5 33

n 5 100

Diameter (mm)

3.3

3.1

3.2

3.5

3.4

3.4

3.1

4.6

3.5

3.2

Length (mm)

17.4

14.4

16.5

17.5

15.2

16.6

17.0

16.8

16.9

15.9

0.62

0.75

0.66

0.64

0.63

0.64

0.61

0.68

0.63

0.64

Curvature post-stent (cm )

0.47

0.54

0.49

0.54

0.45

0.51

0.51

0.53

0.51

0.50

Change in curvature (ΔK)

0.15

0.21

0.17

0.10

0.18

0.13

0.11

0.16

0.12

0.14

0.66

0.88

0.73

0.61

0.66

0.63

0.67

0.69

0.67

0.68

Curvature post-stent (cm )

0.51

0.56

0.53

0.57

0.50

0.54

0.55

0.54

0.55

0.54

Change in curvature (ΔK)

0.15

0.33

0.20

0.04

0.16

0.08

0.12

0.16

0.13

0.14

End-diastole Curvature baseline (cm21) 21

End-systole Curvature baseline (cm21) 21

Data from Chen, S.J., Messenger, J.C., Carroll, J.D., 2010. A methodology for quantifying deformations in stented coronary arteries based on threedimensional angiography. J. ASTM Int. 7 (1), Paper ID JAI101873.

TABLE 6.7 Localization and Degree of Curvature Change at and Adjacent to Stented Segment Proximal Peristent

Stented Segment

Distal Peristent

39

17

46

0.469

0.570

0.292

Curvature post-stent (cm )

0.776

0.636

0.488

Change in curvature (ΔK)

1 0.31

1 0.07

1 0.20

Relative change (%)

1 65

1 11

1 70

61

83

54

0.821

0.718

0.452

Curvature post-stent (cm )

0.508

0.473

0.273

Change in curvature (ΔK)

2 0.31

2 0.25

2 0.17

Relative change (%)

2 38

2 34

2 37

Buckling (% of vessels) 21

Curvature baseline (cm ) 21

Straightening (% of vessels) 21

Curvature baseline (cm ) 21

Data from Chen, S.J., Messenger, J.C., Carroll, J.D., 2010. A methodology for quantifying deformations in stented coronary arteries based on threedimensional angiography. J. ASTM Int. 7 (1), Paper ID JAI101873.

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6. CORONARY ARTERIES AND HEART

of the vessel and variable effects on the proximal and peristent regions. Using a similar technique based on biplane angiography, Zhu et al. (2003) tracked the 3D

motion of coronary arteries in each frame and compared coronary artery dynamics for two cases (one RCA and one LAD). Fig. 6.7 shows a demonstration of 3D vessel tracking applied to

FIGURE 6.7 Demonstration of 3D vessel tracking showing an initial manual path of the vessel lumen (A), refined path of the vessel lumen (B), and a series of windows used to improve mapping onto the next time point (C). From Zhu, H., Warner, J.J., Gehrig, T.R., Friedman, M.H., 2003. Comparison of coronary artery dynamics pre- and post-stenting. J. Biomech. 36 (5), 689 697. PubMed PMID:12694999, Figure 1. II. HOW THE BLOOD VESSELS MOVE

CORONARY ARTERY AXIAL, BENDING, TWISTING, AND BIFURCATION ANGLE DEFORMATIONS

quantify the longitudinal change of the vessel from before to after stenting. Geometric parameters in Zhu et al.’s (2003) study include instantaneous, mean, and pulseinduced change for curvature, arc length, chord length, and chord/arc length ratio. Arc length refers to the parametric curvilinear length between the two ends of the stent along the axis, whereas the chord length refers to the direct straight distance in 3D between the two ends of the stent. Chord/arc length ratio, defined by the chord length divided by arc length, was devised to measure the global change of curvature. Fig. 6.8 illustrates temporal and spatial variation of curvature in the stented segment of the vessel while Fig. 6.9 shows the temporal variation of the stent arc length, chord length, and chord/arc length ratio. They noted that RCA geometry was relatively unchanged by stenting, whereas in the LAD, the occurrence of relatively high curvature and flexing disappeared after stenting (Fig. 6.8). This was also reflected by the global curvature metrics as computed by stent length (Fig. 6.9). Note that while the highest curvature and highest curvature change occur at the same location on the RCA, these locations do not coincide on the LAD (Fig. 6.8). Liao et al. (2002) conducted an extensive analysis of cyclic changes in 21 coronary arteries caused by cardiac motion. In a subgroup analysis, vessels were divided into two groups: those lying in the atrioventricular (AV) groove (LCX, RCA) and those overlying actively contracting myocardium (LAD, diagonal, obtuse marginal, right ventricular marginal, posterior descending, posterolateral). The arteries that resided in the AV groove exhibited lower change in curvature and higher change in torsion (out-of-plane curvature) over the cardiac cycle compared to those on the contracting myocardium (Table 6.8). When considering the proximal, middle, and distal sections of the coronary arteries, it was found that the arteries in the AV groove were more curved in the proximal region compared to the distal region,

97

with no significant dynamic flexion during the cardiac cycle in any region (Table 6.9). On the contracting myocardium, the arteries tended to dynamically flex more and include more flexion points (FP) at the distal sections. This study clearly demonstrated the variation in geometry and bending deformation depending on the spatial location of coronary arteries on the epicardial surface (Liao et al., 2002). Discrete locations of acute bending greater than 15 degrees were marked as FP, and a flexion point index (FPI) was calculated as the number of FP per vessel per 100 mm of vessel length. The authors pointed out that the AV groove around the base of the heart undergoes little shape change during cardiac cycle, thereby resulting in little changes in shape parameters (i.e., curvature, FP, FPI) for the LCX and RCA that follow the AV groove. A potential reason why the distal portions of the arteries residing on the contracting myocardium manifested much greater deformation than the proximal portions is that distal portions of these arteries are located at the cardiac apex, where the most vigorous cardiac contraction occurs at systole. The authors also noted that the diagonal, right ventricular marginal, and obtuse marginal branches demonstrated substantially greater change in curvature compared to other vessel segments. To conclude, the authors highlighted the need to standardize terminology and define simpler metrics for describing coronary arterial shape and deformation in the cardiology field. In an attempt to establish more standardized metrics, Choi et al. (2009) proposed methods to extract global shape parameters derived from intuitive geometric definitions rather than mathematical derivatives that can be potentially sensitive to measurement errors. Fig. 6.10 illustrates the geometric interpretation of bending and twisting deformations of tubular structures. Fig. 6.11 shows an illustrative example of curvature change along the length of the LAD from end-diastolic to end-systolic phases. In this example, from diastole to systole, the LAD

II. HOW THE BLOOD VESSELS MOVE

FIGURE 6.8 Temporal and spatial variations of curvature for right coronary (left column, A) and left anterior descending (right column, B) arteries. As seen in the temporal spatial plots pre-stenting (top row) and post-stenting (second row), and in the temporal plots of mean curvature (third row) and pulse curvature (bottom row), the stent more significantly decreased mean and pulse curvature in the left anterior descending artery with stenting. Note that the two vertical dotted lines represent the margins of the stented segment. From Zhu, H., Warner, J.J., Gehrig, T.R., Friedman, M.H., 2003. Comparison of coronary artery dynamics pre- and post-stenting. J. Biomech. 36 (5), 689 697. PubMed PMID:12694999, Figure 4.

CORONARY ARTERY AXIAL, BENDING, TWISTING, AND BIFURCATION ANGLE DEFORMATIONS

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FIGURE 6.9 Arc length (top row), chord length (middle row), and chord/arc length ratio (bottom row) for the right coronary (left column, A) and left anterior descending (right column, B) arteries. The stent more significantly decreased global curvature in the left anterior descending artery. From Zhu, H., Warner, J.J., Gehrig, T.R., Friedman, M.H., 2003. Comparison of coronary artery dynamics pre- and post-stenting. J. Biomech. 36 (5), 689 697. PubMed PMID:12694999, Figure 5.

TABLE 6.8 Curvature and Torsion Change According to Spatial Location of Coronary Arteries Location

Metric

End-Diastole (cm21)

End-Systole (cm21)

Change (cm21)

AV groove

Curvature

0.69 6 0.06

0.67 6 0.05 (est.)

20.02 6 0.03

Torsion

N.A.

N.A.

21.2 6 0.11

Myocardium

Curvature

0.87 6 0.05

1.2 6 0.07 (est.)

0.33 6 0.04 (38% increase, P , .001)

Torsion

NA

NA

20.005 6 0.10

AV, Atrioventricular. Data from Liao, R., Chen, S.Y., Messenger, J.C., Groves, B.M., Burchenal, J.E., Carroll, J.D., 2002. Four-dimensional analysis of cyclic changes in coronary artery shape. Catheter. Cardiovasc. Interv. 55 (3), 344 354. PubMed PMID: 11870940.

TABLE 6.9 Curvature Change According to Longitudinal Location on Coronary Arteries Location AV groove

Myocardium

Metric

Proximal 21

Middle

Distal

Curvature (ED)

0.90 6 0.11 cm

NA

0.51 6 0.05 cm21

Curvature change FP/vessel, FPI

No significant difference

No significant difference

No significant difference

0.90

0.78

0.91

Curvature change (cm )

0.15

0.43

0.43

FP/vessel

0.46

0.8

1.13

0.94

1.15

4.24

Curvature (ED) (cm21) 21

21

FPI (mm )

AV, Atrioventricular; ED, end-diastole; FP/vessel, number of flexion points per vessel; FPI, flexion point index (FP/vessel) 3 100/vessel length (mm). Data from Liao, R., Chen, S.Y., Messenger, J.C., Groves, B.M., Burchenal, J.E., Carroll, J.D., 2002. Four-dimensional analysis of cyclic changes in coronary artery shape. Catheter. Cardiovasc. Interv. 55 (3), 344 354. PubMed PMID: 11870940.

FIGURE 6.10 Geometric interpretation of curvature represented by circumscribed circle (left) and axial twisting represented by change in angle of separation between adjacent branches (right). Adapted from Choi, G., Cheng, C.P., Wilson, N.M., Taylor, C.A., 2009. Methods for quantifying three-dimensional deformation of arteries due to pulsatile and nonpulsatile forces: implications for the design of stents and stent grafts. Ann. Biomed. Eng. 37 (1), 14 33. PubMed PMID: 19002584, Figures 6 and 8.

CORONARY ARTERY AXIAL, BENDING, TWISTING, AND BIFURCATION ANGLE DEFORMATIONS

101

FIGURE 6.11 Motion of the LAD coronary artery due to cardiac pulsatility (left, where end-diastole is in green and end-systole is in red). Curvature variation of the LAD coronary artery where local curvature maxima during the systolic phase are labeled as C1 C8 (right). The maximum change in curvature is located at C8 with a change of 0.75 mm21. LAD, left anterior descending. Adapted from Choi, G., Cheng, C.P., Wilson, N.M., Taylor, C.A., 2009. Methods for quantifying threedimensional deformation of arteries due to pulsatile and nonpulsatile forces: implications for the design of stents and stent grafts. Ann. Biomed. Eng. 37 (1), 14 33. PubMed PMID: 19002584, Figures 1 and 11.

FIGURE 6.12 Overview of 3D surface-based methods to quantify deformation metrics. Coronary arteries are first straightened for quantifying strain and twisting angle (A). Note that the straightening transformation removes bending components of geometries for easy comparison of branch locations between the two models in diastolic and systolic phases. Length changes (Δli) and twisting angles (Δϕi) are computed by subtraction of axial translations (zi) and rotation angles (Θi) of side branches, respectively, from the aligned straightened geometries (B and C). Curvature (κ) is derived from the radius of curvature (ρ) of the optimally-fitted torus on the segment of interest (D). Bifurcation angle is computed by the angle between two vectors extracted from linear fits of the cross-sectional centroid sets of two branches (E). 3D, Three-dimensional. Adapted from Choi, G., Xiong, G., Cheng, C.P., Taylor, C.A., 2014b. Methods for characterizing human coronary artery deformation from cardiac-gated computed tomography data. IEEE Trans. Biomed. Eng. 61 (10), 2582 2592. PubMed PMID: 24835123, Figures 12 and 13.

shortens 6.7%, the mean curvature increases from 1.0 to 1.8 cm21, the maximum local curvature change is 7.5 cm21, and the vessel twists 3 degrees/cm.

Choi et al. (2014b) further developed a direct 3D surface-based method to quantify coronary deformation from cardiac-gated CT data (Fig. 6.12) and investigated the sensitivity of

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the parameters to segmentation methods (threshold-based and edge-based methods). More details about this method can be found

in Chapter 5, Quantifying Vascular Deformations. Table 6.10 summarizes average deformation measurements in two patients.

TABLE 6.10 Axial Length, Twist, Curvature, and Bifurcation Angle Deformations of the Coronary Arteries in Patients a. Strain (%) Case

Vessel

Proximal

Middle

Distal

I

LAD

2 0.61

2 1.82

2 3.40

RCA

2 1.62

2 0.24

0.18

LAD

2 6.20

2 8.49

2 5.94

RCA

2 2.04

2 5.07

2 8.87

II

2 3.68 6 3.16%

Average b. Twist rate (degrees/cm) Case

Vessel

I

II

Proximal

Middle

Distal

LAD

0.87

2 0.06

2 3.48

RCA

2.18

2 1.29

2 0.03

LAD

2 0.05

0.46

3.86

RCA

2 1.62

2 3.23

2 2.26

Average

2 0.39 6 2.15 degrees/cm

Average absolute

1.62 6 1.39 degrees/cm

c. Curvature (cm21) Case

Vessel

I

LAD

RCA

Proximal

Middle

Distal

Diastole

0.516

0.555

0.923

Systole

0.524

0.676

1.176

Change

0.007

0.121

0.252

Diastole

0.702

0.604

0.890

Systole

0.671

0.706

0.939

Change

2 0.031

0.102

0.049

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c. Curvature (cm21) Case

Vessel

II

LAD

RCA

Proximal

Middle

Distal

Diastole

0.512

0.628

0.815

Systole

0.584

1.033

1.287

Change

0.072

0.406

0.473

Diastole

0.418

0.399

0.512

Systole

0.466

0.419

0.616

Change

0.048

0.021

0.105

21

0.137 6 0128 cm

Average change

(37.8 6 19.8%)

d. Bifurcation angle change between LAD and LCX (degrees) Angle I

II

Diastole

81.2

Systole

75.7

Change

2 5.6

Diastole

52.4

Systole

40.7

Change

2 11.7

Data from IEEE journal, Choi, G., Xiong, G., Cheng, C.P., Taylor, C.A., 2014b. Methods for characterizing human coronary artery deformation from cardiac-gated computed tomography data. IEEE Trans. Biomed. Eng. 61 (10), 2582 2592. PubMed PMID: 24835123, Table IV.

CARDIAC ANATOMY The normal human heart is composed of two upper chambers, including the right and left atria, and two lower chambers, including the right and left ventricles (Fig. 6.13). The right atrium and ventricle are in series with each other to transmit deoxygenated blood to the lungs, and the left atrium and ventricle are in series with each other to pump oxygenated blood to the systemic circulation. Specifically, the right atrium receives deoxygenated blood from the superior and inferior venae cavae and then delivers the blood to the right ventricle

through the tricuspid valve. The right ventricle then sends the deoxygenated blood to the pulmonary arteries through the pulmonary valve. The left atrium receives oxygenated blood from the pulmonary veins and sends it to the left ventricle through the mitral valve, and the left ventricle pumps the oxygenated blood to the aorta and the rest of body through the aortic valve (Fig. 6.13). The right and left atrial contract simultaneously as a pair to help fill the ventricles, and subsequently the right and left ventricles contract simultaneously as another pair to pump blood into the lungs and body.

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FIGURE 6.13 Cardiac structures. Anterior surface of the heart (A), interval view of the right ventricle (B), interval view of the left ventricle (C), and cardiac skeleton and valves (D). Adapted from Drake, R.L., 2018. Gray’s Basic Anatomy. pp. 57 132, Figures 3.59, 3.67, 3.71, and 3.75.

DIRECT MEASUREMENT OF MYOCARDIAL MOTION AND DEFORMATION The myocardium deforms in three dimensions simultaneously, exhibiting longitudinal and circumferential shortening and radial thickening during systole. Cardiac wall motion provides explicit information for assessing the health of the heart due to changes in cardiac dynamics that accompany cardiac disease. Various imaging techniques have been developed to image this complex motion and detect regional motion abnormalities. Echocardiography is the most widely adopted imaging modality due to its low cost, lack of radiation, and ease of use. However, MRI and CT techniques have also been

developed to assess myocardial deformation and function. Cardiovascular MRI tissue tagging provides highly reproducible data of myocardial deformation in all spatial directions (circumferential, longitudinal, and radial). The principle of myocardial tagging is based on producing a spatially modulated pattern of saturated magnetization within the heart wall tissue, and then imaging deformation of that spatial pattern as the heart contracts. Most cardiac MRI tagging data consists of two or three timeresolved data sets of 2D images acquired on parallel planes through the thoracic region (Fig. 6.14) or on planes arranged in a radially sampled pattern, intersecting on the long axis of the left ventricle.

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FIGURE 6.14

Cardiac magnetic resonance tissue tagging. The schematic drawing shows short-axis image planes (three donut shapes) and magnetically saturated planes perpendicular to the image planes (slice planes) in both directions (left, A). In the short axis of the heart, reduced signal is obtained from the magnetically saturated tissue, resulting in a grid of black lines on the tissue (right, B). LV, Left ventricle; RV, right ventricle. From Go¨tte, M.J., Germans, T., Ru¨ssel, I.K., Zwanenburg, J.J., Marcus, J.T., van Rossum, A.C., et al., 2006. Myocardial strain and torsion quantified by cardiovascular magnetic resonance tissue tagging: studies in normal and impaired left ventricular function. J. Am. Coll. Cardiol. 48 (10), 2002 2011. PubMed PMID: 17112990, Figure 1.

FIGURE 6.15 Short-axis view of magnetic resonance myocardial tagging of the left ventricle during diastole (left column) and systole (right column). The top row shows tagged images of the entire left ventricular cross section, while the bottom row shows corresponding zoomed-in images. Change in length of the red line represents radial deformation from diastole to systole, while change in length of the green line represents circumferential deformation. From Jeung, M.Y., Germain, P., Croisille, P., El ghannudi, S., Roy, C., Gangi, A., 2012. Myocardial tagging with MR imaging: overview of normal and pathologic findings. Radiographics. 32 (5), 1381 1398. PubMed PMID: 22977026, Figure 2.

The deformed tag pattern during the cardiac cycle reflects the nonuniform deformation of the myocardium. Thus, tracking the motion of these saturated tag lines in 3D can provide quantitative values of intramural myocardial deformation in the longitudinal, radial, and circumferential directions (Fig. 6.15). Another method is to digitize the corners of the grid

lines, and by tracking these digitized points, material strains can be calculated (Fig. 6.16). Moore et al. (2000) and Clark et al. (1991) measured variation of myocardial circumferential strain through the thickness of the left ventricle wall as measured by MRI tagging methods from healthy volunteers (Table 6.11). Jeung et al. (2012) further evaluated myocardial

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FIGURE 6.16 Depiction of myocardial deformation tracking using magnetic resonance tagging. Short-axis images of the left ventricle with deformed tagging grid at end-systole (A), digitized grid intersection points at end-systole (B), and tracings of the grid intersections for the cardiac cycle superimposed on a diastolic image (C). The displacement of these points can be measured and compared with adjacent points to quantify local intramural myocardial strains. From Go¨tte, M. J., Germans, T., Ru¨ssel, I.K., Zwanenburg, J.J., Marcus, J.T., van Rossum, A.C., et al., 2006. Myocardial strain and torsion quantified by cardiovascular magnetic resonance tissue tagging: studies in normal and impaired left ventricular function. J. Am. Coll. Cardiol. 48 (10), 2002 2011. PubMed PMID: 17112990, Figure 3. TABLE 6.11 Myocardial Strain Measured by Grid Magnetic Resonance Tagging Subjects

Endocardium (%)

Midwall (%)

Epicardium (%)

Moore et al.

31 healthy volunteers

32 6 4

23 6 4

16 6 4

Clark et al.

10 healthy volunteers

44 6 6

30 6 6

22 6 5

strain in the circumferential, longitudinal, and radial directions for normal subjects and those with cardiac disease. One consistent finding was the nonuniform rotation of the base and apex of the heart, resulting in clockwise twisting of the base of the heart with respect to the apex when viewed from the apex (looking from the bottom). In addition, it was found that the diseased patients experienced lower myocardial deformation compared to healthy controls, indicating reduced cardiac contractility. To investigate the effect of aging on regional left ventricular contraction and relaxation, Fonseca et al. (2003) and Oxenham et al. (2003) compared the myocardial strains of 15 younger (19 26 years) and 16 older (60 74 years) healthy volunteers (Table 6.12). Overall, the older subjects exhibited greater peak systolic torsional shear strain, lower peak systolic circumferential and

longitudinal “contraction” strain rates, and lower peak diastolic circumferential, longitudinal, and torsional “relaxation” strain rates. For dilated cardiomyopathy patients, Nelson et al. (2000) reported 5.3 6 2.1% circumferential shortening, which was significantly lower than the 18.6 6 2.9% for control subjects. Regarding twisting motion, Stuber et al. (1999) and Nagel et al. (2000) also showed a wringing motion of the left ventricle with clockwise rotation at the base and counterclockwise rotation at the apex as viewed from the apex. When comparing healthy controls, patients with aortic stenosis, and elite athletes (rowers), controls and elite rowers exhibited similar left ventricular mechanics, while aortic stenosis patients exhibited greater magnitude and faster torsional rotation (Table 6.13).

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TABLE 6.12 Myocardial Strain for Young and Older Healthy Adults Younger

Older

Peak systolic circumferential shortening (%)

20.0 6 2.9

20.0 6 2.9

Peak systolic longitudinal strain (%)

18.0 6 1.2

16.9 6 2.5

7.8 6 0.9

9.1 6 1.7

Peak systolic torsional shear strain (degrees) Peak systolic circumferential strain rate (%/s)

114.8 6 6.7

106.3 6 14.6

Peak systolic longitudinal strain rate (%/s)

112.8 6 9.3

94.5 6 11.7

74.3 6 17.9

65.1 6 11.7

Peak diastolic circumferential strain rate (%/s)

162.7 6 18.2

104.5 6 27.7

Peak diastolic longitudinal strain rate (%/s)

154.5 6 18.0

93.7 6 26.9

91.1 6 15.5

74.5 6 16.0

Peak systolic torsion shear strain rate (degrees/s)

Peak diastolic torsion shear strain rate (degrees/s)

Data from Fonseca, C.G., Oxenham, H.C., Cowan, B.R., Occleshaw, C.J., Young, A.A., 2003. Aging alters patterns of regional nonuniformity in LV strain relaxation: a 3-D MR tissue tagging study. Am. J. Physiol. Heart Circ. Physiol. 285 (2), H621 H630. Epub April 10, 2003. PubMed PMID:12689861 and Oxenham, H.C., Young, A.A., Cowan, B.R., Gentles, T.L., Occleshaw, C.J., Fonseca, C.G., et al., 2003. Age-related changes in myocardial relaxation using three dimensional tagged magnetic resonance imaging. J. Cardiovasc. Magn. Reson. 5 (3), 421 430. PubMed PMID: 12882073.

TABLE 6.13 Left Ventricular Myocardial Torsion for Controls, Aortic Stenosis Patients, and Elite Athletes Control

Aortic Stenosis

Elite Athletes

Myocardial torsion rotation (degrees)

762

12 6 5

662

Myocardial torsion rotation rate (degrees/s)

55 6 17

80 6 29

56 6 8

Myocardial untwist time (ms)

47 6 23

88 6 19

51 6 23

Data from Stuber, M., Scheidegger, M.B., Fischer, S.E., Nagel, E., Steinemann, F., Hess, O.M., et al., 1999. Alterations in the local myocardial motion pattern in patients suffering from pressure overload due to aortic stenosis. Circulation. 100 (4), 361 368. PubMed PMID: 10421595 and Nagel, E., Stuber, M., Burkhard, B., Fischer, S.E., Scheidegger, M.B., Boesiger, P., et al., 2000. Cardiac rotation and relaxation in patients with aortic valve stenosis. Eur. Heart J. 21 (7), 582 589. PubMed PMID: 10775013.

Echocardiographic assessment of myocardial function has played a critical role in diagnosing and managing ischemic heart disease. Ultrasound utilizes tissue Doppler-based or 2D speckle tracking-based methods to measure myocardial motion (Hoit, 2011; Gorcsan and Tanaka, 2011; Shah and Solomon, 2012). Doppler methods calculate time-resolved strain rates from the velocity gradient along the length of the left ventricle, and then the strain rates are integrated to derive strain. Ultrasound speckle tracking is a more recent approach to strain analysis, which quantifies motion of the ultrasound backscatter speckle pattern within B-mode echocardiographic images.

While qualitative visual assessment of endocardial excursion or wall thickening is sufficient for standard clinical diagnostics, strain imaging has enabled more precise assessment of location and severity of ischemia or infarction. Edvardsen et al. (2002) demonstrated an extensive comparison of myocardial strain for 33 healthy volunteers, 17 patients with acute myocardial infarction, and nine patients with suspected coronary artery disease using both Doppler echocardiography and MRI tagging techniques. Longitudinal and radial strain measurements of the left ventricle of healthy subjects were consistent between the two imaging modalities (Tables 6.14 and 6.15).

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TABLE 6.14 Peak Longitudinal Myocardial Strain in Healthy Volunteers Segments Anterior

Tissue Doppler velocities, cm/s (n 5 33)

Septal

Posterior

Lateral

Base

Apex

Base

Apex

Base

Apex

Base

Apex

6.5 6 1.6

2.8 6 1.0

6.7 6 1.4

2.8 6 1.1

6.5 6 1.4

2.9 6 1.3

6.7 6 1.5

3.2 6 1.6

Doppler strain rate, 1/s (n 5 33)

1.7 6 0.4

1.6 6 0.4

1.6 6 0.4

1.7 6 0.3

1.6 6 0.3

1.7 6 0.3

1.6 6 0.3

1.6 6 0.3

Doppler strain, % (n 5 33)

19 6 4

18 6 5

17 6 3

19 6 4

20 6 4

21 6 2

18 6 4

17 6 3

MRI strain, % (n 5 11)

17 6 3

18 6 4

17 6 3

19 6 5

18 6 4

19 6 3

18 6 4

17 6 4

Data from Edvardsen, T., Gerber, B.L., Garot, J., Bluemke, D.A., Lima, J.A., Smiseth, O.A., 2002. Quantitative assessment of intrinsic regional myocardial deformation by Doppler strain rate echocardiography in humans: validation against three-dimensional tagged magnetic resonance imaging. Circulation. 106 (1), 50 56. PubMed PMID:12093769, Table 1.

TABLE 6.15 Peak Radial Myocardial Strain in Healthy Volunteers Segments Anterior Tissue Doppler velocities, cm/s (n 5 33)

3.4 6 0.8

Posterior 4.4 6 0.6

Doppler strain rate, 1/s (n 5 33)

1.6 6 0.2

1.8 6 0.4

Doppler strain, % (n 5 33)

18 6 6

18 6 9

MRI strain, % (n 5 11)

19 6 4

17 6 6

Data from Edvardsen, T., Gerber, B.L., Garot, J., Bluemke, D.A., Lima, J.A., Smiseth, O.A., 2002. Quantitative assessment of intrinsic regional myocardial deformation by Doppler strain rate echocardiography in humans: validation against threedimensional tagged magnetic resonance imaging. Circulation. 106 (1), 50 56. PubMed PMID:12093769, Table 2.

Furthermore, these healthy subjects exhibited relatively uniform longitudinal and radial strain around the entire left ventricle. For patients with myocardial infarction, there were dramatic differences in myocardial strain when comparing the locations of infarction versus remote locations away from the infarctions (Table 6.16). For both anterior and posterior myocardial infarctions the infarcted regions exhibited significant radial thinning while the noninfarcted regions thickened significantly. For longitudinal deformation, while the

infarcted regions exhibited no deformation, the noninfarcted regions shortened significantly.

MYOCARDIAL DEFORMATION ESTIMATED FROM CORONARY ARTERY MOTION Although the myocardium is a natural target for medical imaging with its thick dimensions and ecofriendly location in the body, tracking myocardial tissue is nontrivial due to the lack

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TABLE 6.16 Peak Systolic Radial and Longitudinal Strains in Patients With Myocardial Infarction Radial Thickening (%) Region

Strain Doppler Echo

Longitudinal Shortening (%) MRI

Strain Doppler Echo

MRI

Anterior Infarct (n 5 10) Infarct

5.9 6 3.3

4.6 6 4.5

1.1 6 4.5

1.0 6 4.7

Remote

10.0 6 3.4

12.5 6 7.9

15.1 6 3.5

15.3 6 3.6

Infarct

9.2 6 5.1

6.8 6 4.3

2.3 6 3.9

0.8 6 5.2

Remote

16.4 6 4.2

16.3 6 4.6

14.9 6 4.3

16.2 6 3.9

Posterior Infarct (n 5 7)

Infarct—location of infarction; remote—noninfarcted located remote to the infarction. Data from Edvardsen, T., Gerber, B.L., Garot, J., Bluemke, D.A., Lima, J.A., Smiseth, O.A., 2002. Quantitative assessment of intrinsic regional myocardial deformation by Doppler strain rate echocardiography in humans: validation against three-dimensional tagged magnetic resonance imaging. Circulation. 106 (1), 50 56. PubMed PMID:12093769, Table 3.

of consistently identifiable landmarks on myocardium (Young et al., 1992). Thus Young et al. investigated an alternative approach for inferring myocardial deformation by measuring the motion of superficial coronary artery bifurcation points from biplane coronary angiography. They discovered that 3D motions of the coronary bifurcation points provide an indirect method to estimate regional variations in segmental shortening and epicardial velocity since the coronary arteries tend to be embedded in the myocardium. Specifically, segmental length changes between bifurcation points represent the average myocardial strain between those bifurcation points. Note that the myocardial strain estimations are averages along the length between the bifurcation points and may encompass highly heterogeneous regions exhibiting nonhomogeneous strain. Despite this limitation, this approach provides a mechanistic relationship between myocardial and coronary deformations, and principal strains were estimated as 10% 30% (Young et al., 1992). More recently, Choi et al. (2014a) extracted endocardial and epicardial surfaces of the left ventricle from six subjects, and correlated myocardial thickness change (i.e., radial strain) with curvature changes of the LAD coronary artery (Choi et al., 2014a). From this pilot study, Choi et al. reported

increases in coronary artery curvature of 0.43 6 0.63 cm21 and myocardial thickness of 3.9 6 2.2 mm from diastole to systole. The investigators also demonstrated a potential relationship between coronary artery and myocardial deformations by applying the support vector machinelearning algorithm to predict the myocardial thickness change from geometric parameters of the coronary arteries (Fig. 6.17) (Choi et al., 2014a).

AORTIC VALVE MOTION AND DEFORMATION With the emergence and recent growth of transcatheter aortic valve replacement (TAVR) therapy, aortic annulus geometry and deformation assessment have become critical for device sizing and procedural strategy. Imaging modalities such as multidetector CT and transesophageal echocardiography, and aortic valvuloplasty balloons have provided guidance for therapeutic strategy and have increased our understanding of aortic root anatomy (Kasel et al., 2013; Clavel et al., 2015). Moreover, assessing the dynamic nature of the aortic annulus is critical for evaluating the mechanical durability of TAVR devices, which are less robust than surgically placed replacement valves.

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FIGURE 6.17 Estimation of myocardial deformation from coronary artery deformation using coronary computed tomography data and machine-learning algorithm. Heart axes are defined on the long axis from the base to the apex, and on the lateral axis from the center of the septum to the center of the mitral valve (A). The thickness of the myocardium is computed as the distance between epicardial and endocardial surfaces along the projection of the LAD coronary artery (B). Six LAD centerlines are projected onto the normalized myocardial plane (C). LAD curvature change and myocardial thickness change between diastolic and systolic phases (D) were used as training data sets for the support vector machine algorithm in order to predict myocardial thickness change with LAD curvature change. Moderate correlation of predicted myocardial thickness change with actual measurements is shown (E). LAD, Left anterior descending. From Choi, G., Koo, B., Cheng, C.P., 2014a. TCT-305 quantification of coronary artery and myocardial deformation due to cardiac motion using cardiac-gated computed tomography data. J. Am. Coll. Cardiol. 64 (Suppl. 11), B88; http://dx.doi.org/10.1016/j.jacc.2014.07.350, Figure 1.

Hamdan et al. (2012) assessed the in vivo deformation and mechanical properties of the aortic annulus throughout the cardiac cycle in 35 patients with aortic stenosis and 11 normal subjects using 256-slice CT. Fig. 6.18 shows the graphical variation of aortic annulus change over the cardiac cycle, and Table 6.17 summarizes the range of values of each geometric parameter. This study demonstrated an

increase in the minimum diameter and decrease in ellipticity from diastole to systole. The cross-sectional area increased by 11.2 6 5.4% and 6.2 6 4.8% for subjects with normal and calcified aortic valves, respectively, indicating dramatically lower compliance in stenotic aortic valves. Blanke et al. (2012) performed extensive analysis of conformational pulsatile changes of

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111

FIGURE 6.18 Cross-sectional aortic annulus dimensions in normal subjects (left column) and patients with calcified aortic stenosis (right column). Min diameter (top row), EI (second row), aortic annulus CSA (third row), and Perim (bottom row) are shown throughout the cardiac cycle. CSA, Cross-sectional area; EI, ellipticity index; Min, minimum; Perim, perimeter. From Hamdan, A., Guetta, V., Konen, E., Goitein, O., Segev, A., Raanani, E., et al., 2012. Deformation dynamics and mechanical properties of the aortic annulus by 4-dimensional computed tomography: insights into the functional anatomy of the aortic valve complex and implications for transcatheter aortic valve therapy. J. Am. Coll. Cardiol. 59 (2), 119 127. PubMed PMID: 22222074, Figure 3.

the aortic annulus in 110 patients with severe aortic stenosis using electrocardiogram-gated CT. This study concluded that the aortic annulus exhibited significant pulsatile changes

throughout the cardiac cycle, and commented on the potential risk of TAVR device undersizing if based on diastolic perimeter- or areaderived diameter (Fig. 6.19; Table 6.18).

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TABLE 6.17

Maximum, Minimum, and Change of Cross-Sectional Aortic Annulus Dimensions in Normal Subjects and Patients With Aortic Stenosis Normal Subjects

Min. Values

Delta %

Max. versus Max.a Min. versus Min.b

12.3 6 7.3 12.3 6 1.4 (22.6 6 2.9)

11.1 6 1.2* (20.4 6 2.7)

9.8 6 3.4

.19

.04

1.21 6 0.07**

12.7 6 8.8 1.35 6 0.10

1.19 6 0.08*

10.3 6 2.7

.59

.34

239 6 25 (448 6 81.8)

211 6 31* (398.7 6 93.7)

11.2 6 5.4 257 6 40.9 (480.9 6 108)

234 6 38.2* (438.8 6 103)

6.2 6 4.8

.14

.07

40.9 6 3.0 (76.1 6 6.7)

39.7 6 2.6*** (74.1 6 7.6)

2.2 6 2.2

41.9 6 4.3* (77.3 6 8.6)

0.56 6 0.85 .17

.11

Parameters

Max. Values Min. Values

Delta %

Min. diameter index, mm/m2 (absolute value in mm)

11.7 6 1.1 (21.7 6 1.8)

10.2 6 0.9* (19.0 6 2.6)

Ellipticity

1.38 6 0.10

Area index, mm /m (absolute value in mm2) Perimeter index, mm/m2 (absolute value in mm)

2

a

2

P Value

Patients With Aortic Stenosis Max. Values

42.7 6 4.6 (78.9 6 8.7)

Max. values in normal subjects versus Max. values in patients with aortic stenosis. Min. values in normal subjects versus Min. values in patients with aortic stenosis. Values are mean 6 SD. Max. 5 maximum; Min. 5 minimum. *P , .001; **P 5 .002; ***P 5 .01 for Max. versus Min. values in the same group by paired t test. Data from Hamdan, A., Guetta, V., Konen, E., Goitein, O., Segev, A., Raanani, E., et al., 2012. Deformation dynamics and mechanical properties of the aortic annulus by 4-dimensional computed tomography: insights into the functional anatomy of the aortic valve complex and implications for transcatheter aortic valve therapy. J. Am. Coll. Cardiol. 59 (2), 119 127. PubMed PMID: 22222074, Table 2.

b

AORTIC VALVE MOTION AND DEFORMATION

113

FIGURE 6.19 Change of average area-derived diameter (DA) and perimeter-derived diameter (DP) throughout the cardiac cycle. Time-varying average DA and DP (A), relative change of DA and DP with values at 95% of the R R interval as reference (B), and difference between DA and DP (C) are plotted for the patient population. From Blanke, P., Russe, M., Leipsic, J., Reino¨hl, J., Ebersberger, U., Suranyi, P., et al., 2012. Conformational pulsatile changes of the aortic annulus: impact on prosthesis sizing by computed tomography for transcatheter aortic valve replacement. JACC Cardiovasc. Interv. 5 (9), 984 994. PubMed PMID: 22995887, Figure 3.

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TABLE 6.18 Maximum, Minimum, and Change in Annulus Dimensions in Patients With Severe Aortic Stenosis Maximum

Minimum

P Value Absolute Change

P Value Relative Change P Value ,.001

483.4 6 75.2 mm (332 720 mm2)

410.5 6 68.7 mm (279 619 mm2)

,.001

72.9 6 22.6 mm (34 120 mm2)

Perimeter 79.6 6 6.0 mm (66.8 97.3 mm)

74.2 6 5.7 mm (61.1 90.5 mm)

,.001

5.4 6 1.5 mm (2.6 9.6 mm)

DA

24.7 6 1.9 mm (20.6 30.3 mm)

22.8 6 1.9 mm (18.9 28.1 mm)

,.001

2.0 6 0.6 mm (0.9 3.2 mm)

DP

25.3 6 1.9 mm (21.3 31.0 mm)

23.6 6 1.8 mm (19.5 28.8 mm)

,.001

1.7 6 0.5 mm (0.8 3.1 mm)

CSA

2

2

2

18.2 6 6.1% (7.7% 34.1%)

,.001

7.3 6 2.1% (3.4% 11.5%) ,.001

8.7 6 2.8% (3.8% 15.8%)

,.001

7.3 6 2.1% (3.4% 11.5%)

Values are mean 6 range. CSA, cross-sectional area; DA, area-derived diameter; DP, perimeter-derived diameter. Data from Blanke, P., Russe, M., Leipsic, J., Reino¨hl, J., Ebersberger, U., Suranyi, P., et al., 2012. Conformational pulsatile changes of the aortic annulus: impact on prosthesis sizing by computed tomography for transcatheter aortic valve replacement. JACC Cardiovasc. Interv. 5 (9), 984 994. PubMed PMID: 22995887, Table 3.

CONCLUSION The coronary vasculature and heart structures undergo dramatic and frequent deformations. Since the coronary arteries are embedded in the myocardium, the complex 3D structure and dynamics of the coronary tree and myocardium are intimately linked. The coronary arteries experience significant axial shortening, bending, twisting, and bifurcation angle deformation from diastole to systole, while the myocardium of the left ventricle experiences longitudinal shortening, radial thickening, and circumferential shortening. The presence of disease and implants can significantly impact the geometry and compliance of the native tissues, warranting disease- and device-specific investigations. Advances in medical imaging and quantification techniques have made deformation and strain measurements possible, which are critical for understanding the complex dynamic environment of the coronary arteries and heart structures.

References Blanke, P., Russe, M., Leipsic, J., Reino¨hl, J., Ebersberger, U., Suranyi, P., et al., 2012. Conformational pulsatile changes of the aortic annulus: impact on prosthesis

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incremental elastic modulus. Int. J. Cardiol. 13 (1), 27 45. PubMed PMID: 3771000. Stuber, M., Scheidegger, M.B., Fischer, S.E., Nagel, E., Steinemann, F., Hess, O.M., et al., 1999. Alterations in the local myocardial motion pattern in patients suffering from pressure overload due to aortic stenosis. Circulation. 100 (4), 361 368. PubMed PMID: 10421595. Topol, Eric J., 2000, Cleveland Clinic Heart Book, New York : Hyperion, ISBN: 9780786864959. Tuncay, V., Vliegenthart, R., den Dekker, M.A.M., de Jonge, G.J., van Zandwijk, J.K., van der Harst, P., et al., 2018. Non-invasive assessment of coronary artery geometry using coronary CTA. J. Cardiovasc. Comput. Tomogr. 12 (3), 257 260. Available from: https://doi. org/10.1016/j.jcct.2018.02.003. Epub February 19, 2018. PubMed PMID: 29486988. Young, A.A., Hunter, P.J., Smaill, B.H., 1992. Estimation of epicardial strain using the motions of coronary bifurcations in biplane cine´angiography. IEEE Trans. Biomed. Eng. 39 (5), 526 531. PubMed PMID: 1526643. Zhu, H., Warner, J.J., Gehrig, T.R., Friedman, M.H., 2003. Comparison of coronary artery dynamics pre- and poststenting. J. Biomech. 36 (5), 689 697. PubMed PMID:12694999.

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C H A P T E R

7

Arteries of the Head and Neck D. Frakes1 and Christopher P. Cheng2 1

School of Biological and Health Systems Engineering, School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, AZ, United States 2Division of Vascular Surgery, Stanford University, Stanford, CA, United States

The importance of the head and neck arteries is clear given their role in supplying blood to one of the most critical human organs, the brain, which is particularly demanding in terms of oxygen consumption. Although the brain accounts for only about 2% of the human body’s weight, it consumes approximately 20% of the body’s oxygen. The brain is also particularly sensitive to oxygen deprivation as demonstrated by the severe repercussions associated with cerebrovascular diseases, including brain aneurysms and stroke. It follows that arteries of the head and neck have become popular sites for endoluminal therapies designed to prevent catastrophic outcomes of cerebrovascular disease. The head and neck arteries also present an interesting dichotomy in the context of motion. The cerebral arteries, surrounded by dense brain tissue, are generally considered to deform very little. Vessels of the neck, on the other hand, often deform visibly when simply observed from outside of the body. In this chapter, we will cover the anatomy of the head and neck arteries with particular emphasis on

Handbook of Vascular Motion DOI: https://doi.org/10.1016/B978-0-12-815713-8.00007-3

the carotid and vertebrobasilar arteries, which supply most of the blood flow to the head and neck. We will also examine deformations of the head and neck arteries caused by cardiac pulsatility and musculoskeletal motions and explore external influences, including medical devices.

CAROTID ARTERY ANATOMY The left and right common carotid arteries (CAs) (CCAs) both originate from the aorta. The left CCA originates directly from the aorta like the left subclavian artery, whereas the right CCA originates from the brachiocephalic trunk along with the right subclavian artery. As they ascend into the neck, the CCAs bifurcate into internal and external CAs (ICAs and ECAs, respectively) near the upper border of the thyroid cartilage, around the level of the fourth cervical vertebrae. The ICAs supply approximately 80% of the blood flow to the brain, while the ECAs supply blood flow to the neck and face (Tallarita et al., 2010).

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FIGURE 7.1 Illustration of the internal carotid artery and its branches in the context of the skeletal system. Source: From musculoskeletalkey.com.

The ICAs traverse superiorly inside the carotid sheath then pass through the carotid canal of the temporal bone to enter the brain, as shown in Fig. 7.1. There are no branches from the ICAs to the face or neck. Upon entering the cranial cavity the ICAs extend anteriorly beside the sphenoid bone and through the cavernous sinus, which is surrounded by the sympathetic nerve plexus from the superior cervical ganglion (Arslan et al., 2017). The abducens nerves at the sinus adhere to the ICAs on their lateral borders. Further distal and near the cranial nerves, each artery gives rise to several more. The anterior cerebral artery supplies blood to a portion of the cerebrum, the posterior communicating artery provides an anastomotic connection to the circle of Willis, and the

ophthalmic artery perfuses orbital tissues. Distal to these vessels, the ICAs proceed as the middle cerebral artery, which perfuses the lateral cerebrum. The ECAs, which perfuse the face and neck, emerge from the CCAs then ascend through the upper neck near the lower jaw and into the parotid glands as shown in Fig. 7.2. Specifically, they follow a superior and posterior trajectory between the auricle lobule and mandible neck. The ECAs give rise to the following six arteries (in ascending order): superior thyroid, ascending pharyngeal, lingual, facial, occipital, and posterior auricular. They then bifurcate to form two terminating branches, the maxillary and superficial temporal arteries (Yilmaz et al., 2015). These collective arteries perfuse anatomy, including the

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FIGURE 7.2 Illustration of the external carotid artery and its branches in the context of the skeletal system. Source: From musculoskeletalkey.com.

larynx, pharynx, thyroid gland, sublingual gland, submaxillary glands, dura matter, tongue, face, teeth, and palates.

CAROTID ARTERY MOTION FROM CARDIAC PULSATILITY Carotid Artery Diameter Changes Pulsatile flow can cause dramatic deformations in the CAs. Perhaps most

straight- forward among these is the crosssectional deformation characteristic of the arteries over the course of the heart cycle. Although the CAs may never be perfectly circular, measuring their diameter over the heart cycle has become an accepted metric for capturing expansion and contraction. A typical waveform demonstrating diametric variation of the CCA over the course of the heart cycle is shown in Fig. 7.3. Although the CAs can be imaged with several different imaging modalities including

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FIGURE 7.3 Example waveform representing the diameter of the common carotid artery over the course of a heart cycle. Source: From Persson, M., Ahlgren, A.R., Jansson, T., Eriksson, A., Persson, H.W., Lindstro¨m, K., 2003. A new non-invasive ultrasonic method for simultaneous measurements of longitudinal and radial arterial wall movements: first in vivo trial. Clin. Physiol. Funct. Imaging 23, 247 251, Figure 7.

magnetic resonance, computed tomography, and ultrasound imaging, ultrasound has been particularly popular due to its low cost, portability, lack of radiation, and the accessibility of the CAs. Regardless of modality, there are different ways of measuring CA diameter given that the artery is three-dimensional (3D), and diameter is a one-dimensional measurement. There are of course also different conditions under which measurements can be taken. Pomella et al. (2017) used the following protocol to measure CCA diameter over time. A SSD-5500 ultrasound system (Aloka, Tokyo, Japan) equipped with a 7.5 MHz linear-array vascular probe was used to image with a resolution of 0.013 mm. Scans were performed in the longitudinal view approximately 2 cm proximal to the bifurcation. The images were optimized to ensure that the depth was as shallow as possible, and the vessel walls were well delineated (i.e., that there was clear discrimination among the lumen, media intima, and adventitia). The insonation angle was maintained between 58 and 60 degrees, and diameter was calculated as the distance between the two walls of the CCA over

time. Every measurement was taken for at least 6 s at a sampling rate of 1000 Hz and repeated six times. Twelve healthy volunteers (aged 27 6 2 years, six females, body mass: 66.9 6 5.7 kg, height: 1.69 6 0.1 m, body mass index: 23.3 6 1.2 kg/m2) participated in the study. The participants were tested twice (once per day on 2 consecutive days) at the same time of the day, refrained from vigorous exercise and caffeine consumption for 24 and 12 h, respectively, before the laboratory visits, and maintained the same diet for the 2 days. The tests were conducted with participants in a reclined position and their upper bodies in the semirecumbent position. Data analysis was performed in MATLAB (MathWorks, Natick, MA, USA). A second-degree Savitzky Golay filter (Savitzky and Golay, 1964) with a 16-point halfwidth window was applied to mitigate highfrequency noise. For each measurement, best-quality consecutive heart cycles were selected based on whether or not typical physiologic features (such as the dicrotic notch) were retained. The features were also monitored to ensure that no obvious drift or damping was present.

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TABLE 7.1

Change in Common Carotid Artery Diameter at Rest

Common Carotid Artery Diameter Change at Rest Rest Day 1

Rest Day 2

Mean 6 standard deviation (mm)

0.59 6 0.15

0.60 6 0.14

Intraclass correlation coefficient

0.96

Coefficient of variation (%)

6.0

From Pomella, N., Wilhelm, E.N., Kolyva, C., Gonzalez-Alonso, J., Rakobowchuk, M., Khir, A.W., 2017. Common carotid artery diameter, blood flow velocity, and wave intensity responses at rest and during exercise in young healthy humans: a reproducibility study. Ultrasound Med. Biol. 43, 943 957.

Results from the Pomella et al. study are shown in Table 7.1. All values are expressed as mean 6 standard deviation. Statistical analyses were performed using SPSS Statistics (IBM, Armonk, NY, USA). Tukey’s test was performed for the detection of outliers (Hoaglin and Iglewicz, 1987; Hoaglin et al., 1986; Tukey, 1977). All variables were tested for normality using the Shapiro Wilk test (Shapiro and Wilk, 1965). Subsequently, a two-tailed Student t-test determined whether the data differed between testing days. The intraclass correlation coefficients (ICCs) were calculated between the 2 days of testing to measure intersession variability. The within-patient coefficient of variation (CV) between testing days was also calculated for each participant and then averaged across all participants to measure the dispersion of the data around the mean during rest as opposed to exercise (the latter category of activity is discussed later). Interobserver reproducibility was assessed via ICCs between data set means, by taking into account all measurement sessions for both testers. An ICC . 0.7 was classified as “high reproducibility,” an ICC , 0.5 as “low reproducibility,” and an ICC within 0.5 0.7 as “moderate reproducibility” (Portney and Watkins, 2000). A CV $ 20% was considered “high dispersion,” a CV # 10% was considered “low dispersion,” and the range between the two was considered “moderate dispersion.”

While the Pomella protocol detailed above provides an example methodology for quantifying CCA diameter change over time, it is noteworthy that many different ultrasound studies employing a variety of methodologies have been executed—often producing quite different results. For example, Studinger et al. (2003) examined a slightly smaller number of participants (i.e., 10 subjects), imaged with a different ultrasound system equipped with a 7.5 MHz linear-array vascular probe [i.e., Scanner 200 (Pie Medical, Maastricht, The Netherlands)], measured at a slightly different location within the CCA (i.e., 1.5 cm proximal to the bifurcation), and took repeat measurements separated by greater lengths of time (i.e., 7 14 days). The Studinger study reported greater CCA diameter changes of 0.804 6 0.035 mm. In contrast, Morganti et al. (2005) examined a larger cohort of participants (i.e., 41 subjects), measured CCA diameter differently (i.e., using a modified two-dimensional autocorrelation algorithm), and collected data in singular sessions. The Morganti study reported smaller CCA diameter changes of 0.499 6 0.188 mm. Accordingly, it is clear that even when measuring CCA diameter change using a common modality such as ultrasound, study protocol and implementation details can have a considerable impact on quantitative results. A number of studies have also looked at the effects that exercise and disease have on CA

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TABLE 7.2

Change in Common Carotid Artery Diameter During Exercise

Common Carotid Artery Diameter Change During Exercise Exercise Day 1

Exercise Day 2

Mean 6 standard deviation (mm)

0.71 6 0.16

0.74 6 0.16

Intraclass correlation coefficient

0.96

Coefficient of variation (%)

5.3

From Pomella, N., Wilhelm, E.N., Kolyva, C., Gonzalez-Alonso, J., Rakobowchuk, M., Khir, A.W., 2017. Common carotid artery diameter, blood flow velocity, and wave intensity responses at rest and during exercise in young healthy humans: a reproducibility study. Ultrasound Med. Biol. 43, 943 957.

diameter change. For example, the Pomella et al. study acquired parallel measurements while each of the subjects was pedaling a supine bicycle ergometer. Exercise measurements were taken after 2 3 min of pedaling at a low cadence (i.e., 30 50 rpm) and work rate (i.e., 20 40 W) and then increasing to a cadence of 60 rpm and work rates of 80 W for males and 50 W for females (exercise period). The latter phase corresponded to roughly 30% 35% of the participants’ maximum workload (Fletcher et al., 2013; Sallis et al., 1985). Recording of the measurements started 3 min into the exercise period, and the complete protocol lasted approximately 20 min. Results from the Pomella exercise study are shown in Table 7.2. As Pomella et al. reported, mean change in CCA diameter was considerably larger during exercise (i.e., 0.71 and 0.74 mm) as opposed to at rest (i.e., 0.59 and 0.60 mm). Similar findings were reported by Studinger et al. (2003), who measured diameter changes of 0.891 6 0.047 mm during exercise. Once again, however, the values reported by Studinger et al. were considerably larger than those reported by Pomella et al. Apart from the aforementioned protocol discrepancies, the difference in this case may be explained by the greater work rate (i.e., maximum effort) targeted by the Studinger study. An exploratory ultrasound study by Smilde et al. (1998) investigated CCA dynamics in populations affected by a number of different

disease states and/or lifestyles, including homocystinuria, premature vascular disease, hypertension, and smoking. Although change in CCA diameter was measured directly as in the aforementioned studies, the authors chose to characterize arterial dynamics through a distensibility coefficient: Distensibility Coefficient 5

2 3 ΔD=D ; ΔP

where D represents CCA diameter, ΔD represents change in CCA diameter, and ΔP represents change in pulse pressure at the site of the brachial artery. The study observed decreased distensibility of the CCA in cohorts affected by vascular disease, hypertension, and smoking as reported in Table 7.3. Ultimately, the study found distensibility coefficient to be statistically affected by underlying factors including age, low-density lipoprotein cholesterol, and systolic blood pressure. The following is a literature summary of pulse pressure, diametric distension percentage, and distensibility coefficient of the CCA for different subject populations (Table 7.4). It includes healthy children and adults, and patients with hypertension, impaired glucose metabolism, and diabetes (Kawasaki et al., 1987; Benetos et al., 1993; Willekes et al., 1998; Henry et al., 2003). Note that diametric distension and distensibility coefficient decrease with increasing age,

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TABLE 7.3 Common Carotid Artery Distensibility Coefficient for Healthy Control, Vascular Disease, Hypertension, and Smoking Cohorts

21

Mean right CCA DC 6 SD (kPa

21

Mean left CCA DC 6 SD (kPa

Control

Vascular Disease

Hypertension

Smoking

3 10 )

23.5 6 6.9

15.3 6 3.1

9.9 6 5.2

17.7 6 5.7

23

20.9 6 6.4

14.2 6 4.2

9.3 6 4.3

16.1 6 5.6

23

3 10 )

CCA, Common carotid artery; DC, distensibility coefficient; SD, standard deviation. From Smilde, T., ven den Berkmortel, F., Boers, G., Wollersheim, H., de Boo, T., van Langen, H., et al., 1998. Carotid and femoral wall thickness and stiffness in patients at risk for cardiovascular disease, with special emphasis on hyperhomocysteinemia. Arterioscler. Thromb. Vasc. Biol. 18, 1958 1963.

TABLE 7.4 Summary of Population, Pulse Pressure, and Diametric Distension of the Femoral Artery in Healthy Volunteers and Patients With Cardiovascular Disease Risk Factors Pulse P (mmHg)

Diametric Distension (%)

Distensibility Coefficient (kPa21 3 1023)

0 19 years

46

14 6 4

60.9 6 17.4

20 39 years

47

962

38.3 6 8.5

40 59 years

47

762

29.8 6 8.5

60 81 years

53

561

18.9 6 3.8

Benetos et al. (1993)

Healthy/Hypertensive, 47 6 6 years

5.7 6 2.2

6.07 6 0.28

21.6 6 1.75

Willekes et al. (1998)

Healthy women, 18 35 years

47 6 6

11.2 6 2.9

35.9 6 8.9

Henry et al. (2003)

Normal glucose metabolism, 68.7 6 6.1 years

59 6 17

4.51 6 1.32

12.82 6 4.34

Henry et al. (2003)

Impaired glucose metabolism, 70.3 6 6.3 years

62 6 14

4.30 6 1.14

11.56 6 4.55

Henry et al. (2003)

Type 2 diabetic, 67.3 6 8.1 years

68 6 16

4.18 6 1.36

10.44 6 4.25

Study

Population

Kawasaki et al. (1987)

Healthy

Literature review of carotid pulsatility. Pulse P, Arterial pulse pressure.

and with the presence of cardiovascular disease. Pulsatile diametric distension is 14% 6 4% for healthy children # 19 years old and steadily decreases to 9% 6 2%, 7% 6 2%, and 5% 6 1% for healthy adults aged 20 39, 40 59, and 60 81 years old (Kawasaki et al., 1987). The data from Benetos et al. (1993) and Willekes et al. (1998) agree with these numbers. Diametric distension also appears to decrease with compromised glucose metabolism, with

percent distension of 4.51% 6 1.32%, 4.30% 6 1.14%, and 4.18% 6 1.36% for subjects with normal metabolism, impaired metabolism, and type 2 diabetes, respectively, with all groups age matched (Henry et al., 2003). In addition, while diametric distensibility decreases with increased age and disease, pulse pressure increases with age and disease, translating into dramatically decreased distensibility coefficient.

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Longitudinal Motion of the Carotid Artery Among motions of the CA, diameter change or radial motion may be the most thoroughly studied to date; however, longitudinal motion of the CA has received considerable attention in recent years. Longitudinal motion differs from radial motion as illustrated in Fig. 7.4. CA longitudinal motion (CALM) was first confirmed in the human CCA by Golemati et al. (2003) and Persson et al. (2003). Both studies measured CALM by applying block matching to ultrasound images like the example shown in Fig. 7.5. Sample waveforms from the Persson study that depicts longitudinal (axial) motion of the anterior and posterior walls of the CCA are shown in Fig. 7.6. Measurements were taken approximately 3 cm proximal to the carotid bifurcation. A 2016 study by Au et al. (2016) went beyond simply measuring CALM to establish relationships between CALM and the mechanics of the heart. Simultaneous ultrasound measurements of CALM, CCA mean blood velocity, and left ventricular motion were acquired in 10 healthy subjects (6 males; 22 6 1 years). Peak anterograde CALM was observed at a similar time point as compared to peak mean blood velocity (18.57% 6 3.98% vs 18.53% 6 2.81% of the cardiac cycle). Maximum retrograde CALM displacement demonstrated different timing compared to left ventricular motion, but related to both peak apical rotation (41.00% 6 7.81% vs 35.33% 6 5.79% of the cardiac cycle) and peak basal rotation (41.80% 6 6.12% vs 37.30% 6 5.66% of the cardiac cycle), with peak cardiac displacements in both cases occurring before peak CALM displacements. The association between basal rotation and retrograde CALM was further supported by strong correlations between their peak amplitudes. The results from the Au study suggest that the rotational mechanical movement of the left ventricle (LV) base may be closely related to CALM.

FIGURE 7.4 Illustration of longitudinal versus radial motion. Source: From Persson, M., Ahlgren, A.R., Jansson, T., Eriksson, A., Persson, H.W., Lindstro¨m, K., 2003. A new noninvasive ultrasonic method for simultaneous measurements of longitudinal and radial arterial wall movements: first in vivo trial. Clin. Physiol. Funct. Imaging 23, 247 251, Figure 1.

FIGURE 7.5

Ultrasound image of the common carotid artery with blocks where motion was measured over time indicated by the black and white boxes. The direction of flow is indicated by the white arrow. Source: From Persson, M., Ahlgren, A.R., Jansson, T., Eriksson, A., Persson, H.W., Lindstro¨m, K., 2003. A new non-invasive ultrasonic method for simultaneous measurements of longitudinal and radial arterial wall movements: first in vivo trial. Clin. Physiol. Funct. Imaging 23, 247 251, Figure 3.

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CAROTID ARTERY MOTION FROM MUSCULOSKELETAL MOVEMENT WITH AND WITHOUT MEDICAL DEVICES

FIGURE 7.6 Longitudinal (axial) position of the common carotid artery versus time. The dashed line represents anterior wall position, and the solid line represents posterior wall position. Source: From Persson, M., Ahlgren, A.R., Jansson, T., Eriksson, A., Persson, H.W., Lindstro¨m, K., 2003. A new non-invasive ultrasonic method for simultaneous measurements of longitudinal and radial arterial wall movements: first in vivo trial. Clin. Physiol. Funct. Imaging 23, 247 251, Figure 4.

0.2 0.1

Longitudinal movement (mm)

125

0 –0.1 –0.2 –0.3 –0.4 –0.5 –0.6 –0.7 –0.8 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Time (s)

CAROTID ARTERY MOTION FROM MUSCULOSKELETAL MOVEMENT WITH AND WITHOUT MEDICAL DEVICES As the arteries of the head and neck are fundamental in maintaining healthy blood flow to the oxygen-hungry brain, they are often subject to treatment when cardiovascular pathologies threaten their function. For example, carotid endarterectomy (CEA) may be performed to restore normal blood flow in the CA when atherosclerosis has led to carotid stenosis. Treatment with angioplasty and CA stenting (CAS) represents another class of options wherein medical devices are deployed into (and remain in) the CA. The introduction of a medical device into any artery is of course an extreme environmental change that has many effects, including the alteration of vascular motion. Specific effects of different CA treatments were elucidated by Vos et al. (2003, 2005), who performed several studies examining CA motion and flow during musculoskeletal movement after treatments with and without stents. One Vos study employed time-of-flight magnetic

resonance angiography to capture 3D CA geometry and magnetic resonance flow quantification to measure CA flow (Vos et al., 2005). The cohort included six subjects after CAS (median age 70 years) and six subjects after CEA (median age 67 years). Five head positions were considered: neutral, bent forward, bent backward, turned to the treated ipsilateral side, and turned to the untreated contralateral side. Maximum-intensity projection reconstructions were produced to quantify the maximal angulation of the ICA in the forward, backward, ipsilateral, and contralateral positions as compared to neutral (Fig. 7.7). Next, 1 cm distal to the stent or 4 cm distal to the carotid bifurcation (in CEA patients), flow through a plane perpendicular to the ICA was measured. Volume flow rate through this plane was quantified for each position. In CAS patients the median ICA angulation change in the forward position was 110.2 degrees (interquartile range, 17.3 to 117.9 degrees), while in CEA patients, the median ICA angulation change in the forward position was only 10.2 degrees (interquartile range, 21.0 to 12.4 degrees). This indicates that the presence of the CA stent correlated with reduced bending

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FIGURE 7.7 Maximum-intensity projection reconstructions from (A) a carotid endarterectomy patient in the neutral position, (B) a carotid endarterectomy patient in the forward position, (C) a carotid artery stent patient in the neutral position, and (D) a carotid artery stent patient in the forward position. Source: MIP reconstructions, from Vos, J.A., Floris Vos, A.W., Linsen, M. A., Marcus, J.T., Overtoom, T., van den Berg, J., et al., 2005. Impact of head movements on morphology and flow in the internal carotid artery after carotid angioplasty and stenting versus endarterectomy. J. Vasc. Surg. 41, 469 475, Figure 3.

deformation with neck flexion, likely a consequence of added bending stiffness. There was no statistically significant difference in angulation change for any other head positions. Likewise, there was no statistically significant difference in volume flow rate change between groups in any of the head positions. This means that although there was a significant increase in ICA angulation in CAS patients when the head was bent forward, the change did not lead to significant changes in blood flow. Robertson et al. utilized cine X-ray fluoroscopy to investigate the effects of head turning

and swallowing on the CA immediately after CAS (Robertson et al., 2008). Patients (mean age 76.9 years) were treated with CAS for severe CA bifurcation atherosclerotic disease because they were considered high risk for endarterectomy surgery. Stent diameters were 6 10 mm and either 30 or 40 mm in length. All stents were nitinol tapered or nontapered open-cell designs. Epipolar geometric processing techniques were used to track the 3D geometries of the stents by using two orthogonal fluoroscopic views (i.e., anteroposterior and lateral). Specifically, the space between each “ring” of struts on the stent

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CAROTID ARTERY MOTION FROM MUSCULOSKELETAL MOVEMENT WITH AND WITHOUT MEDICAL DEVICES

was digitized in anteroposterior and lateral views, and the stent geometry was reconstructed in 3D space (Fig. 7.8). The digitization and 3D reconstruction process was repeated for each time point during the biomechanical cycle (i.e., during neck turning or swallowing) and compared to quantify motion and deformation (Robertson et al., 2008). For example, during swallowing motion, the lateral view of a left carotid stent shows posterior to anterior back to posterior position, and the anteroposterior view shows lateral to medial back to lateral position (Fig. 7.9). It is also apparent from the anteroposterior view that there is bending deformation at the midpoint of the stent during the maximum swallowing position. Metrics quantified included diametric crush, radial, axial length, and curvature deformations during swallowing and head turning in both directions (Fig. 7.10) (Robertson et al., 2008). Diametric crush refers to the noncircular deformation of the stent into an elliptical shape. This metric was computed based on the diameter of the stent rings measured in anteroposterior (dAP) and lateral views (dLAT). Radial strain was derived from the change in effective diameter (deff), which was calculated as the average of dAP and dLAT. Axial deformation was defined as the lengthening or shortening centerline path of the

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carotid stent in response to the motions. The stent’s centerline path was represented by a polynomial curve in order to enable quantification of arclength. Each of these metrics was calculated for segment lengths of five stent rings to reduce the effects of pixelation error. In addition, centerline curvature was calculated as the inverse of the radius of the circle fit onto the centerline points of three adjacent stent rings. Average radial deformations were generally very small magnitude (,0.5%) with swallowing and ipsilateral head turning (turning toward the side implanted with a stent); however, contralateral head turning (turning away from the side implanted with a stent) produced 1.7% radial contraction (Robertson et al., 2008). Note, however, that when averaging the maximum radial deformations for all patients, the deformations were in the |x| 5 2.5% 6.8% range, meaning there is dramatic variation along the stent length and within the population. Axial length changes averaged 3.5%, 4.4%, and 5.4% for swallowing, ipsilateral heading turning, and contralateral head turning, respectively, indicating a stretching of the stent with these biomechanical motions. This length change is in the opposite direction of what the superficial femoral arteries experience due to hip and knee flexion (Cheng et al., 2006). This means that while femoropopliteal arteries FIGURE 7.8 Digitizing the space between stent “rings” in lateral (left) and anteroposterior (right) X-ray fluoroscopic views. This example shows the process on a left carotid artery stent in the neutral head and neck position, with a close-up of red digitizing points between the stent rings (bottom, middle).

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7. ARTERIES OF THE HEAD AND NECK

FIGURE 7.9 Tracking of a left carotid artery stent during swallowing motion. From the lateral view (top row and bottom left graph) it is apparent that the stent translates anteriorly during swallowing then returns to a posterior position. The AP view (middle row and bottom right graph) shows a dramatic translation medially during swallowing, as well as a bending deformation at the middle of the stent. AP, Anteroposterior.

εcrush, AP

deflection d max d neutral AP AP neutral d AP

εradial

deflection d max d neutral eff eff d neutral eff

εcrush, LAT

deflection d max d neutral LAT LAT neutral d LAT

εAxial

L max deflection L neutral L neutral

FIGURE 7.10 Equations for defining maximum deformations for diametric crush in the anteroposterior view (top left), diametric crush in the lateral view (top left), radial deformation (top right), and axial arclength (bottom right).

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VERTEBROBASILAR ARTERY ANATOMY

tend to shorten with respect to the neutral position (straight legs) during everyday movement, CAs tend to lengthen with respect to the neutral position (neck straight, not swallowing). Diametric crush deformations varied widely along the length of the stent and within the patient population, with population-averaged maximum values in the 11.9% 14.9% range in both the anteroposterior and lateral directions (Robertson et al., 2008). Interestingly, while the average diametric crush deformations were low in response to head turning, swallowing was accompanied by average crushing of the stent in the anteroposterior direction and expansion in the lateral direction. This means that swallowing caused the CA stent to get relatively wider in the right left direction. This asymmetric response is likely due to the elevation of the larynx, whose closure and elevation prevents swallowed material from entering the trachea and lungs. When the larynx is elevated, so are the hyoid bone and thyroid cartilage, which allows the powerful, highly tensioned cervical musculature to push the CAs medially and anteriorly, as seen in Fig. 7.9. This notion is supported by the fact that the CA stents also bend inward with increased curvature during swallowing, with average maximum curvature values up to 0.31 cm21. Other studies have suggested that common motions such as head turning and nodding may pose a risk of stent fracture (Vos et al., 2003, 2005), which is supported by the diametric crush, radial, axial, and curvature deformations quantified by Robertson et al. (Robertson et al., 2008). However, during daily activities, mostly mild head nodding and turning will occur, while the head motions tested in the Robertson et al. study are extreme and relatively rare. The swallowing motion tested in the study, on the other hand, was representative of normal swallowing and may cause greater stent fatigue effects owing to its higher frequency. Since people constantly produce saliva and need to swallow it, even while asleep, the average person swallows approximately 500,000 times a

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year (Rudney et al., 1995). Furthermore, the location of greatest bending during swallowing coincides with the junction between the CCA and the ICA, where there is a sudden diametric tapering. This means that the strain concentration of bending is stacked on top of the strain concentration of diametric transition, which explains the reporting of CA stent fracture exactly at that location (Valibhoy et al., 2007).

VERTEBROBASILAR ARTERY ANATOMY The left and right vertebral arteries (VAs) originate from the left and right subclavian arteries, respectively, medial to the anterior

FIGURE 7.11 Illustration of the left vertebral artery in the context of the skeletal system. The vertebral artery is segmented into the first (proximal), second (transverse), third (suboccipital), and fourth (intracranial) parts. Source: From musculoskeletalkey.com.

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FIGURE 7.12 Illustrations of the vertebrobasilar artery system from the vascular-only (A), posterior (B), and left (C) perspectives. Source: From musculoskeletalkey.com.

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VERTEBROBASILAR ARTERY MOTION FROM NATURAL MUSCULOSKELETAL MOVEMENT

scalene musculature. They are typically considered to have four distinct segments as shown in Fig. 7.11: proximal, transverse, suboccipital, and intracranial. Starting with the proximal segment at C6 (in most people), the VAs ascend the posterior neck via the foramen transversarium, which are cavities in the transverse processes of the cervical vertebrae (Moshayedi et al., 2018). After passing through the foramen magnum the VAs enter the cranial cavity. Several branch arteries originate from the VAs in the cranial vault. The posterior inferior cerebellar artery perfuses the cerebellum, which plays an important role in motor control (e.g., regulating and coordinating muscular activity). The meningeal branch artery perfuses dura matter referred to as the falx cerebelli. The anterior and posterior spinal arteries perfuse the spinal cord and extend to cover its entire length. Distal to the aforementioned branch arteries, the left and right VAs come together to form the basilar artery. A number of small branch arteries, which perfuse the cerebellum and pons, originate from the basilar artery shortly after the VAs converge. The basilar artery then bifurcates into the posterior cerebral arteries, which are part of the circle of Wills as shown in Fig. 7.12. These and other arteries constitute the redundant structure of the circle, which ensures that even if one of its components is blocked, collateral circulation can still perfuse the brain to avoid ischemia. Overall, the vertebrobasilar artery system supplies approximately 20% of the oxygenated blood received by the brain.

VERTEBROBASILAR ARTERY MOTION FROM NATURAL MUSCULOSKELETAL MOVEMENT While the vertebrobasilar and other arteries of the cerebrovascular system do experience

131

motion from pulsatility, they are generally characterized by far less diameter change over time in comparison to the CAs. For example, middle cerebral artery diameter fluctuates so little that transcranial Doppler ultrasound operates on the assumption of constant diameter even across variability in blood pressures and blood gas concentrations (Verbree et al., 2017). It is noteworthy that this assumption has proven controversial in recent literature (Hoiland and Ainslie, 2016). In terms of musculoskeletal movement, however, the vertebrobasilar artery system can be subject to dramatic ranges of motion, which can in turn compromise blood flow and even lead to vertebrobasilar ischemia (Mitchell and Kramschuster, 2008). Mitchell et al. used real-time ultrasound to measure the changes in suboccipital VA diameter associated with cervical spine motion (Mitchell and Kramschuster, 2008). Thirty-five healthy female participants 20 30 years old were recruited from a student population. The participants were nonsmokers and nondrug users, and none were clinically obese. Further, no participants reported musculoskeletal issues, had participated in recent manipulations of the cervical spine, or experienced symptoms consistent with vertebrobasilar ischemia. An Acuson Sequoia pulsed-wave Doppler ultrasound system (Siemens, DE, USA) was used to insonate the third part of the VA (VA3) as illustrated in Fig. 7.13. A 6 MHz linear-array probe was employed to measure orthograde blood flow at insonation angles ranging from 10 to 40 degrees. Each subject was seated with spine supported, and with hips, knees, and ankles at 90-degree angles. Imaging began with the cervical spine in the neutral position and continued as each subject slowly rotated her head to left, back to neutral, and then to the right. All movements were actuated by the volunteers themselves under verbal guidance. Images of the VA3 region were taken approximately 1 cm distal to the VA’s departure from the atlas transverse

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FIGURE 7.13 Right lateral view of subject participant (A) and posterior view of registered internal anatomy (B). Label C1 indicates the atlas vertebra, C2 indicates the axis vertebra, O indicates the occiput, the arrow indicates the insonation angle, and VA3 indicates the suboccipital vertebral artery. Source: From Mitchell, J., Kramschuster, K., 2008. Real-time ultrasound measurements of changes in suboccipital vertebral artery diameter and blood flow velocity associated with cervical spine rotation. Physiother. Res. Int. 13, 241 254, Figure 1.

foramen. VA diameters were compared using a paired two-tailed t-test for the left and right rotation positions and corresponding neutral positions, for both the left and right VAs.

Results of the Mitchell study are illustrated in Fig. 7.14 (Mitchell and Kramschuster, 2008). Statistical analysis showed no significant difference in terms of vessel diameter between the neutral positions preceding left or right rotation. The same was true for contralateral rotations. However, for ipsilateral rotations, there was a significant decrease in diameter for both left and right VAs. The Mitchell study concluded that it is possible that the VA3 region may be compressed during ipsilateral rotation, which could reshape the vessel especially if tethered in the foramen or along the posterior atlas arch, thereby preventing the vessel from sliding to accommodate ipsilateral rotation (Haynes, 2004). More specifically, the VA3 region of the VA in some individuals may be vulnerable to considerable morphological distortion even during normal full-range ipsilateral rotation sustained for a minute or more. While Mitchell et al. focused on one specific region of vulnerability in the VA, concerns around compression along the entire arterial portion traversing through the transverse foramen from C6 to C1 have been raised (Mitchell and Kramschuster, 2008). Fixation to the spine in this region coupled with vertebral subluxation has long been cited as a potential mechanism of problematic tension and/or compression (Toole and Tucker, 1960; Brown and Tatlow, 1963). Sequences of movements, including rotation followed by extension and then traction, have also been proposed as particular stressors (Haynes, 1996). More recently, discussions in literature focused on ischemic blood flow in the vertebrobasilar artery system have connected the phenomenon to similar movements affecting vascular deformation. For example, a number of studies have demonstrated blood flow reductions in the VA during contralateral cervical rotation (Arnold et al., 2004; Li et al., 1999; Mitchell, 2003). Like the 2008 study by Mitchell et al., however, other studies also failed to recognize statistically significant changes under the same circumstances

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VERTEBROBASILAR ARTERY MOTION FROM MANIPULATION

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FIGURE 7.14 Mean values 6 standard deviation of vertebral artery diameter in mm at the suboccipital vertebral artery (VA3) region. LVA, Left vertebral artery; RVA, right vertebral artery; N, neural spine position; L and R, left and right cervical spine rotations, respectively; ipsi, ipsilateral cervical spine rotation; contra, contralateral cervical spine rotation; VA3, third part of the vertebral artery. ***Statistical significance with P # .001. Source: Adapted from Mitchell, J., Kramschuster, K., 2008. Real-time ultrasound measurements of changes in suboccipital vertebral artery diameter and blood flow velocity associated with cervical spine rotation. Physiother. Res. Int. 13, 241 254, Figure 3.

(Haynes et al., 2002). Regardless, there appears to be agreement that maximal mechanical stress on the contralateral artery occurs during cervical rotation and extension, which if sustained, can lead to delayed normalization of arterial flow patterns (Zaina et al., 2003). In rare cases, such cervical movement can naturally overextend (by as much as 30%) due to rupture of the alar ligament after motor vehicle accidents or because of congenital defects (Panjabi et al., 1991; Jo´nsson et al., 1994).

VERTEBROBASILAR ARTERY MOTION FROM MANIPULATION Even when head and neck movements are actuated naturally by an individual, moderateto-extreme ranges of motion (B20 degrees of cervical rotation and/or B20 degrees of extension) can constrict the VA such that little or no blood flows through the vessel (Endo et al., 2000). So it is not surprising that when the

head and neck are manipulated by external forces—from hair washing to chiropractic therapy—even more dangerous vertebrobasilar artery deformations can result. Beauty parlor stroke syndrome, for example, occurs when the neck of a customer receiving a shampoo treatment in a hair salon is hyperextended (Weintraub, 1993). The result can be an episode of vertebrobasilar insufficiency with cerebral infarction. Most likely, the condition is caused by VA compression at the atlantooccipital junction leading to VA stenosis and ultimately compromised blood flow. Unilateral VA insufficiency rarely results in any neurological deficits, however, due to collateral flow through the contralateral VA and other arteries (Golueke et al., 1987). Specifically, a study by Stern et al. reported flow rate increases of up to 100% in the contralateral CA during experimental VA occlusion (Stern, 1969). Whether or not ischemic affects are temporary, sufficient hyperextension of the neck can do lasting damage to the VA. Among

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nonpenetrating traumas to the artery, neck hyperextension (with rotation or without) and cervical side flexion are most frequent and can lead to stretching and tearing of the intima at sites where the VA attaches to bone (Auer et al., 1994; Bose et al., 1985). During a rotation, it is the artery contralateral to the side of the rotation that is most vulnerable to stretch injury (Tissington Tatlow and Bammer 1957; Fast et al., 1987; Ouchi and Ohara, 1973). Chiropractic spinal manipulation, particularly of the upper spine, has been proposed by many as a mechanism that can underlie dissection of the VA and ICA leading to stroke and death (Hillier and Gross, 1998; Peters et al., 1995; Jeret and Bluth, 2000; Klougart et al., 1996). VA dissection at the atlantoaxial joint as a result of chiropractic manipulation was noted specifically by Frisoni et al. (Frisoni and Anzola, 1991). However, 115 reports of manipulationinduced cerebrovascular accidents in 198 English-based articles from 1966 to 1998 provide little or no details around the specific forces applied or procedures followed during manipulations to support that they were dangerous. An alternative explanation is that the manipulations in question only aggravated preexisting conditions (Haldeman et al., 1999). Overall, the risk of vertebrobasilar artery dissection due to a manipulation has been estimated at 1 in 1.3 M to 1 in 400,000 manipulations (Assendelft et al., 1996; Dvorak and Orelli, 1985).

VERTEBROBASILAR ARTERY MOTION DUE TO MEDICAL DEVICES Entirely separate from vertebrobasilar artery motion due to musculoskeletal movements (natural or otherwise) is the motion that the vasculature can experience as a result of interacting with medical devices. The basilar artery bifurcation in particular has been examined frequently in this context. It is noteworthy that much of the work in this area applies to basilar arteries affected by aneurysms. One clearly presented example of vascular motion after medical device deployment was provided by Saglam et al. (2015). The study examined 19 patients ranging from 27 to 80 years old who underwent Y-stent configuration assisted coiling for basilar bifurcation aneurysms. Three different arterial angles were quantified. Angles B1 and B2 represented the angles between the basilar artery and the proximal segments (P1) of the right and left (respectively) posterior cerebral arteries. A third, angle A, represented the complementary angle between B1 and B2. Each angle was measured before and after deployment of the aforementioned Ystent configuration. An example of basilar artery geometry before and after stenting is shown in Fig. 7.15. What stands out about the study’s results is that statistically significant A, FIGURE 7.15 Illustration of B1 (left angle in green) and B2 (right angle in green) angular measures associated with prestented (left) and poststented (right) basilar tip aneurysm. Source: Adapted from Saglam, M., Kizilkilic, O., Anagnostakou, V., Yildiz, B., Kocer, N., Islak, C., 2015. Geometrical characteristics after Y-stenting of the basilar bifurcation. Diagn. Interv. Radiol. 21, 483 487, Figures 2 and 3.

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REFERENCES

TABLE 7.5 Measurements of the A, B1, and B2 Angles Before and After Stent Deployment as Quantified by Three Different Expert Radiologists Angle

Radiologist

Prestent ( ) Median (min, max)

A

1

177 (101, 263)

122 (73, 212)

41 (8, 122)

2

177 (103, 259)

120 (75,201)

48 (15, 132)

3

175 (101, 253)

122 (74, 202)

45 (14, 124)

1

89 (36, 119)

117 (60, 137)

27 (3,74)

2

86 (41, 117)

119 (66,133)

28 (7, 74)

3

86 (42, 113)

113 (67, 131)

26 (5, 67)

1

103 (57, 158)

121 (88,160)

13 (2, 67)

2

100 (56,154)

124 (92, 158)

18 (2,72)

3

104 (51, 159)

126 (91, 161)

17 (2, 78)

B1

B2

Poststent ( ) Median (min, max)

Angle Change ( ) Median (min, max)

A, Angle between right and left posterior cerebral arteries; B1, angle between right posterior cerebral artery and basilar artery; B2, angle between left posterior cerebral artery and basilar artery. From Saglam, M., Kizilkilic, O., Anagnostakou, V., Yildiz, B., Kocer, N., Islak, C., 2015. Geometrical characteristics after Y-stenting of the basilar bifurcation. Diagn. Interv. Radiol. 21, 483 487.

B1, and B2 value changes were recognized (P , .001), with smaller prestenting angles B1 or B2 correlating with larger poststenting angle changes (Table 7.5). Similar findings were reported by other investigators, although more so in the context of embolic coils than stents (Beller et al., 2016; Rai et al., 2018).

CONCLUSION The arteries of the head and neck experience deformation from cardiac pulsatility and movement of the musculoskeletal system in the head and neck region. Arterial pulse pressure causes radial distension of the CAs to varying degrees based on arterial wall stiffness. In general, with increased age, hypertension, diabetes, and atherosclerosis, the CA wall stiffness increases, and distensibility decreases. In addition the CA experiences longitudinal motion correlated to the pulsatile blood flow. Neck flexion and extension, and neck turning, can cause cross-

sectional, axial length, and bending deformations, which are critical to understand for longterm stent durability and device design. While the vertebrobasilar arteries do not deform much with cardiac pulsatility, the VA can experience diametric compression to the point of ischemia with ipsilateral neck turning. It has even been found that manual manipulation during chiropractic therapy and hair salon shampoo treatment can cause vertebrobasilar insufficiency due to VA compression. Finally, stenting can affect the natural morphology and deformation of the arteries in the head and neck.

References Arnold, C., Bourassa, R., Langer, T., et al., 2004. Doppler studies evaluating the effect of a physical therapy screening protocol on vertebral artery blood flow. Man. Ther. 9, 13 21. Arslan, I., Arslan, Y., Demirhan, E., Genc, S., Pekcevik, Y., Altin, L., et al., 2017. Medially displaced common and internal carotid arteries presenting as a pulsatile mass: clinicoradiologic analysis of 62 cases. Ear Nose Throat J. 96, E1 E7.

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Haldeman, S., Kohlbeck, F.J., McGregor, M., 1999. Risk factors and precipitating neck movements causing vertebrobasilar artery dissection after cervical trauma and spinal manipulation. Spine 24, 785 794. Haynes, M.J., 1996. Doppler studies comparing the effects of cervical rotation and lateral flexion on vertebral artery blood flow. J. Manipulative Physiol. Ther. 19, 378 384. Haynes, M., 2004. Letters to the editor. J. Manipulative Physiol. Ther. 27, 67 68. Haynes, M.J., Cala, L.A., Melsom, A., et al., 2002. Vertebral arteries and cervical rotation: modeling and magnetic resonance angiography studies. J. Manipulative Physiol. Ther. 25, 370 383. Henry, R.M.A., Kostense, P.J., Spijkerman, A.M.W., Dekker, J.M., Nijpels, G., Heine, R.J., et al., 2003. Arterial stiffness increases with deteriorating glucose tolerance status. Circulation 107, 2089 2095. Hillier, C.E., Gross, M.L., 1998. Sudden onset vomiting and vertigo following chiropractic neck manipulation. Postgrad Med. J. 74, 567 568. Hoaglin, D.C., Iglewicz, B., 1987. Fine-tuning some resistant rules for outlier labeling. J. Am. Stat. Assoc. 82, 1147 1149. Hoaglin, D.C., Iglewicz, B., Tukey, J.W., 1986. Performance of some resistant rules for outlier labeling. J. Am. Stat. Assoc. 81, 991 999. Hoiland, R., Ainslie, P., 2016. CrossTalk proposal: the middle cerebral artery diameter does change during alterations in arterial blood gases and blood pressure. J. Physiol. 594, 4073 4075. Jeret, J.S., Bluth, M.B., 2000. Stroke following chiropractic manipulation: report of 3 cases and review of the literature. J. Neuroimaging 10, 52. Jo´nsson Jr., H., Cesarini, K., Sahlstedt, B., et al., 1994. Findings and outcome in whiplash-type neck distortions. Spine 19, 2733 2743. Kawasaki, T., Sasayam, S., Yagi, S., Asakawa, T., Hirai, T., 1987. Non-invasive assessment of the age related changes in stiffness of major branches in the human arteries. Cardiovasc. Res. 21, 678 687. Klougart, N., Leboeuf-Yde, C., Rasmussen, L.R., 1996. Safety in chiropractic practice, part 1: the occurrence of cerebrovascular accidents after manipulation to the neck in Denmark from 1978 1988. J. Manipulative Physiol. Ther. 19, 371 377. Li, Y.K., Zhang, Y.K., Lu, C.M., et al., 1999. Changes and implications of blood flow velocity of the vertebral artery during rotation and extension of the head. J. Manipulative Physiol. Ther. 22, 91 95. Mitchell, J.A., 2003. Changes in vertebral artery blood flow following normal rotation of the cervical spine. J. Manipulative Physiol. Ther. 26, 347 351.

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C H A P T E R

8

Thoracic Aorta and Supra-Aortic Arch Branches B. Ullery1,2, G. Suh1 and Christopher P. Cheng1 1

Division of Vascular Surgery, Stanford University, Stanford, CA, United States 2 Providence Heart and Vascular Institute, Portland, OR, United States

The thoracic aorta and its branches are exposed to physiologic strain induced by cyclic changes in both cardiac and respiratory mechanics. A complex interplay between aging, genetics, environmental factors, and cardiovascular disease yields additional influence on the structural and functional demands of the vascular system over time (Lakatta and Levy, 2003; O’Rourke et al., 2002). While thoracic endovascular aortic repair (TEVAR) is the preferred treatment strategy for an expanding group of aortic pathologies, the influence of these variables on aortic strain and durability of thoracic aortic stent grafts remains poorly defined. Among a host of important biomechanical properties to consider, supra-aortic branch vessel geometry and aortic curvature of the proximal landing zone may be highly influential with regard to technical success and clinical outcome following TEVAR. Extremes of systemic arterial pressure and the associated pulsatile hemodynamic forces and motions

Handbook of Vascular Motion DOI: https://doi.org/10.1016/B978-0-12-815713-8.00008-5

owing to its proximity to the heart add further challenge to thoracic devices in the more proximal aorta. In this chapter, we will describe the anatomy and common pathologies of the thoracic aorta and its branches, including an indepth analysis of our current understanding of the native thoracic aortic dynamic motion and associated alterations in thoracic aortic anatomy following the implantation of aortic endografts.

ANATOMY OF THORACIC AORTA Thoracic Aorta The aorta originates from the left ventricle of the heart and serves as the largest blood vessel of the human body. The thoracic aorta is divided into three parts: ascending aorta, aortic arch, and descending aorta (Fig. 8.1). Located obliquely in a left paramedian plane at the level

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© 2019 Elsevier Inc. All rights reserved.

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of the third intercostal space, the ascending aorta begins at the sinotubular junction and includes both the aortic root and coronary artery ostia. Termination of the ascending aorta is marked by its exit from the pericardium and a transition to a backward bend in the superior

mediastinum. This bend, or arch, forms two curvatures: one with its convexity oriented upward and another with its convexity positioned forward and leftward. There is well-defined variation with regard to the aortic arch angulation, most commonly classified using the vertical distance from the origin of the brachiocephalic trunk to the superior aspect of the aortic arch in the parasagittal projection (Fig. 8.2). The aortic arch configuration has significant implications with regards to the technical success and thromboembolic potential during endovascular thoracic aortic interventions. Finally, the descending thoracic aorta begins at the lower border of the fourth thoracic vertebra following the takeoffs of the supra-aortic arch vessels and continues caudally within the posterior mediastinal cavity until it transitions to the abdominal aorta after entering the aortic hiatus in the diaphragm anterior to the lower border of the 12th thoracic vertebra.

Supra-Aortic Arch Branches FIGURE 8.1 Thoracic ascending, arch, and descending aorta, and adjacent branches.

The aortic arch gives rise to three supraaortic arch branch vessels, including the

FIGURE 8.2 Aortic arch types classified by the vertical distance from the origin of the brachiocephalic artery to the superior aspect of the arch in parasagittal projection in terms of the diameter of the left CCA. Types I (left), II (middle), and III (right) are categorized where the vertical distances are ,1, 1 2, and .2 diameters of the CCA. CCA, Common carotid artery. From Madhwal, S., Rajagopal, V., Bhatt, D.L., Bajzer, C.T., Whitlow, P., Kapadia, S.R., 2008. Predictors of difficult carotid stenting as determined by aortic arch angiography. J. Invasive Cardiol. 20 (5), 200 204, Figure 1.

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GEOMETRIC ANALYSIS METHODS

FIGURE 8.3 Aortic arch types classified by anatomic variation.

brachiocephalic artery (BA) (also referred to as the innominate artery), left common carotid artery (LCCA), and, lastly, the left subclavian artery (LSA) (Fig. 8.1). Multiple congenital variations exist with regard to supra-aortic arch branch vessel configuration. Approximately 75% of individuals have the previously described conventional three-vessel arch anatomy. Common variants include bovine arch anatomy, accounting for approximately 20% of individuals, marked by a common origin of the brachiocephalic and left common carotid arteries, as well as anomalous origins of the left vertebral and right subclavian arteries directly off the aorta (Fig. 8.3).

GEOMETRIC ANALYSIS METHODS Image-based modeling and geometric analysis aid in the understanding of the thoracic aorta and arch branch vessels. Changes in aortic arclength and curvature serve as important deformation metrics that characterize the complex and dynamic thoracic anatomy. This includes the heart pulling and releasing the ascending aorta with each cardiac cycle, rhythmic expansion and relaxation of the thorax by the diaphragm muscles with respiration, and the interaction of the thoracic aorta

with adjacent bone and soft tissues. In addition, supra-aortic branch vessel angle and its change due to in vivo motion are crucial pieces of information for the design and evaluation of thoracic endografts with branched components. Here, we summarize our methodology to acquire aortic arclength, curvature, and arch branch angles. The computed tomography angiography (CTA) data were utilized to construct 3D lumen models and centerline paths of the thoracic aorta and branch vessels. Following hand-picked lumen paths, cross-sections of vessels were segmented orthogonally from the aortic root to the distal descending aorta, as well as for the supra-aortic branches at least to their respective bifurcation points within the BA, LCCA, and LSA. Finally, true vessel centerline paths were defined by computing the mathematical centroids for each lumen contour, connecting the centroids, and smoothing the centroid-based path with optimized Fourier modes (Fig. 8.4) (Choi et al., 2009; Wilson et al., 2001). Refer to the chapter on geometric modeling for more details about the image processing and model construction. Axial arclengths and curvatures were quantified from the thoracic aorta utilizing the “true” centerlines formed from contour centroids and smoothing. Arclengths were

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FIGURE 8.4 Three-dimensional modeling technique of the native thoracic aorta, supra-aortic branch vessels, and thoracic aortic endograft. Along manually created lumen centerlines (A), perpendicular slices went through to follow the exterior aortic surface from the aortic root to the end of the imaged aorta (B) and, separately, follow the metallic boundary from end to end of the endograft (C). The resultant model surface is visualized for aorta (gray) and endograft (red) (D). While it is not shown here, the lumen contours were utilized to extract their centroids, connected and smoothed with optimized Fourier smoothing, and generated “true” centerline paths.

FIGURE 8.5 Quantification of thoracic aorta geometry including the arclength of ascending (yellow) and stented aorta (red) (A), curvature as an inverse of radius of circumscribed circle along the centerline (B), and branch angles for BA, LCCA, and LSA (C). Changes in these metrics characterize axial deformation, bending deformation, and branch angulation, respectively. BA, Brachiocephalic; LCCA, left common carotid; LSA, left subclavian arteries.

measured separately for the ascending aorta, aortic arch, and stented aorta where the endograft was placed. The curvature of the thoracic aorta was defined as the inverse of the radius of the circumscribed circle defined by

three centerline points spanning 20 mm (Fig. 8.5). The curvature was quantified at every 1 mm along the centerline. For comparison, curvature was averaged separately for the ascending aorta, aortic arch, and

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PATHOLOGIES OF THE THORACIC AORTA

stented aorta (mean curvature). Also, maximum curvature at each dynamic state (peak curvature) was measured for the three aortic sections. From one dynamic state to another, point-wise curvature was subtracted and the absolute greatest difference was measured (maximum change in curvature) (Ullery et al., 2018). In order to understand the arch branch deformation, branch angles were measured between the thoracic aorta centerline and branch vessel centerlines using vectors formed by 10 mm segments from the branching points (Fig. 8.5). An increase in branching angle from one physiologic state to another indicates that the branch vessel is angling away from the aortic arch (Suh et al., 2014).

PATHOLOGIES OF THE THORACIC AORTA Thoracic Aortic Aneurysm A thoracic aortic aneurysm is defined as a localized dilation of the thoracic aorta in excess of 50% of the diameter of the normal

FIGURE 8.6

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adjacent aortic segment (Fig. 8.6). Aneurysms of the thoracic aorta are most commonly degenerative in nature and occur in association with one or more atherosclerotic risk factors, including smoking, hypercholesterolemia, or hypertension (Isselbacher, 2005). Inflammatory (e.g., giant cell arteritis) and genetic connective tissue disorders (e.g., Marfan, Ehlers Danlos) may also lead to aneurysmal formation. Interestingly, the pathogenesis of aortic disease distal to the ligamentum arteriosum is predominately atherosclerotic in etiology, whereas more proximal aortic disease is most often attributed to nonatherosclerotic causes (Elefteriades and Farkas, 2010). Such pathophysiologic differences have been attributed to unique embryologic origins of aortic smooth muscle cells, which play a dominant role in aneurysm development via the secretion of multiple proteolytic factors. Specifically, smooth muscle cells with the ascending aorta and supra-aortic arch vessels arise from neural crest cells, while the descending thoracic aorta arises from paraxial mesoderm (Cheung et al., 2012). Similar to other large vessel aneurysms, the natural history of thoracic aortic aneurysms involves

Aneurysm (A) and dissection (B) in the thoracic aorta.

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slow expansion, ranging from 0.1 to 1 cm per year depending on the location and etiology of the aneurysm, leading to variable progressive risk of dissection, rupture, and sudden death (Dapunt et al., 1994; Davies et al., 2002; Elefteriades and Farkas, 2010). Indications for open or endovascular surgical treatment include maximum aneurysm diameter in excess of 5.5 cm in the ascending aorta or 6.5 cm in the descending thoracic aorta, rapid aneurysm growth ( . 0.5 mm/6 month), or at any size when the aneurysm is symptomatic or aortic rupture is present. Endovascular repair using thoracic aortic stent grafts has largely supplanted open surgical repair for cases isolated to the descending thoracic aorta. Open repair remains the gold standard for aneurysms of the ascending aorta and aortic arch given there are currently no FDA-approved devices to treat this proximal portion of the aorta; however, multiple clinical trials are underway to assess clinical

feasibility of branched and fenestrated technology in these anatomic locations.

Aortic Dissection Dissection of the aorta involves separation of the layers of the aortic wall as a result of intimal injury or tear (Fig. 8.6). Etiology of aortic dissection may be spontaneous, iatrogenic, or traumatic. Aortic dissections are commonly stratified according to two different anatomic classification systems, referred to as the DeBakey and Stanford classifications, based on the distribution of aorta involved in the dissection (Fig. 8.7). Risk factors for dissection include hypertension, atherosclerosis, prior cardiac or aortic surgery, bicuspid aortic valve, or connective tissue disorder (Hagan et al., 2000; Pape et al., 2015). Clinical presentation of aortic dissection commonly includes an acute onset of severe chest or back pain. Progression of the

FIGURE 8.7 DeBakey and Stanford classification systems for aortic dissection.

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THORACIC AORTIC DEFORMATIONS

dissection and/or involvement of branch vessels may result in end-organ malperfusion, resulting in shock, congestive heart failure, myocardial ischemia, stroke, paraplegia, renovisceral ischemia, or extremity ischemia. The pathognomonic finding of aortic dissection on imaging involves the presence of two distinct lumens, referred to as the “true” and “false” lumen. One or more intimal tears or flaps may also be present. Aortic dissections involving the ascending aorta are managed almost exclusively by emergency cardiac surgery. Acute management of type B aortic dissections involves pain control and antiimpulse therapy, which is aimed at reducing aortic wall shear stress by decreasing the velocity of left ventricular contraction. Indications for more aggressive intervention in cases involving type B aortic dissection include refractory pain, malperfusion, false lumen aneurysmal degeneration, or rupture. Elective repair using thoracic aortic stent grafts for select patients in the subacute (14 90 days from initial presentation) or chronic ( . 90 days from initial presentation) phase has gained considerable momentum in recent years following clinical trial data demonstrating improved midterm clinical outcomes and favorable aortic remodeling associated with endovascular repair in combination with medical therapy compared to medical therapy alone (Nienaber et al., 2013).

THORACIC AORTIC DEFORMATIONS Native Thoracic Aortic Deformations Cardiac pulsatility in the aorta is most obvious in the cross-sectional plane, with significant deformations observed from diastole to systole. Table 8.1 summarizes cardiacinduced motion measured from multiple locations on the thoracic aorta by previous studies. Morrison et al. (2009) quantified

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circumferential strains from diastole to systole in 14 nondiseased thoracic aortas using cardiac-resolved CTA, where the younger group of patients (mean age, 41 6 7 years) exhibited significantly larger cyclic strains compared to the older group (mean age, 68 6 6 years) along the thoracic aorta. This implies that aging has a significant stiffening effect on the thoracic aorta along its entire length, which is consistent with the known general degradation of aortic elastin and associated diametric expansion with age (Cheng et al., 2003; Morrison et al., 2009). Rengier et al. (2012) studied 61 healthy subjects and measured the maximum diameter change along the thoracic aorta. Similar to the findings from Morrison et al., the younger group exhibited greater aortic motion as compared to the older group (Rengier et al., 2012). Weber et al. (2009a) recorded an unbalanced distribution of magnitude and direction of cardiac-related displacement along the thoracic aorta in their quantitative analysis using dynamic CTA. Their investigation found a significant reduction of displacement from the ascending aorta to the aortic arch and descending thoracic aorta, as well as an anterior displacement for the ascending aorta and cranial displacement for the aortic arch (Weber et al., 2009a c). Additional studies using both echocardiography and finite element analysis have described myocardial contraction to elicit a shortening of the long cardiac axis that induces downward displacement of the aortic root during systole and a return to the initial position during diastole (Beller et al., 2008; Emilsson et al., 2006). de Beaufort et al. (2017a) studied thoracic aortic deformation due to cardiac pulsation in both longitudinal and radial directions from 10 patients with abdominal or thoracic aortic aneurysms using ECG-gated CT imaging (Table 8.2). The ascending aorta exhibited the greatest longitudinal extensibility and strain, and the descending aorta exhibited the smallest longitudinal extensibility and strain.

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TABLE 8.1 Cross-Sectional Deformation and Displacement of Thoracic Aorta due to Cardiac Pulsation Mid Asc to Prox BA

Dist LCCA to Prox LSA

Dist LSA to Prox Desc

Prox Desc to Mid Desc

Dist Desc

Circumferential strain (%)

11.3 6 6.9

8.9 6 3.5

7.9 6 2.4

7.3 6 2.6

8.1 6 3.3

Morrison et al. (2009) (68 6 6 years)

Circumferential strain (%)

3.4 6 1.5

2.7 6 1.4

2.0 6 2.0

2.7 6 1.3

4.2 6 1.9

Rengier et al. (2012) (,50 years)

Major diametric strain (%)

10.9 6 4.6

11.0 6 3.3

11.6 6 3.9

11.0 6 3.4

11.6 6 5.0

Rengier et al. (2012) ($50 years)

Major diametric strain (%)

5.4 6 2.0

7.1 6 3.1

7.3 6 2.9

5.3 6 2.7

8.5 6 4.4

Rengier et al. (2012) (,50 years)

Center of mass displacement (mm)

6.7 6 1.8

3.4 6 0.9

2.3 6 0.8

1.3 6 0.4

1.8 6 0.5

Rengier et al. (2012) ($50 years)

Center of mass displacement (mm)

6.3 6 1.3

2.5 6 0.8

1.8 6 0.6

1.5 6 0.7

1.6 6 0.6

Weber et al. (2009b) (62 6 12 years)

Area change (%)

12.9 6 3.7

11.4 6 1.8

NA

16.5 6 5.9 (true), 10.5 6 5.7 (false)a

NA

Weber et al. (2009b) (62 6 12 years)

Major diametric strain (%)

7.7 6 1.9

6.2 6 1.3

NA

5.9 6 2.0 (true), 6.1 6 3.6 (false)a

NA

Weber et al. (2009a) (63 6 12 years)

Net displacement (mm)

5.2 6 1.7

1.6 6 1.0b

0.9 6 0.4 (true), 1.1 6 0.4 (false)a

NA

Study (Age Group)

Parameter

Morrison et al. (2009) (41 6 7 years)

a b

Weber et al. (2009a) and (2009b) reported separate measurement for true lumen and false lumen of dissected thoracic aorta. Weber et al. (2009a) reported the net displacement at the highest point of the aortic arch (vertex of arch) which was proximal or distal to LSA branch.

Data are shown as mean 6 standard deviation. BA, Brachiocephalic artery; LCCA, left common carotid artery; LSA, left subclavian artery; Prox, proximal; Dist, distal; Asc, ascending aorta; Desc, descending aorta. Deformation and displacement were measured somewhere within the five regions of the thoracic aorta. From Morrison, T.M., Choi, G., Zarins, C.K., Taylor, C.A., 2009. Circumferential and longitudinal cyclic strain of the human thoracic aorta: age-related changes. J. Vasc. Surg. 49 (4), 1029 1036; Rengier, F., Weber, T.F., Henninger, V., Bo¨ckler, D., Schumacher, H., Kauczor, H.-U., et al., 2012. Heartbeat-related distension and displacement of the thoracic aorta in healthy volunteers. Eur. J. Radiol. 81, 158 164; Weber, T.F., Ganten, M.K., Bockler, D., Geisbusch, P., Kauzor, H.U., von Tengg-Kobligk, H., 2009a. Heartbeat-related displacement of the thoracic aorta in patients with chronic aortic dissection type B: quantification by dynamic CTA. Eur. J. Radiol. 72 (3), 483 488; Weber, T.F., Tetzlaff, R., Rengier, F., Geisbu¨sch, P., KoppSchneider, A., Bo¨ckler, D., et al., 2009b. Respiratory displacement of the thoracic aorta: physiological phenomenon with potential implications for thoracic endovascular repair. Cardiovasc. Interv. Radiol. 32 (4), 658 665.

Cross-sectional distensibility and circumferential strain were greatest at the sinotubular junction. We used cardiac- and respiratory-resolved CTA images to quantify 3D motion of the thoracic aorta in patients with thoracic aortic aneurysms and/or dissections (Suh et al., 2014). The images were acquired by performing cardiac-resolved electrocardiogram-gated CTA during both inspiratory and expiratory breath holds. Retrospective cardiac-gated CTA was performed during inspiratory breath hold,

followed by an additional retrospective cardiac-gated sequence during expiratory breath hold. For the inspiratory acquisition, contrast medium injection was utilized consistently with routine clinical CTA. After the first sequence (inspiratory) was completed, the patient was instructed to breathe normally for a few breathing cycles in order to catch his breath and then for the second acquisition (expiratory) perform a breath hold at the end of expiration. This second acquisition acquired

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TABLE 8.2 Longitudinal and Cross-Sectional Pulsatile Geometry Change of Thoracic Aorta From Patients With Untreated Aortic Aneurysms (n 5 10) Longitudinal Measurement

Entire Thoracic Aorta

Ascending Aorta

Aortic Arch

Descending Aorta

Length change (mm)

9.4 (3.7 16.0)

7.0 (4.5 10.9)

2.3 (1.0 5.0)

5.3 (1.7 11.2)

N )

3.5 (1.3 6.8)

20.6 (5.7 36.2)

6.5 (2.5 22.9)

4.4 (1.6 12.3)

Longitudinal strain (%)

2.7 (1.0 4.5)

15.9 (6.6 31.9)

4.7 (2.0 11.2)

2.2 (0.7 4.7)

23

Extensibility (10

21

Cross-Sectional Measurement Sinotubular Junction Brachiocephalic Trunk Left Subclavian Artery Celiac Trunk Diameter change (mm)

2.7 (0.5 6.7)

1.7 (0.3 3.8)

1.3 (0.3 4.3)

1.8 (0.3 4.8)

Area change (mm2)

95.4 (30.9 201.9)

64.5 (23.4 177.3)

35.4 (10.8 81.0)

38.6 (11.4 72.5)

Distensibility (1023 mmHg21)

1.7 (0.5 2.9)

1.2 (0.3 3.3)

0.9 (0.3 2.5)

1.2 (0.4 3.3)

7.5 (2.2 18.4)

5.9 (2.2 14.0)

7.7 (2.5 18.3)

Circumferential area strain (%) 11.3 (3.3 18.5)

Data are shown as mean (minimum 2 maximum). Each measurement included (maximum 2 minimum) which is why all values are positive. From de Beaufort, H.W.L., Nauta, F.J.H., Conti, M., Cellitti, E., Trentin, C., Faggiano, E., et al., 2017a. Extensibility and distensibility of the thoracic aorta in patients with aneurysm. Eur. J. Vasc. Endovasc. Surg. 53 (2), 199 205.

image data using only residual contrast recirculating inside the patient, without additional administration of contrast, and utilized dose modulation to decrease radiation to the patient. Refer to the chapter on medical imaging for more details on imaging protocol and acquisition parameters. From the visual comparison, it is notable that greater translation seemed to occur through the entire thoracic aorta due to respiration as compared to cardiac contraction (Fig. 8.8) (Suh et al., 2014). According to the measurement of 3D translation of each branch ostia at the aortic arch, from systole to diastole, the aortic arch branches moved rightward and posteriorly (P , .05, at expiration only). From inspiration to expiration, the aortic arch branches moved posteriorly and superiorly (P , .05) (Table 8.3). Despite notable translational motion of the thoracic aorta, there was no significant change in the axial length or curvature along the centerline of thoracic aorta with cardiac pulsation or respiration.

Sailer et al. (2015) performed quantitative analysis with 60 subjects to document respiratory motion of the aorta and side branches in 3D. Respiratory movement was greatest along the ascending aorta and arch branch ostia compared to the aortic arch and descending thoracic aorta. Weber et al. (2009b) reported significant translation of the thoracic aorta when respiratory thorax excursion exceeded the certain threshold. They concluded that, while this threshold may not be exceeded during tidal respiration in most individuals, segmental differentials observed during periods of forced vital capacity may generate additive extrinsic forces on the aorta wall. Acknowledgment of cardiopulmonaryinduced aortic changes is of great importance to the surgeon performing TEVAR near the ascending aorta or aortic arch, particularly due to the fact that this motion is not always well characterized on predeployment angiography performed during inspiratory breath hold. For this reason, thoracic stent grafts should be

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FIGURE 8.8 Visual comparison of thoracic aorta and arch branch vessels between diastole versus systole (A and B), inspiration versus expiration (C and D), and all together (E). From Suh, G., Beygui, R.E., Fleischmann, D., Cheng, C.P., 2014. Aortic arch vessel geometries and deformations in patients with thoracic aortic aneurysms and dissections. J. Vasc. Surg. 25 (12), 1903 1911, Figure 4.

deployed in the same ventilatory arrest status used during initial angiography. Moreover, placement of thoracic aortic stents in the more proximal aorta (ascending aorta and aortic arch),

the conduct of which is presently limited to clinical trial devices, is greatly facilitated by rapid ventricular pacing so as to minimize the influence of motion related to cardiac pulsatility.

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TABLE 8.3 Cardiac- and Respiratory-Induced 3D Aortic Arch Translation (mm) at the Brachiocephalic Artery (BA), Left Common Carotid Artery (LCCA), and Left Subclavian Artery (LSA) Branch Points Translating Physiologic Mode

Fixed Physiologic Mode

BA

LCCA

LSA

LEFT-TO-RIGHT TRANSLATION (MM) Systole-diastole

Inspiration-expiration

Inspiration

0.3 6 1.8

2 0.2 6 1.8

0.2 6 1.3

Expiration

0.7 6 1.2

0.8 6 1.0

1.0 6 0.9a

Diastole

1.3 6 2.7

0.6 6 2.9

0.2 6 2.6

Systole

0.9 6 2.8

2 0.4 6 2.8

2 0.5 6 2.2

a

a

POSTERIOR-TO-ANTERIOR TRANSLATION (MM) Systole-diastole

Inspiration-expiration

Inspiration

2 0.4 6 1.5

Expiration

2 0.0 6 1.4

2 0.1 6 1.6

2 1.1 6 1.4

a

2 0.6 6 1.7

2 3.3 6 4.0

a

2 2.8 6 3.7a

2 3.4 6 4.3a

2 2.3 6 3.9a

2 2.2 6 3.7a

Inspiration

0.7 6 1.7

0.3 6 1.7

0.8 6 1.3a

Expiration

0.6 6 2.3

1.0 6 2.5

0.2 6 2.3

Diastole

2.6 6 3.9

a

3.2 6 3.6

3.4 6 3.7a

Systole

2.8 6 3.8a

2.5 6 3.3a

4.0 6 3.4a

Inspiration

2.4 6 1.7

2.2 6 1.7

2.0 6 1.5

Expiration

2.5 6 1.7

2.9 6 1.8

2.8 6 1.5

Diastole

6.7 6 4.4

6.3 6 4.2

6.1 6 3.9

Systole

6.6 6 3.9

5.6 6 3.5

6.4 6 3.1

2 0.8 6 1.2

a

Diastole

2 3.9 6 4.6

a

Systole INFERIOR-TO-SUPERIOR TRANSLATION (MM) Systole-diastole

Inspiration-expiration

a

3D TRANSLATION (MM) Systole-diastole

Inspiration-expiration

a

Indicates statistically significant translation from one physiologic mode to another. Data are shown as mean 6 standard deviation. Positive value for translation in each of 3D directions indicates rightward, anterior, and superior translations. The significance threshold (P , .05) was adjusted by Bonferroni Holm correction for multiple comparisons. From Suh, G.Y., Beygui, R.E., Fleischmann, D., Cheng, C.P., 2014. Aortic arch vessel geometries and deformations in patients with thoracic aortic aneurysms and dissections. J. Vasc. Interven. Radiol. 25 (12), 1903 1911.

Morphologic Alterations Due to Thoracic Aortic Endograft Placement The longitudinal stiffness of a thoracic aortic endograft changes the morphology of the native anatomy. Midulla et al. (2014) reported that pre-to-post-TEVAR geometry differences were found in 23 of 30 patients (76%). The geometry differences were noted at the upper implantation zone (14 patients) mostly at the

aortic arch (11 patients). Mestres et al. (2017) analyzed curve angle of the thoracic aorta from 36 TEVAR patients and reported that the proximal descending thoracic aorta straightened with a 4.0 4.9 degree increase of curve angle after placement of an endograft into the aortic arch and proximal thoracic aorta. According to the analysis of our TEVAR cohort (n 5 18), from pre-to-post-TEVAR, the stented lumen exhibited a significant decrease

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TABLE 8.4 Geometry of the Thoracic Aorta Before and After Thoracic Endovascular Aortic Repair (TEVAR) (n 5 18) Aortic Location

Pre-TEVAR

Post-TEVAR

Post Pre

Ascending aorta

0.214 6 0.031a

0.218 6 0.030a,b

0.003 6 0.014a

Aortic arch

0.184 6 0.048

0.178 6 0.051b

2 0.006 6 0.024

Stented lumen

0.177 6 0.038

0.164 6 0.034

2 0.012 6 0.017a,c

Ascending aorta

0.335 6 0.051a,b

0.344 6 0.048b

0.009 6 0.035b

Aortic arch

0.257 6 0.076b,d

0.252 6 0.071b,d

2 0.005 6 0.033b,d

Stented lumen

0.442 6 0.199a,d

0.353 6 0.109d

2 0.090 6 0.183d

Aortic location

|Post pre|

21

MEAN CURVATURE (CM )

a

a

PEAK CURVATURE (CM21)

MAXIMUM CURVATURE CHANGE (CM21) Ascending aorta

0.081 6 0.044a,b

Aortic arch

0.050 6 0.031b,d

Stented lumen

0.213 6 0.185a,d

a

Indicates significant difference between ascending aorta and stented lumen. Indicates significant difference between ascending aorta and aortic arch. c Indicates significant difference between pre- and post-TEVAR. d Indicates significant difference between aortic arch and stented lumen. Data are shown as mean 6 standard deviation. Mean curvature, Average curvature over the aortic range. Peak curvature—maximum curvature within the aortic range; Maximum curvature change—maximum absolute difference of curvature between pre- and post-TEVAR. Significance threshold was set as P , .05. From Ullery, B.W., Suh, G., Hirotsu, K., Zhu, D., Lee, J.T., Dake, M.D., et al., 2018. Geometric deformations of the thoracic aorta and supra-aortic arch branch vessels following thoracic endovascular aortic repair. Vasc. Endovasc. Surg. 52 (3), 173 180. b

in mean curvature (P , .05) (Table 8.4) (Ullery et al., 2018). While other pre-to-post-TEVAR curvature change was not significant from this group of patients, the comparison between aortic locations revealed that the stented lumen exhibited greater curvature reduction than any other aortic location. This makes sense considering the added bending stiffness of thoracic aortic endograft.

Deformation Alterations Due to Thoracic Aortic Endograft Placement If an endograft in fact increases stiffness in the thoracic aorta, it should induce changes in the aortic deformation. de Beaufort et al. (2017b) performed experiments with 20 porcine

specimens and measured pulse wave velocity (an indication of aortic stiffness) at multiple locations on each specimen before and after the deployment of multiple types of endografts. The pulse wave velocity increased by 8.9% after deployment of a 100-mm endograft, and 23.0% when the endograft was extended distally, indicating a significant correlation between the aortic stiffness and the amount of graft coverage. This finding is corroborated by van Prehn et al. (2009), which used cardiac-resolved CTA from patients with thoracic aortic aneurysm to measure mean aortic diameter and lumen cross-sectional area before and after TEVAR. From pre- to post-TEVAR, neither the mean diameter nor lumen cross-sectional area changed

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TABLE 8.5 End-Systolic Aortic Length and Longitudinal Strain for Series of Four Patients With Type B Aortic Dissection Patient

Status

Total Thoracic Aorta

Ascending Aorta

Aortic Arch

Descending Aorta

END-SYSTOLIC LENGTH (MM) Pre-TEVAR

363.7 6 1.8

80.7 6 1.6

38.2 6 1.0

246.3 6 1.5

Post-TEVAR

361.1 6 2.2

83.4 6 1.4

42.6 6 1.8

238.6 6 1.8

Pre-TEVAR

391.2 6 3.1

74.0 6 2.5

42.3 6 1.4

281.0 6 4.2

Post-TEVAR

398.7 6 5.4

80.6 6 3.8

43.9 6 1.4

275.1 6 1.8

3

Control

373.3 6 5.1

73.0 6 3.5

55.1 6 0.9

246.3 6 1.4

4

Control

336.3 6 2.3

52.0 6 2.2

50.1 6 0.8

235.2 6 1.3

Pre-TEVAR

1.4

5.0

8.6

1.5

Post-TEVAR

1.7

5.3

14.2

2.4

Pre-TEVAR

2.4

9.9

9.6

4.9

Post-TEVAR

4.4

16.8

9.5

1.7

3

Control

4.5

14.0

3.9

1.7

4

Control

2.1

12.9

4.2

1.7

1

2

LONGITUDINAL STRAIN (%) 1

2

Data are shown as mean 6 standard deviation for end-systolic length only. TEVAR, Thoracic endovascular aortic repair. From Nauta, F., van Bogerijen, G., Conti, M., Trentin, C., Moll, F.L., Van Herwaarden, J.A., et al., 2017. Impact of thoracic endovascular repair on pulsatile aortic strain in acute type B aortic dissection. Aorta 5 (2), 42 52.

significantly; however, there was a trend toward decreased distension at the site of the endograft post-TEVAR. This makes sense as the endograft should add radial stiffness to the aorta. Another interesting aspect of these data was that it showed that cross-sectional distension seemed to be asymmetric since the cross-sectional area changes were lower than the predicted range derived by the mean aortic diameter changes. Thoracic aortic endografts can also effect nonradial deformations. Nauta et al. (2017) noted TEVAR to be associated with a significant increase in pulsatile longitudinal strain proximal to the thoracic stent grafts in two patients with type B aortic dissection. In addition, aortic dissection patients demonstrated lower pulsatile longitudinal strain of the total thoracic aorta before TEVAR compared to control subjects (Table 8.5). This study and others

(Dong et al., 2010; Huang et al., 2013; Raaz et al., 2015) have suggested that elevated pulsatile wall stress may be linked to aortic wall fatigue, thereby resulting in aneurysmal degeneration and increased risk of new entry tears at the proximal or distal end of the stent graft and/or compromise of the aortic wall leading to transmural rupture. In a larger study, eight patients underwent cardiac-resolved CTA both before and after TEVAR, and alterations to axial length and centerline curvature deformations due to TEVAR were quantified (Table 8.6) (Hirotsu et al., 2018). As stated previously, we observed lower mean and peak curvatures in the stented location post-TEVAR as compared to pre-TEVAR, both at diastole and systole. From a dynamic deformation perspective, the maximum curvature change from diastole to systole was greatest within the stented location during the

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TABLE 8.6 Diastole to Systole Changes of Geometry of the Ascending Aorta, Aortic Arch, and Stented Aorta for Pre- and Post-Thoracic Endovascular Aortic Repair (TEVAR) States (n 5 8) Geometric Change (Diastole-Systole)

Ascending Aorta

Aortic Arch

Stented Aorta

1.5 6 2.9a

1.1 6 4.6

21

Mean curvature (cm )

0.21 6 0.03-0.21 6 0.03

0.21 6 0.05 -0.20 6 0.06

0.21 6 0.03a-0.21 6 0.04a

Peak curvature (cm21)

0.36 6 0.03-0.36 6 0.04

0.31 6 0.11-0.31 6 0.12

0.63 6 0.24a-0.61 6 0.24a

Max curvature change (cm21)

0.06 6 0.05b,c

0.05 6 0.04b,d

0.28 6 0.26a,b,c,d

Axial length change (%)

2.7 6 3.1a,b,c

2 0.4 6 7.5

2 0.3 6 0.8c

Mean curvature (cm21)

0.21 6 0.03-0.20 6 0.03b

0.19 6 0.05a-0.19 6 0.04a

0.18 6 0.02a-0.18 6 0.02a

Peak curvature (cm21)

0.38 6 0.05-0.36 6 0.05b

0.30 6 0.11-0.28 6 0.10

0.40 6 0.12a-0.37 6 0.07a

Max curvature change (cm21)

0.06 6 0.05b

0.04 6 0.03b

0.06 6 0.06a,b

PRE-TEVAR Axial length change (%)

0.1 6 3.2 a

a

POST-TEVAR

Indicates significant difference between pre- and post-TEVAR (P , .05). Indicates significant change from diastole to systole (P , .05). c Indicates significant difference between ascending and stented aorta (P , .05). d Indicates significant difference between aortic arch and stented aorta (P , .05). Data are shown as mean 6 standard deviation. Mean and peak curvatures are reported by Diastolic measurement-systolic measurement, for pre- versus post-TEVAR comparison of each curvature measurement. From Hirotsu, K., Suh, G., Lee, J.T., Dake, M.D., Fleischmann, D., Cheng, C.P., 2018. Changes in geometry and cardiac deformation of the thoracic aorta after thoracic endovascular aortic repair. Ann. Vasc. Surg. 46, 83 89. a

b

pre-TEVAR state, which significantly decreased to a level similar to other regions during the post-TEVAR state. Similar to the finding described by Nauta et al. (2017), the ascending aorta exhibited an increase of axial length change from 1.5 6 2.9% to 2.7 6 3.1% due to TEVAR. This is possibly due to damping of longitudinal deformation of the downstream descending aorta due to the stiffness of the thoracic aortic endograft, and resultant augmentation of deformation of the ascending aorta to compensate for the reduced motion downstream. A related explanation is an increase in pressure wave reflection in the ascending aorta due to the abrupt stiffness increase at the site of endograft implantation. Based on a study with 15 post-TEVAR patients, cardiac and respiratory-induced motion of the thoracic aorta appears to be affected by the presence of a thoracic endograft

(Suh et al., 2018). Fig. 8.9 shows two examples of the thoracic aorta post-TEVAR deforming during the cardiac cycle and respiration, which demonstrates different motion compared to Fig. 8.8 with an unrepaired thoracic aorta. One notable finding was that the ascending aorta exhibited longitudinal elongation from diastole to systole, which was significantly greater than that due to respiration (P , .05) (Table 8.7). We postulated that such dramatic elongation of the ascending aorta was induced by caudal pulling of the aortic root with systolic contraction of the heart. This can explain the significant decrease of mean curvature of ascending aorta from diastole to systole, as the pulling straightened the ascending aorta. We noted a similar range of curvature reduction in the ascending aorta from expiration to inspiration (P , .05), which may be due to the relaxation of the ascending aorta during

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THORACIC AORTIC DEFORMATIONS

153 FIGURE 8.9 Two examples of thoracic aortic motions with endograft [(A) thoracic aorta with repaired descending aortic dissection; (B) thoracic aorta with repaired descending aortic aneurysm]. Note that geometry deformations persist mostly at the ascending aorta and aortic arch while the stented descending aorta is static during cardiac pulsation and respiration. From Suh, G., Ullery, B.W., Lee, J.T., Dake, M.D., Fleischmann, D., Cheng, C.P., 2018. Cardiopulmonary-induced deformations of the thoracic aorta following thoracic endovascular aortic repair. Vascular. Available from: https://doi.org/ 10.1177/1708538118811204, Figure 2.

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TABLE 8.7 Deformation of Thoracic Aorta From Thoracic Endovascular Aortic Repair (TEVAR) Cohort (n 5 15, Post-TEVAR) Aortic Location

Diastole-Systole (Inspiration)

Diastole-Systole (Expiration)

Expiration-Inspiration (Diastole)

Expiration-Inspiration (Systole)

4.8 6 4.4a,b,c

0.9 6 3.0a

2 1.4 6 3.6a

ARCLENGTH CHANGE (%) Ascending aorta

2.3 6 4.3a

Aortic aorta

1.1 6 6.4

Stented aorta 0.2 6 0.6

2 1.3 6 6.4

2 0.2 6 5.9

2.0 6 6.8

0.1 6 0.8c

0.3 6 0.9

0.4 6 1.0

MEAN CURVATURE CHANGE (CM21) Ascending aorta

2 0.010 6 0.012b,c

2 0.008 6 0.011b,c

2 0.010 6 0.012b,c

2 0.012 6 0.012b,c

Aortic arch

0.001 6 0.026

2 0.008 6 0.021

2 0.013 6 0.026

2 0.004 6 0.018

Stented aorta

2 0.002 6 0.004c

2 0.000 6 0.003c

2 0.000 6 0.003c

2 0.001 6 0.005c

21

MAXIMUM CURVATURE CHANGE (CM ) Ascending aorta

0.069 6 0.040b,c

0.073 6 0.058b,c

0.070 6 0.049b

0.066 6 0.038b,c

Aortic aorta

0.059 6 0.034b,d

0.062 6 0.039b,d

0.051 6 0.023b

0.053 6 0.037b

0.033 6 0.016

0.042 6 0.019

0.041 6 0.015b,c

Stented aorta 0.039 6 0.018

b,c,d

a,b,c,d

a,b

a

Indicates significant difference between cardiac and respiratory deformation. Indicates significant change from one state to another. c Indicates significant difference between ascending and stented aorta. d Indicates significant difference between aortic arch and stented arch. b

Data are shown as mean 6 standard deviation. Mean curvature, Average curvature over the aortic range. Significance threshold was set as P , .05. From Suh, G.Y., Ullery, B.W., Lee, J.T., Dake, M.D., Fleischmann, D., Cheng, C.P., 2018. Cardiopulmonary-induced deformations of the thoracic aorta following thoracic endovascular aortic repair. Vascular. Available from: https://doi.org/10.1177/1708538118811204.

diaphragmatic movement from superior (compressing the aorta upward) to inferior direction (releasing the aorta from the compression) from expiration to inspiration. Comparing aortic regions, we observed significantly lower curvature changes at the stented aorta for both cardiac- and respiratory-induced motion. This makes sense because the thoracic aortic endograft adds bending stiffness to the native thoracic aorta.

Long-Term Aortic Remodeling Changes in vascular structure and function accompany increasing age and may be further

modified in the presence of concomitant cardiovascular disease states. It is well documented that mural thickening and dilation of large elastic arteries such as the aorta and supraaortic branch vessels occur during the aging process (Crouse et al., 1994; Sugawara et al., 2008; Virmani et al. 1991). To further investigate the generalized belief that these large vessels elongate and become relatively tortuous with aging, Sugawara et al. (2008) calculated arterial lengths using 3D transverse magnetic resonance imaging arterial tracings of the aorta, carotid, and iliac arteries in 256 healthy adults aged 19 79 years. Their results indicated that the length of the ascending aorta

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FIGURE 8.10

Changes in aortic and arterial lengths with age. From Sugawara, J., Hayashi, K., Yokoi, T., Tanaka, H., 2008. Age-associated elongation of ascending aorta in adults. J. Am. Coll. Cardiol. Cardiovasc. Imaging 1 (6), 739 748, Figure 2.

increased significantly with advanced age, whereas such age-related lengthening was not observed in the distribution of the descending thoracic aorta (Fig. 8.10). Of note, these findings were present across the studied population independent of cardiovascular disease status. Due to the corresponding increase in central arterial stiffness and pulse wave amplification noted in the ascending aorta, the authors posited that the decrease in elasticity and increase in local pulsatile pressure may contribute to this remodeling behavior over time. Others have suggested that the ascending aorta is the most likely aortic segment to negatively remodel as a result of “material fatigue” owing to its proximal location and greater absorption of chronic left ventricular ejection relative to the more distal aorta (Nichols and O’Rourke, 2005). Interestingly, the magnitude of age-related change in ascending aortic lengthening observed in the study by Sugawara et al. (2008) was 12% per

decade, a figure that is far greater than that noted for ascending aortic cross-sectional expansion in prior studies (approximately 3% per decade) (Gerstenblith et al., 1977; Vasan et al., 1995). Redheuil et al. (2011) studied 100 healthy subjects using magnetic resonance imaging to determine aortic arch geometry and function. Their findings indicated that aortic diameters and arch length increased significantly with age. Similar to the results of Sugawara et al. (2008), the ascending aortic length was noted to have the greatest increase over time, with increased age also leading to aortic arch widening and decreased curvature (Table 8.8). Increased ascending aortic diameter, lengthening, and decreased aortic arch curvature were all notably associated with increased left ventricular mass and concentric remodeling independent of age, body size, gender, and systemic arterial blood pressure (Redheuil et al., 2011; Sugawara et al., 2008).

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TABLE 8.8 Relative Change in Measures of Aortic Geometry With Age: Comparison of Young (age ,30 Years) and Older Subjects (age .70 Years) Parameter

Age ,30 Years

Age .70 Years

Average Annual Change

Relative Change (%)

Ascending aorta diameter (mm)

27.5 6 2.8

33.2 6 4.3

1 0.11

1 21

Aortic arch length (mm)

100.4 6 7.1

130.9 6 13.9

1 0.60

1 30

Aortic arch width (mm)

58.6 6 4.7

78.5 6 8.7

1 0.40

1 34

Aortic arch height (mm)

34.3 6 2.9

41.5 6 4.5

1 0.14

1 21

Aortic arch curvature (mm21)

0.034 6 0.002

0.027 6 0.003

2 0.14 3 1023

2 21

Proximal descending aorta diameter (mm)

20.5 6 1.6

24.3 6 2.7

1 0.08

1 19

Distal descending aorta diameter (mm)

18.3 6 1.4

21.5 6 3.2

1 0.06

1 17

Descending aorta length (mm)

139.3 6 15.8

142.6 6 13.3

1 0.07

12

From Redheuil, A., Yu, W., Mousseaux, E., Harouni, A.A., Kachenoura, N., Wu, C.O., et al., 2011. Age-related changes in aortic arch geometry. J. Am. Coll. Cardiol. 58 (12), 1262 1270.

A growing body of literature has also noted long-term changes in aortic length after TEVAR. Naguib et al. (2016) retrospectively evaluated centerline measurements of the aorta in 53 consecutive patients treated with TEVAR for a heterogenous group of aortic pathologies. The authors noted a significant change in aortic length observed at 12 months after TEVAR, including as much as a 9.3% increase in aortic length in patients treated for thoracic aortic aneurysm and up to 10.5% in patients treated for aortic dissection at 2-year follow-up. The basis for the greater increase in mean overall aortic length noted in the dissection group compared to the aneurysm group at 2 years is unclear; however, the investigators suggest that the intact intima in the aneurysm group may play a role in ameliorating the magnitude of aortic elongation over time.

PATHOLOGIES OF THE AORTIC ARCH AND SUPRA-AORTIC ARCH BRANCHES Thoracic Outlet Syndrome Thoracic outlet syndrome refers to a constellation of signs and symptoms that result from

FIGURE 8.11 Anatomy of the thoracic outlet.

the compression of the neurovascular structures within the thoracic outlet region of the upper extremity. The thoracic outlet comprises three separate anatomic locations prone to neurovascular compression, including the scalene triangle, costoclavicular space, and pectoralis minor (Fig. 8.11). Trunks of the brachial plexus or portions of the subclavian artery may be compressed within the scalene triangle, defined as the space between the first rib and the borders of the anterior and middle scalene muscles, especially in the presence of cervical or anomalous first ribs. The bony abnormalities commonly found in these patients, including the presence of cervical ribs

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PATHOLOGIES OF THE AORTIC ARCH AND SUPRA-AORTIC ARCH BRANCHES

in up to 85% of the patients with arterial thoracic outlet syndrome (Aljabri and Al-Omran, 2013; Orlando et al., 2015), can cause compression and progressive injury of the proximal subclavian artery resulting in intimal damage, thrombosis, aneurysmal degeneration, or distal thromboembolization. Chronic compression of the brachial plexus can lead to perineural inflammation and subsequent upper extremity and neck pain, muscle wasting, and disabling peripheral motor and sensory deficits. Any of the aforementioned sequelae of the subclavian arterial compression mandates intervention, most commonly in the form of first rib resection alone or in combination with adjunctive procedures such as brachial plexus neurolysis, scalenectomy, removal of cervical or supernumerary ribs, pectoralis minor tendon release, or subclavian artery reconstruction. Diagnostic criteria and indications for intervention for neurogenic thoracic outlet syndrome remain controversial, particularly given that many patients experience improvement with dedicated physical therapy alone. Less commonly, the proximal subclavian vein may be compressed within the costoclavicular space, defined by first rib inferiorly, anterior scalene posterolaterally, clavicle superiorly, and costoclavicular ligament anteromedially (Fig. 8.11). Repetitive arm movements are believed to be central in the pathogenesis of venous thoracic outlet syndrome as they cause chronic traumatic injury to the thin-walled vein by compression within the costoclavicular space. The affected portion of the vein is subjected to posttraumatic inflammation, intimal fibrosis and scarring, stenosis, and the potential for both acute and chronic disabling upper extremity deep venous thrombosis. Intervention is indicated in such cases and is initiated acutely with catheter-directed thrombolysis and anticoagulation to aid in early symptomatic relief via evacuation of thrombus load and optimization of collateral venous drainage. Once patency of the subclavian vein is restored,

157

addressing the underlying anatomic constraint is pursued through first rib resection, often in combination with resection of the anterior scalene muscle and subclavius tendon.

Supra-Aortic Branch Vessel Aneurysm Supra-aortic branch vessel aneurysms constitute between 0.4% and 4% of all aneurysms (Bower et al., 1991; Brewster et al., 1985; Regina et al., 2000). The majority of publications on such aneurysms are limited to case reports or small case series, the combined experience of which amounts to fewer than 200 cases reported in the last century in the English medical literature (Cury et al., 2009). While such aneurysms may share a similar pathophysiology with traditional degenerative aortic aneurysms, other etiologies are often cited in these cases, including traumatic pseudoaneurysms, congenital anomalies, connective tissue disorders, vasculitis, and infection. Supra-aortic branch vessel aneurysms similarly share with aortic aneurysms their risks of rupture, local compressive phenomenon, and thromboembolization but also have a notably elevated risk of neurologic morbidity secondary to potential catastrophic cerebral embolization. As such, a supra-aortic aneurysm of any size should be regarded as clinically significant and treatment should be considered. Surgical resection of the aneurysm with interposition bypass has been the mainstay therapy since the first report of surgical intervention for such a case in 1805 (Ellis, 1985). However, the growing advancement of endovascular technology has surfaced alternative therapeutic options for supra-aortic aneurysms in recent years (Fernandez-Alonso et al., 2018; Tsilimparis et al., 2016).

Aortic Arch Dissection Any dissection flap or intramural hematoma that affects the transverse arch but does

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not involve the aorta proximal to the innominate artery is termed an aortic arch dissection. In such cases, the primary entry tear may occur within the aortic arch or distal to the LSA with associated retrograde dissection into the arch. Data from the International Registry of Acute Aortic Dissection noted that 25.5% of the Stanford type B aortic dissections involved the aortic arch (Tsai et al., 2007). Notably, extension into one or more of the supra-aortic branch vessels may also be present. In addition, isolated innominate artery dissection (Kanady et al., 1990; Nagata et al., 2017; Munakata et al., 2008) and retrograde extension of common carotid artery dissection into the aortic arch have also been reported (Yoshioka et al., 2011). As with other cases of aortic dissection not involving the ascending aorta, such cases are usually managed with medical treatment only, even in the presence of supra-aortic arch vessel involvement. Open surgical or endovascular intervention is reserved for refractory

pain, false lumen aneurysmal degeneration, retrograde type A dissection, or evidence of end-organ malperfusion.

SUPRA-AORTIC ARCH BRANCH VESSEL DEFORMATIONS Native Supra-Aortic Arch Branch Vessel Deformations In vivo deformation of supra-aortic branch vessels with respect to the thoracic aorta is not well described in the literature to date. According to our analysis, branching angle changes of the arch vessels were not significant due to either cardiac pulsation or respiration (Table 8.9). Although nonsignificant branching angle changes may result from aortic arch translation, it seems that the aortic arch and branch vessels move predominantly in unison. This suggests that aortic arch endografts with branched

TABLE 8.9 Branch Angle Deformation of the Arch Vessels From Native Aorta Cohort (n 5 16) and Thoracic Endovascular Aortic Repair (TEVAR) Cohort (n 5 15, Post-TEVAR) Arch Vessel

Diastole-Systole (Inspiration)

Diastole-Systole (Expiration)

Expiration-Inspiration (Diastole)

Expiration-Inspiration (Systole)

BRANCH ANGLE CHANGE (DEGREE), NATIVE AORTA COHORT BA

2 0.3 6 4.2

2 0.5 6 6.7

2 1.6 6 7.9

2 1.4 6 5.0

LCCA

2 1.0 6 4.3

2 0.3 6 7.8

2 2.3 6 4.7

2 3.0 6 5.6

LSA

2 0.1 6 4.8

2 0.2 6 7.0

2 0.5 6 6.3

2 0.3 6 7.1

BRANCH ANGLE CHANGE (DEGREE), TEVAR COHORT BA

2 4.1 6 6.9

0.8 6 5.9

0.6 6 7.1

2 4.2 6 7.3

LCCA

2 1.8 6 4.8

2.7 6 6.3

2 0.2 6 5.8

2 4.7 6 5.5

LSA

1.4 6 7.7

2.8 6 8.5

2 0.0 6 9.3

2 1.4 6 6.1

Data are shown as mean 6 standard deviation. BA, Brachiocephalic artery; LCCA, left common carotid artery; LSA, left subclavian artery. No significant differences in branch angle deformation were found between the dynamic states or between vessels.

Partially from Suh, G.Y., Beygui, R.E., Fleischmann, D., Cheng, C.P., 2014. Aortic arch vessel geometries and deformations in patients with thoracic aortic aneurysms and dissections. J. Vasc. Interven. Radiol. 25 (12), 1903 1911.

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159

SUPRA-AORTIC ARCH BRANCH VESSEL DEFORMATIONS

components may not be subjected to aggressive cyclic bending and angulation at the arch branches.

Musculoskeletal Influences (Thoracic Outlet Syndrome) Anatomic factors such as the presence of cervical or supernumerary ribs, elongated C7 vertebra transverse process, hypertrophied scalene muscles, or prominent first rib may exert an extrinsic compressive effect on the brachial plexus, subclavian artery, and/or subclavian vein. Static variables may also play a role in conformational change of the thoracic outlet, including postural abnormalities of the spine or shoulder girdle (Vanti et al., 2007), as well as the potential additive effects of local trauma to the shoulder or neck (e.g., whiplash injury or chronic repetitive upper extremity activities related to work or athletics) owing to posttraumatic scarring and shortening of the involved musculature (Sanders et al., 2008). Dynamic postural or fixed arterial stenosis at the thoracic outlet is believed to be a precursor to aneurysm development, most notable in the subclavian artery. Experimental reports suggest that poststenotic dilatation, and subsequent aneurysm formation, is a reversible process following alleviation of the stenotic or compressive physiology (Roach, 1972; Robiesek, 1995). Nevertheless, the natural history and clinical correlation of arterial compression in such cases with thoracic outlet syndrome remain poorly defined, particularly given the fact that such compression of the subclavian artery at the thoracic outlet with provocative maneuvers yields a decrease in palpable distal upper extremity pulse in up to 60% of healthy, asymptomatic individuals and is found bilaterally in nearly one-third of the people (Gergoudis and Barnes, 1980). Indeed, multiple provocative maneuvers are used in

the clinical diagnosis of thoracic outlet syndrome despite specificities ranging from 30% to 100%. Despite the controversial utility of these maneuvers in the diagnosis of patients with thoracic outlet syndrome, the cornerstone of conservative treatment for all forms of thoracic outlet syndrome includes patient education to avoid provocative upper extremity positions, as well as individualized physical therapy geared toward improved posture and relaxation of the thoracic outlet musculature.

Morphologic Alterations Due to Thoracic Aortic Endograft Placement A comparative analysis with our TEVAR cohort revealed that the geometry of supraaortic arch branches was not significantly different between pre- and post-TEVAR states (Table 8.10) (Suh et al., 2014). The branch angle of the LCCA was lower than the BA at pre-TEVAR state, and lower than the LSA at post-TEVAR state (P , .05), which is due to its natural acute angulation near the vertex of the arch (Suh et al., 2014; Wilbring et al., 2016). TABLE 8.10 Supra-Aortic Arch Branch Geometry Before and After Thoracic Endovascular Aortic Repair (TEVAR) (n 5 18) Branch Angle (Degree)

Pre-TEVAR

Post-TEVAR

Post Pre

BA

55.0 6 15.1

3.1 6 10.2

LCCA

0.7 6 5.6

LSA a b

58.1 6 11.0

a

46.4 6 12.3

b

47.1 6 12.8

a

52.6 6 10.9

b

52.1 6 10.6

2 0.6 6 9.3

Indicates significant difference between BA and LCCA (P , .05). Indicates significant difference between LCCA and LSA (P , .05).

Data are shown as mean 6 standard deviation. BA, Brachiocephalic artery; LCCA, left common carotid artery; LSA, left subclavian artery. From Ullery, B.W., Suh, G., Hirotsu, K., Zhu, D., Lee, J.T., Dake, M.D., et al., 2018. Geometric deformations of the thoracic aorta and supra-aortic arch branch vessels following thoracic endovascular aortic repair. Vasc. Endovasc. Surg. 52 (3), 173 180.

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While there are no clinical data demonstrating possible relationship between this relative acuity of LCCA and performance of endovascular device at this site, we opine that the acute configuration of the LCCA may be more challenging for next-generation thoracic aortic endografts with branched components for the arch reconstruction, especially if the branched component is perpendicular to the main body such as in fenestrated endovascular aneurysm repair. Also, the relative acuity of the LCCA may induce an additional technical challenge for a transfemoral approach during branched TEVAR (Ullery et al., 2018).

CONCLUSION The physiologic strains of the thoracic aorta and its branches induced by cardiopulmonary mechanics has been captured by a variety of methods, including in both experimental animal and clinical studies. Multiple investigations indicate that the stented descending thoracic aorta exhibits significantly less deformation during both the cardiac and respiratory cycles, including lower axial length, curvature, and diametric changes compared to the unstented ascending aorta. Our understanding of long-term aortic remodeling continues to evolve, particularly as it relates to natural increases in aortic diameter and arch length with age. The impact of TEVAR on these natural tendencies for the aging aorta is poorly understood, but aortic lengthening appears to be a prominent feature in these patients. The aortic arch branches appear to exhibit less relative motion as compared to the thoracic aorta both acutely and in the long term. Additional investigation is warranted to better elucidate how the augmented mechanical stress and strain observed in the more proximal aorta will impact endografts relative to other aortic

segments. Further, future clinical studies will be important to correlate aortic deformation to endograft performance among patients treated with TEVAR.

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C H A P T E R

9

Abdominal Aorta and Renovisceral Arteries G. Suh1, B. Ullery1,2 and Christopher P. Cheng1 1

Division of Vascular Surgery, Stanford University, Stanford, CA, United States 2 Providence Heart and Vascular Institute, Portland, OR, United States

The abdominal aorta and renovisceral artery branches are subject to deformation related to pulsatile hemodynamics, abdominal organ and diaphragmatic motion due to respiration, and potentially from musculoskeletal movement. In addition, several abdominal aortic and branch vessel pathologies feature a mechanical component, including those related to compressive phenomenon [e.g., median arcuate ligament syndrome (MALS), nutcracker syndrome]. From a therapeutic perspective, patency and durability of stent grafts used in the treatment of renovisceral occlusive disease and complex endovascular abdominal aortic repair (EVAR) may be influenced by repetitive in vivo arterial motion. The present chapter will highlight physiologic-, device-, and remodeling-induced deformations of the abdominal aorta and branch vessels. We will examine theoretical modes of stent graft failure following complex EVAR and discuss durability issues related

Handbook of Vascular Motion DOI: https://doi.org/10.1016/B978-0-12-815713-8.00009-7

to branch vessel angulation (predisposition to endoleak, stent dislocation, or fracture), end-stent angle (potential increased risk of stent fracture and tissue injury resulting in intimal hyperplasia), and branch vessel curvature/tortuosity (mechanical stresses in areas characterized by stiffness and motion discontinuities).

ANATOMY OF ABDOMINAL AORTA Abdominal Aorta The abdominal aorta serves as a continuation of the descending thoracic aorta at the level of the 12th vertebrae posterior to the median arcuate ligament and crura of the diaphragm. The aorta extends caudally down the posterior wall of the abdomen in the retroperitoneal space and is situated directly anterolateral to the vertebral column on the left side of the body. It is accompanied by

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Inferior phrenic artery Celiac trunk Splenic artery

Hepatic artery Superior mesenteric artery Renal artery

Renovisceral Arteries Inferior mesenteric artery

Lumbar artery Gonadal artery

organ. The posterior peritoneum of the abdominal cavity is draped over the abdominal aorta. Organs located directly anterior of the aorta include the stomach, duodenum, and pancreas (Fig. 9.1).

Common iliac artery

Median sacral artery

FIGURE 9.1 Anatomy of the abdominal aorta and its branches.

the azygos vein and the thoracic duct within the diaphragmatic hiatus and runs parallel to the inferior vena cava, which is located to the right of the midline. The abdominal aorta terminates at the fourth lumbar vertebrae level and is marked by bifurcation of the aorta into the common iliac arteries. The abdominal aorta is traditionally divided into the suprarenal (or paravisceral) segment, which is situated inferior to the diaphragm but cephalad to the renal arteries, and the infrarenal segment, which is situated immediately inferior to the renal arteries and extends to the aortic bifurcation. The branches of the abdominal aorta include the right and left inferior phrenic arteries, celiac artery, superior mesenteric artery (SMA), bilateral renal arteries, bilateral gonadal arteries, inferior mesenteric artery (IMA), middle sacral artery, and paired lumbar arteries. Because the aorta lies slightly left of the midline, right-sided arteries are longer than their left-sided equivalent arteries due to the longer required length of travel to the end

Renovisceral arteries are major vessels that branch from the abdominal aorta (Fig. 9.1). The celiac artery branches off the anterior surface of the aorta at the level of the 12th thoracic vertebra and supplies blood to the organs corresponding to the embryonic foregut, including the liver, stomach, distal esophagus, spleen, and proximal duodenum and pancreas. The SMA arises from the anterior surface of the aorta at the level of vertebra L1 and is generally 1 2 cm distal to the celiac artery. It provides blood supply to the structures of the embryonic midgut such as the distal pancreas and the intestines beginning at the distal duodenum and extending through the proximal two-thirds of the transverse colon. Blood supply to the structures of the embryonic hindgut is provided by the IMA at the level of L3 and includes the intestines from the distal one-third of the transverse colon to the proximal rectum. Renal arteries are lateral branches of the abdominal aorta and are situated between the SMA and IMA. The renal arteries carry up to one-third of the total cardiac output to the kidneys. Due to the position of the abdominal aorta left of the midline, the right renal artery (RRA) is longer in length compared to the left renal artery (LRA).

GEOMETRIC ANALYSIS METHODS We utilized image-based modeling and three-dimensional (3D) geometric analysis

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focused on the abdominal aorta and renovisceral arteries. To acquire geometric information, we started with contrast-enhanced image data including magnetic resonance angiograms and computed tomography angiography (CTA). Particularly for respiratory-induced motion, some images were acquired at two separate breathing states, inspiration breath hold with contrast injection and expiration breath hold without contrast injection. Next, we identified lumen boundaries of the abdominal aorta, celiac artery, SMA, LRA, RRA, and, further, metallic boundaries of endovascular devices (aortic endograft and vascular stents) after EVAR. From the segmented contours comprising aorta, vessels, and devices, 3D surface boundaries were lofted for visualization and volume calculation. Lastly, true centerline paths of aorta, vessels, and devices were determined from the mathematical centroids of segmented contours (Fig. 9.2) (Choi et al., 2009a; Wilson et al., 2001). Refer to the chapter on geometric modeling for more details about the image processing and model construction. To understand the regression of the aneurysm sac after EVAR, aortic volume was used. Specifically, the volume was measured separately for the “whole aorta” defined along

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the outer aortic boundary, “lumen” along the inner aortic boundary, and “excluded lumen” subtracting the lumen volume from the whole aorta volume. The top-to-bottom range for volume calculation was from the inferior renal artery to the aortic bifurcation (Fig. 9.3). For the renovisceral arteries, we extracted branch angle, end-stent angle, and curvature. Branch angle is defined as the angle of the branch vector with respect to the orthogonal plane of the aorta at the ostium. The branch vector originates from the ostium and ends at the centerline point 10 mm distal to the ostium along the branch artery centerline. This measurement was used to quantify how much the branch vessel angulation changed with respect to the aorta due to respiration or after snorkel EVAR (Sn-EVAR) or fenestrated EVAR (F-EVAR) (Fig. 9.3). End-stent angle is defined as the angle between the distal end of the stent and the adjacent native artery, with each represented by vectors that are formed by 10 mm of arclength along the centerline. This measurement was used to quantify bending or kinking at the stent end. To compare postop and preop geometries, consistent locations on the branch vessel centerline were approximated by arclengths from the ostium to the stent end (Fig. 9.3) (Ullery et al., 2017). Finally, curvature

FIGURE 9.2 Three-dimensional geometric modeling with an example case after endovascular abdominal aorta repair with snorkel stents. From the CT image, manual centerline paths were created, orthogonal 2D segmentations were performed along those paths separately for stents and vessels, centroids of the segmentations were computed, and true centerline paths were constructed from the centroids. CT, Computed tomography.

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FIGURE 9.3 Quantification of aortic volume and branch angle of visceral arteries before (A) and after EVAR (B). Whole aorta (gray), lumen (yellow), and excluded lumen (subtracting lumen volume from whole aorta volume) were modeled and their 3D volumes were calculated. Branch angle is defined as the angle of the 10 mm branch vector from the orthogonal plane with respect to the aorta. Upward angle is positive and downward angle is negative. The end-stent angle is defined as the angle between the distal stent vector (10 mm arclength) and adjacent native artery vector (10 mm arclength). Since the preop artery does not have stents, the position of the stent-end was approximated by where the stentend resides in the postop condition, and both vectors were formed by the native vessel centerline. EVAR, Endovascular abdominal aortic repair.

was defined as the inverse of the radius of the circumscribed circle defined by three evenly spaced points spanning 10 mm and quantified at every mm along the vessel centerline (Suh et al., 2013a, 2016; Ullery et al., 2015).

PATHOLOGIES OF THE ABDOMINAL AORTA An abdominal aortic aneurysm (AAA) is the most common form of the true arterial aneurysm, which is categorically defined as a segmental dilatation of all three layers of a blood vessel that is in excess of 50% of the normal adjacent arterial diameter. While the mean adult human infrarenal aorta measures approximately 2 cm, the diameter of a normal healthy abdominal aorta varies based on a variety of

demographic factors (e.g., age, gender). Using the definition above, an abdominal aorta with a diameter of 3 cm or more is generally considered aneurysmal. The overwhelming majority of AAAs are limited to the infrarenal aorta, with only 5% of AAAs involving the renal or visceral vessels. Moreover, AAAs may be associated with iliac artery aneurysms in up to 40% of the cases (Chaikof et al., 2018; Hirsch et al., 2006; Johnson et al., 1991). Aneurysms of the abdominal aorta are stratified based on the following classification (Fig. 9.4): Thoracoabdominal aortic aneurysm: The aneurysm involves any component of both the thoracic and abdominal aorta. Suprarenal aortic aneurysm: The aneurysm involves the origin of either the SMA and/ or celiac artery but does not extend to the thoracic aorta.

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FIGURE 9.4

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Classification of abdominal aortic aneurysms.

Pararenal aortic aneurysm: One or both renal arteries arise from the AAA itself; however, the visceral segment (SMA and celiac) is not involved and arises from an otherwise healthy-appearing aorta. Juxtarenal aortic aneurysm: The aneurysm does not involve the origin of either renal artery; however, the aneurysm begins immediately distal to the renal arteries with no normal infrarenal aorta. Infrarenal aortic aneurysm: The aneurysm begins distal to the renal arteries such that there is a well-defined segment of nonaneurysmal aorta below the renal arteries. Risk factors for the development of AAA include male gender, age .65 years, family history of AAA, and tobacco use. The prevalence of AAA is estimated at 1.4% among those between 50 and 84 years of age, amounting to nearly 1.1 million individuals in the United States (Chaikof et al., 2018). General indications for intervention include symptomatic patients (e.g., back or abdominal pain), aneurysm rupture, rapid aneurysmal growth ( . 5 mm/6 months), or absolute size greater than 5.0 5.5 cm. Historically, AAAs were treated with open surgical repair involving a generous midline laparotomy or left flank retroperitoneal incision. However, an endovascular approach to the repair of AAAs has rapidly become the standard of care since its first

FIGURE 9.5 Endovascular abdominal aortic aneurysm repair.

introduction in 1991 for the majority of AAAs. Endovascular AAA repair (EVAR) requires nonaneurysmal proximal and distal attachment sites as defined by device-specific instructions for use (Fig. 9.5). The majority of conventional commercially available EVAR devices require a nonaneurysmal infrarenal neck, or sealing zone, of 10 15 mm, an infrarenal neck diameter of ,32 mm, and infrarenal neck angulation of ,60 degrees. Delivery profile of these endovascular devices range from 14 to 20 Fr and, therefore, require a minimum of 5 6 mm diameter

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iliofemoral access vessels to accommodate passage of the device up to the abdominal aorta. Open surgical repair remains a valid treatment option among those who fail to meet anatomic requirements for EVAR, such as those with the involvement of the renovisceral vessels, challenging infrarenal neck anatomy (e.g., extensive thrombus, extreme angulation), or heavily calcified or tortuous iliofemoral vessels. While the safety and efficacy of EVAR have been reliably demonstrated among those with suitable aneurysm morphology (Giles et al., 2009), it is estimated that up to 30% 40% of the patients are unsuitable anatomic candidates for conventional EVAR, most commonly due to the challenging proximal aortic neck anatomy (Wilderman and Sanchez, 2009). The inadequate proximal landing zone below the renal arteries precludes EVAR using standard devices, thereby restricting such patients to open surgical repair and the associated risks of suprarenal or supravisceral clamping. With increasing surgeon experience and accompanying technologic advances, a myriad of complex endovascular strategies have evolved to address this issue of proximal neck fixation, ranging from deployment of conventional infrarenal aortic stent-grafts outside the instructions for use of the device, homemade and physician-modified endografts, modular branch endografts, snorkel/chimney (Sn-EVAR) approaches with

parallel covered stents, and utilization of customized fenestrated (F-EVAR) endografts. Sn-EVAR and F-EVAR serve as the two most commonly utilized advanced endovascular techniques to combat hostile proximal neck anatomy. F-EVAR utilizes customized fenestrations and/or scallops cut directly into the fabric of the device in order to achieve more proximal seal without compromising renovisceral patency (Fig. 9.6). In contrast, the conceptual basis for Sn-EVAR involves deployment of one or more stent grafts parallel to the main aortic endograft so as to generate a cranial extension of the proximal seal zone with preservation of branch vessel patency, thereby expanding the applicability of aortic endografts from the infrarenal to the suprarenal aorta (Fig. 9.7). Both of these advanced techniques have been applied to more proximal aortic segments, including the aortic arch and paravisceral aorta, as well as for a broader array of pathologic conditions such as aortic dissections. Sn-EVAR utilizes off-the-shelf devices, thereby obviating the manufacturing delay associated with individualized customization of the current fenestrated/branched endografts, and provides a useful endovascular alternative to the treatment of ruptured or symptomatic complex AAAs. Arterial dissections confined to the abdominal aorta are rare and represent less than 2% of

FIGURE 9.6 F-EVAR. Retrograde cannulation of bilateral renal arteries from a transfemoral approach (A); balloon molding of suprarenal barbs and proximal main body piece (B); deployment of balloon-expandable covered stents in the target vessels (C); flaring of proximal portion of the renal artery stents (D); initial completion angiography demonstrating no proximal endoleak, as well as preservation of patency of superior mesenteric artery and bilateral renal arteries (E). F-EVAR, Fenestrated endovascular aneurysm repair.

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FIGURE 9.7 Sn-EVAR. Bilateral antegrade renal artery cannulation from transbrachial artery approach (A); inflation of balloon-expandable renal artery covered stents (B); simultaneous inflation of molding balloon in main body aortic stent graft (C); completion angiography showing the absence of proximal endoleak and preserved patency of bilateral renal artery stents (D). Sn-EVAR, Snorkel endovascular abdominal aortic aneurysm repair.

all aortic dissections, with those involving the ascending aorta (70%), descending thoracic aorta (20%), and aortic arch (7%) being far more common (Roberts and Roberts, 1991). Isolated abdominal aortic dissections typically feature a dissection flap at or below the level of the renal arteries (Baumgartner et al., 1998) and may be spontaneous, traumatic, or iatrogenic in nature. Such aortic pathology may be incidentally discovered during cross-sectional imaging obtained for other reasons or may be associated with clinical symptoms, particularly if there is a rapid expansion of the false lumen. Patients may complain of abdominal or back pain or distal embolization (e.g., cold or pulseless lower extremity). A pulsatile abdominal mass may be present on physical examination if false lumen aneurysmal degeneration is present. Given the relative rarity of these cases, there is no well-defined treatment algorithm in the literature. In a metaanalysis encompassing 92 patients with isolated abdominal aortic dissections reported by Jonker et al. (2009), treatment included conservative management in 29%, open surgical repair in 50%, and endovascular repair using a variety of techniques in 21%. A more recent clinical series of 21 similar patients treated exclusively with endovascular repair noted excellent clinical efficacy, which included no early or late mortality and low

rates of complications and need for secondary intervention (Jawadi et al., 2014). A more common scenario involves extensive arterial dissections of the thoracoabdominal aorta (see Chapter 8. Thoracic Aorta and Supra-Aortic Arch Branches). In addition to impulse control (reduction of heart rate and blood pressure) using pharmacologic agents, the primary objective in the treatment of such cases is to seal the primary entry tear in the proximal thoracic aorta, typically by endovascular exclusion using a stent graft. The remaining portion of the dissection in the abdominal aorta (and even, at times, the distal descending thoracic aorta) is initially left alone. Sealing the proximal entry tear promotes blood flow through the true lumen and facilitates in the remodeling of both the thoracic and abdominal aorta, including false lumen thrombosis and prevention of aneurysmal degeneration.

ABDOMINAL AORTIC DEFORMATIONS Cardiac Pulsatility Before and After Endograft Placement Cross-sectional pulsatile deformation of the abdominal aorta in patients with AAA has

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been quantified before and after infrarenal EVAR (Table 9.1) (Teutelink et al., 2007; van Keulen et al., 2010a). The CTA-based study conducted by Teutelink et al. (2007) reported that preoperatively, from diastole to systole, the mean aortic diameter increased from 24 6 2 to 25 6 2 mm and from 21 6 3 to 23 6 3 mm at the suprarenal and infrarenal levels, respectively (P , .001). Aortic cross-sectional lumen area increased, from diastole to systole, from 464 6 73 to 494 6 76 mm2 and from 381 6 112 to 409 6 118 mm2 at the suprarenal and infrarenal levels, respectively (P , .001). Postoperatively, from diastole to systole, mean aortic diameter increased from 23 6 2 to 25 6 2 mm and from 22 6 3 to 24 6 3 mm at the suprarenal and infrarenal levels, respectively (P , .001). Lumen area increased from 447 6 63 to 480 6 72 mm2 and from 411 6 109 to 436 6 110 mm2 at the suprarenal and infrarenal levels, respectively (P , .001). Neither diameter nor cross-sectional area changes were significantly altered by infrarenal EVAR. van Keulen et al. (2010a) quantified aortic diameter and lumen area change of AAA

patients treated by three different infrarenal AAA endograft designs (Medtronic Talent, Gore Excluder, Medtronic Endurant). The evidence suggests that the presence of these three AAA endograft designs does not significantly affect the compliance of the pararenal aortic segment, with a slight trend of increased distension post-EVAR. This could be due to decreased compliance at the region of the endograft, which could amplify the distention in the region just proximal. At the suprarenal level, the median major/minor axis diameter distension ratio was 1.38, 1.31, and 1.33 pre-EVAR, and 1.34, 1.35, and 1.35 post-EVAR for the Talent, Excluder, and Endurant groups, respectively. These values are all significantly greater than 1.0 (P , .05), indicating asymmetric crosssectional distension with the major axis of distension in the right-anterior direction. Another study conducted by van Keulen et al. (2010b) reported on 26 patients treated with EVAR and divided them into two groups: 11 patients where endograft migration was $ 5 mm and 15 patients where there was little to no endograft migration. The data showed

TABLE 9.1 Pulsatile Percent Changes (From Diastole to Systole) in Mean Diameter and Lumen Cross-Sectional Area Above and Below the Renal Arteries in Abdominal Aortic Aneurysm Patients Before (Preop) and After (Postop) Endovascular Aortic Repair Study

Parameter

SR (Preop)

IR (Preop)

SR (Postop)

IR (Postop)

Teutelink et al. (2007)

Mean diameter

6 (max 5 11)

5 (max 5 14)

7 (max 5 11)

6 (max 5 15)

Cross-sectional area

7.0 (max 5 12.5)

Mean diameter (Talent)

6.4 6 2.0

5.5 6 1.3

6.8 6 2.0

6.4 6 1.0

Mean diameter (Excluder)

5.8 6 1.8

5.4 6 2.0

6.7 6 2.5

5.8 6 0.8

van Keulen (2010a,b)

7.9 (max 5 14.5)

Mean diameter (Endurant)

6.7 6 2.4

5.5 6 1.3

7.9 6 1.8

6.3 6 1.4

Cross-sectional area (Talent)

8.5 6 4.9

5.8 6 1.4

9.9 6 4.0

7.9 6 2.2

Cross-sectional area (Excluder)

8.1 6 3.5

6.0 6 2.3

9.3 6 4.6

6.7 6 1.6

Cross-sectional area (Endurant)

8.2 6 4.4

5.8 6 3.0

10.6 6 4.4

8.4 6 2.9

Data from van Keulen (2010a) are shown as mean 6 standard deviation. SR, Suprarenal aorta; IR, infrarenal aorta. From Teutelink, A., Muhs, B.E., Vincken, K.L., Bartels, L.W., Cornelissen, S.A., van Herwaarden, J.A., et al., 2007. Use of dynamic computed tomography to evaluate pre- and postoperative aortic changes in AAA patients undergoing endovascular aneurysm repair. J. Endovasc. Ther. 14 (1), 44 49; van Keulen, J.W., Moll, F.L., Barwegen, G.K., Vonken, E.P., van Herwaarden, J.A., 2010a. Pulsatile distension of the proximal aneurysm neck is larger in patients with stent graft migration. Eur. J. Vasc. Endovasc. Surg. 40 (3), 326 331.

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that the cardiac-induced diameter and area changes at both the suprarenal and infrarenal levels were significantly higher in the group that experienced stent graft migration, compared to the one that did not experience migration. Multivariate regression analysis showed that suprarenal aortic pulsatility was a significant predictor for stent graft migration after 3 years. van Prehn et al. (2009) utilized cardiacresolved MRI to evaluate the asymmetric aspect of aortic shape changes in the aneurysm neck before and after EVAR at the suprarenal, juxtarenal (between the two renals), and infrarenal levels. The study showed that the changes in major and minor diameter were significantly different at all levels both pre- and post-EVAR, indicating that the presence of asymmetric expansion was consistent. PreEVAR, the major/minor axis diameter change ratios ranged from 1.10 to 1.82, where the suprarenal direction of distention was rightanterior, juxtarenal direction was middleanterior, and infrarenal direction was leftanterior (van Prehn et al., 2009). Asymmetric pulsatile distension has also been supported by data generated from M-mode ultrasound, cine phase contrast MRI, and intravascular ultrasound (Arko et al., 2007; Goergen et al., 2007; van Prehn et al., 2009).

Aortic distension asymmetry may be influenced by the spiraling flow patterns that have been described in the thoracic and abdominal aortas (Hope et al., 2007; Houston et al., 2003, 2004), which may pose asymmetric forces at different longitudinal and circumferential areas of the aorta. Asymmetric aorta distension is also undoubtedly related to the mechanical constraints of branches and surrounding tissues. In fact, it has been hypothesized that the direction of branch angulation of the celiac and superior mesenteric arteries (usually rightanterior), and the IMA (usually left-anterior), might be related to blood flow and distention patterns. Cardiac pulsatility has also been shown to induce noncross-sectional deformations in the abdominal aorta. Iezzi et al. (2014) utilized cardiac-gated CT to assess pulsatile variations in length of the proximal neck in 40 patients aged 80 6 6 years selected to undergo EVAR. Significant longitudinal lengthening was observed from systole to diastole for the proximal aortic neck (from the lowest renal artery to the proximal edge of the aneurysmal sac) of 5.3 6 1.8 mm (19.1 6 8.6%). Similarly, de Jonge et al. (2015) utilized cardiac-gated CT to analyze pulsatile movement of the aorta in 30 patients with infrarenal AAAs at multiple locations of interest (Table 9.2). By finding the

TABLE 9.2 Three-Dimensional Translation Along the Length of the Aorta During the Cardiac Cycle Parameter (mm)

3 cm Distal to the Celiac Trunk

3 cm Proximal to the Distal RA

1 cm Distal to the Distal RA

0.5 cm Distal to the Aortic Bifurcation (Right CIA)

Mediolateral translation

2.3 (1.7 3.9)

2.1 (1.9 2.9)

2.0 (1.8 3.0)

3.5 (2.3 5.5)

Ventrodorsal translation

2.3 (1.8 3.3)

2.5 (2.1 3.2)

2.0 (1.6 2.8)

3.6 (2.7 5.5)

Craniocaudal translation

2.2 (1.9 2.8)

2.6 (1.7 3.1)

2.4 (1.9 2.9)

3.7 (2.5 4.6)

Data are shown as median value (interquartile range). RA, renal artery; CIA, common iliac artery. From de Jonge, C., Zandvoort, J.A., Vonken, E.P.A., Moll, F.L., van Herwaarden, J.A., 2015. Through-plane movement at multiple aortic levels on dynamic computed tomography angiography is limited in patients with an abdominal aortic aneurysm. J. Endovasc. Ther. 22 (5), 765 769.

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difference in translation between two locations, the segment length change was quantified. Note that lengthening of the aorta tends to happen during diastole, meaning that the diametric and longitudinal strains are not in phase with each other. Wittek et al. (2016) used 3D ultrasound speckle tracking to quantify circumferential, longitudinal, and rotational movement of material points on the abdominal aorta from the diaphragm to the proximal renal artery in 18 healthy subjects aged 24 27 years. These movements were then used to quantify the maximum circumferential (12.3%), longitudinal (2.2%), and axial twist (1.2 degree/cm) deformations of the suprarenal region of the aorta during the cardiac cycle. This study also noted that cross-sectional, longitudinal, and twist deformations are not synchronous. Namely, while cross-sectional deformations track the blood pressure, there are phase shifts associated with longitudinal and twist deformations. In general, the largest aortic diameters occur at peak systolic pressure, which approximately coincides with the shortest aortic lengths. This

makes sense since the aortic tissue approximately follows conservation of tissue volume so that an expansion in one direction is accompanied by a contraction in another direction.

Musculoskeletal Influences The abdominal aorta can also deform due to musculoskeletal movement. Hip flexion, known to shorten and curve the iliac arteries since they are anterior to the hip joint, also acts to axially shorten the abdominal aorta (Fig. 9.8). In healthy adult subjects that were scanned with contrast-enhanced magnetic resonance angiography in the supine and fetal positions, the abdominal aorta shortened by 2.9 6 2.1% with maximum hip flexion (Choi et al., 2009b). However, even with maximum hip flexion, the healthy abdominal aorta does not appear to experience significant change in curvature or axial twist. This makes sense because the healthy aorta is under axial tension, so a small amount of shortening due to bilateral hip flexion should not cause the aorta to exceed the point of slack or twist. The

FIGURE 9.8 Magnetic resonance angiography of a subject moving from supine to fetal position (left), and definition of the infrarenal aorta from renal artery ostium to the aortic bifurcation (right). Adapted from Choi, G., Suh, G., Shin, L.K., Taylor, C.A., Cheng, C.P., 2009b. In vivo deformation of the human abdominal aorta and common iliac arteries with hip and knee flexion: implications for the design of stent-grafts. J. Endovasc. Ther. 16 (5), 531 538, Figures 1 and 2.

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deformations of disease aortas would likely be different in the presence of decreased elastic tension and increased tortuosity.

Long-Term Aortic Remodeling after Endograft Placement Volumetric assessment is believed by many to be a more accurate and suitable mode of follow-up surveillance than the more commonly utilized linear diameter measurements. Indeed, multiple studies have demonstrated that changes in linear diameter post-EVAR do not always translate into corresponding changes in 3D aneurysm dimensions (Czermak et al., 2001; Lee et al., 2003; Prinssen et al., 2003). Table 9.3 summarizes measured changes of aneurysm volume and diameter during post-EVAR follow-up surveillance (Bley et al., 2009; Hahne et al., 2012; Czermak et al., 2001; Lee et al., 2003). There are differences in aneurysm growth depending on the

presence or absence of endoleak. Also, Hahne et al. and Bley et al. have revealed marked differences in volume and diameter modification rates by comparing different types of endoleak, including a more rapid and absolute increase in aneurysm dimensions among those with high-flow (Type I or III) endoleaks compared to the lower flow Type II endoleaks (Bley et al., 2009; Hahne et al., 2012). Our analysis with complex EVAR patients was specifically focused on tracking aortic volume (whole aorta, lumen, and excluded lumen) over the study period (Table 9.4) (Ullery et al., 2017). The median period between preop CT and surgery was 77 (13 194) days, and the period between surgery and follow-up CT was 350 (58 1249) days. From the postop to followup time point, volumes of the whole aorta and excluded lumen decreased significantly (P , .05), which was due to thrombus regression after surgery. Volume changes from the preop to postop time point did not correlate

TABLE 9.3 Preoperative or Postoperative to Follow-Up Change of Volume and Diameter of Abdominal Aorta After Endovascular Abdominal Aortic Repair Study (Follow-Up Interval) Czermak et al. (2001) (12-month follow-up)

Lee et al. (2003) (5-year follow-up)

Patient Group

Volume (mL or %)

Diameter (cm)

All (n 5 37)

222 mL (47 600); postop-199 mL (41 2 687; 12 months)

NA

Secondary Type IA (n 5 1)

280 mL (postop)-310 mL (12 months)

NA

Secondary Type IB (n 5 1)

122 mL (postop)-115 mL (12 months)

NA

Secondary Type III (n 5 3)

161 mL (postop)-165 mL (12 months)

NA

All (n 5 177)

25.8% (1 year), 26.7% (2 years), 212.9% (5 years); compared to preop

22.4 cm (1 year), 23.3 cm (2 years), 27.4 cm (5 years); compared to preop

No endoleak (n 5 115) 212.9% (1 year), 216.7% (2 years), 224.9% NA (5 years); compared to preop Endoleak (n 5 62)

4.0% (1 year), 4.9% (2 years), 21.6% (5 years); compared to preop

NA (Continued)

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TABLE 9.3 (Continued) Study (Follow-Up Interval) Bley et al. (2009) (12-month follow-up)

Hahne et al. (2012) (17-month mean follow-up)

Patient Group

Volume (mL or %)

Diameter (cm)

No endoleak (n 5 183) 23.2% (24.71 to 22.0)

NA

Types I and III (n 5 10)

10.0% (5.0 2 18.2)

NA

Type II (n 5 37)

5.4% (4.6 2 6.2)

NA

No endoleak (n 5 31)

240.0 mL (8.2 2 62.5) (224.2%)

21.4 cm (0.4 2 2.9) (223.5%)

Type I (n 5 3)

107.7 mL (13.4 2 201.9) (34.6%)

1.0 cm (0.2 2 1.7) (16.4%)

Type II (n 5 34)

20.6 mL (28.6 2 117.7) (12.4%)

0.5 cm (20.2 2 1.9) (8.1%)

Data are shown as median value (range when it is available). From Czermak, B.V., Fraedrich, G., Schocke, M.F., Seingruber, I.E., Waldenberger, P., Perkmann, R., et al., 2001. Serial CT volume measurements after endovascular aorticaneurysm repair. J. Endovasc. Ther. 8 (4), 380 389; Lee, J.T., Aziz, I.N., Lee, J.T., Haukoos, J.S., Donayre, C.E., Walot, I., et al., 2003. Volume regression of abdominal aortic aneurysms and its relation to successful endoluminal exclusion. J. Vasc. Surg. 38 (6), 1254 1263; Bley, T.A., Chase, P.J., Reeder, S.B., Franc¸ois, C.J., Shinki,K., Tefera, G., et al., 2009. Endovascular abdominal aorticaneurysm repair: nonenhanced volumetric CT forfollow-up. Radiology 253 (1), 253 262; Hahne, J.D., Arndt, C., Herrmann, J., Schonnagel, B.,Adam, G., Habermann, C.R., 2012. Follow-up of abdominalaortic aneurysm after endovascular aortic repair:comparison of volumetric and diametric measurement. Eur. J. Radiol. 81 (6), 1187 1191.

TABLE 9.4 Volume Changes (Δ, cm3) of the Abdominal Aorta Treated With Endovascular Repair From Preoperative to Early Postoperative and Latest Follow-Up Patient Group

Volumetric Region

Δ(Postop 2 Preop)

Δ(Follow-Up 2 Postop)

Δ(Follow-Up 2 Preop)

All (n 5 29)

Whole aorta

16 6 37a,b

228 6 62a,b

212 6 83

Lumen

262 6 79

3 6 10

260 6 75a,c

Excluded lumen

79 6 87a,b,c

231 6 64a,b,c

48 6 85a,c

Whole aorta

13 6 23a,b

247 6 48a,b,d

235 6 43a,d

Lumen

278 6 92a,b,c

3 6 10b,c

275 6 86a,c

Excluded lumen

91 6 100a,b,c

250 6 52a,b,c,d

40 6 71a,c

Whole aorta

23 6 57

8 6 70d

32 6 122d

Lumen

233 6 33a,b,c

1 6 9b

232 6 35a,c

Excluded lumen

56 6 48a,b,c

7 6 72b,d

63 6 109c

No endoleak (n 5 19)

Endoleak (n 5 10)

a,b,c

b,c

a

Indicates significant changes between time points. Indicates difference between Δ(postop 2 preop) and Δ(follow-up 2 postop). c Indicates significant difference between lumen and excluded lumen. d Indicates significant difference between no endoleak group and endoleak group. Data are shown as mean 6 standard deviation. Δ, Change of volume. Significance threshold was set as P , .05. Partially from Ullery, B.W., Suh, G.Y., Kim, J.J., Lee, J.T., Dalman, R.L., Cheng, C.P., 2017. Dynamic geometric analysis of the renal arteries and aorta following complex endovascular aneurysm repair. Ann. Vasc. Surg. 43, 85 95. b

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PATHOLOGIES OF THE RENOVISCERAL ARTERIES

with the changes from the postop to follow-up time point in the whole aorta, lumen, or excluded lumen. This means that geometry change immediately after EVAR may not be predictive of postoperative remodeling over time. Moreover, like other studies reported (Table 9.3), we observed different levels of aortic volume change depending on whether there was an endoleak or not. Among 29 patients with complex EVAR, 10 patients exhibited Type IA or II endoleak during the study period. From postop to follow-up time point, the endoleak group exhibited an insignificant change of the whole aorta and excluded lumen, whereas the no endoleak group did exhibit a significant change (P , .05). This supports the hypothesis suggested by other studies that the presence of endoleak interferes with successful aneurysm regression.

PATHOLOGIES OF THE RENOVISCERAL ARTERIES Mesenteric ischemia refers to the relative hypoperfusion of the intestines and may be classified as either acute or chronic depending on the duration of symptoms. More commonly, chronic mesenteric ischemia (also referred to as intestinal angina) is marked by episodic or continued hypoperfusion of the small intestine and occurs primarily in those with the occlusive disease in more than one mesenteric arterial bed. The most common etiology of chronic mesenteric ischemia is atherosclerosis, usually occurring at the ostium of the celiac artery, SMA, and/or IMA. Less frequent causes include vasculitis, arterial dissection, fibromuscular dysplasia, radiation-induced narrowing, or vasospastic disorders. While atherosclerosis of the visceral vessels is relatively common, usually involving the ostial segment of the vessel but may be more diffuse, the presence of clinically relevant symptoms associated with mesenteric artery disease is rare (Hansen et al.,

177

2004; Thomas et al., 1998). In one review, up to 60% of the patients with mesenteric artery occlusive disease were noted to be completely asymptomatic (ter Steege et al., 2012). When present, symptoms associated with chronic mesenteric ischemia classically feature postprandial abdominal pain, unintentional weight loss, and food aversion owing to the anticipation of pain after eating. Diagnosis of chronic mesenteric ischemia is frequently delayed as the differential diagnosis of relatively nonspecific abdominal pain and weight loss is quite broad. Due to the robust collateral network within the visceral arterial beds, high-grade stenosis and/or occlusion of at least two major visceral vessels must be established. Abdominal duplex ultrasound and CTA serve as the two dominant imaging modalities for chronic mesenteric ischemia, both having sensitivities in excess of 90% (Cognet et al., 2002; Holland et al., 1996; Harward et al., 1993; Nicoloff et al., 1997). Revascularization is indicated for patients with severe symptoms and documented mesenteric artery occlusive disease. Options for revascularization include open surgical reconstruction (e.g., bypass or endarterectomy) and endovascular stenting. A recent systematic review identified 8 observational studies with 569 patients treated for chronic mesenteric ischemia with either open or endovascular modalities (Cai et al., 2015); it showed no significant difference in perioperative mortality between the groups. The endovascular group noted lower in-hospital complications but at the expense of a higher recurrence rate within 3 years of revascularization compared to those undergoing open revascularization. MALS, also referred to as celiac artery compression syndrome or Dunbar syndrome, is a relatively rare vascular disorder characterized by chronic and recurrent abdominal pain related to a variable combination of mechanical extrinsic compression of the celiac artery and excessive stimulation of the celiac sympathetic plexus (Fig. 9.9) (Bech, 1977; Delis et al., 2007;

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FIGURE 9.9 Median arcuate ligament syndrome illustrated from coronal and sagittal views. The celiac axis is compressed due to low riding median arcuate ligament.

Sultan et al., 2013; Szilagyi et al., 1972). While this uncommon disorder is classically characterized by the clinical triad of postprandial abdominal pain, weight loss, and the occasional abdominal bruit, the diagnosis of MALS is considered a diagnosis of exclusion given such nonspecific symptoms overlap with many other abnormalities, including chronic mesenteric ischemia. Diagnosis of MALS requires dedicated vascular imaging, preferably during both inspiration and expiration, to confirm compression of the celiac artery by the fibrous arch of the median arcuate ligament that traverses the aorta and bridges the diaphragmatic crura. Treatment is indicated for symptomatic patients with imaging confirmation of celiac artery compression. The primary objective in the treatment of MALS is celiac artery decompression by dividing the median arcuate ligament. A variety of approaches have been described as it pertains to so-called release of the median arcuate ligament, including using conventional laparotomy and laparoscopic or robotic-assisted laparoscopic techniques (Sultan et al., 2013). Some surgeons will perform division of the celiac plexus (e.g., neurolysis) at the time of ligament release in order to address the potential neuropathic

component of the disease process. In cases of persistent or recurrent symptoms, ganglionectomy is recommended if not done already. Open or endovascular revascularization may also be required in such cases. Importantly, revascularization should not be performed without initial celiac artery decompression. Multiple series have reported poor outcomes in cases where revascularization was used as the only interventional strategy, presumably owing to the negative effect of persistent extrinsic pressure exerted on the revascularized celiac artery (Matsumoto et al., 1995; Takach et al., 1996). Nutcracker syndrome was first described in 1937 and refers to patients presenting with signs and symptoms associated with anatomic compression of the left renal vein (Grant, 1937). Classically, the left renal vein is compressed between the SMA and abdominal aorta. Previous reports have described that an SMA branching angle of ,35 degrees is required for the diagnosis of nutcracker syndrome. Such a branching pattern produces aortomesenteric narrowing of the left renal vein, which promotes local venous hypertension and dilation of the veins of the kidney and ureter. In addition to pelvic or flank pain, clinical findings in such patients may include gonadal varices due to associated renal or pelvic venous congestion or hematuria resulting from rupture of these thin-walled veins into the urinary system. A less common anatomic variant, sometimes referred to as posterior nutcracker syndrome, involves compression of the left renal vein between the aorta and the vertebral body (Erben et al., 2013; Skeik et al., 2011; Velasquez et al., 2018). The prevalence of nutcracker syndrome is not clearly known as the majority of reports to date are limited to case reports or small retrospective series. Moreover, the anatomy characteristic of nutcracker syndrome (referred to as nutcracker “phenomenon”) is suggested as a normal variant by many given

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FIGURE 9.10 Nutcracker syndrome. Extrinsic compression of the proximal left renal vein by the superior mesenteric artery, resulting in dilatation of the more distal left renal vein and its tributaries (A). Surgical repair in the form of left renal vein transposition to the more caudal inferior vena cava and oversewing of the native left renal vein ostium (B). From Reed, N.R., Kaira, M., Bower, T., Vrtiska, T.J., Ricotta, J.J., Gioviczki, P., 2009. Left renal vein transposition for nutcrackersyndrome. J. Vasc. Surg. 49 (2), 386 394, Figure 1.

that such findings may be present in individuals void of any corresponding clinical sequelae (Velasquez et al., 2018). Given the paucity of cases reported in the literature, optimal management of such patients remains ill defined. Nonoperative management can generally be pursued in those with mild symptoms or in young patients. However, the majority opinion within the field of vascular surgery would argue open surgical repair to be the standard of care in symptomatic patients. The goal of open surgery in these patients is to reduce or eliminate the left renal vein compression and may be accomplished by a variety of methods, including transposition of the left renal vein, nephropexy, renal autotransplantation, or gonadocaval bypass (Erben et al., 2013; Ullery et al., 2014; Wang et al., 2012). Left renal vein transposition, which serves as the most widely reported form of

open repair in these patients, corrects the venous compression at the aortomesenteric angle by moving the takeoff of the left renal vein caudally by several centimeters (Fig. 9.10). More recently, various endovascular interventions have been attempted in these patients but results are limited by short-term follow-up and mixed, including several cases of reported migration of stents into the inferior vena cava (IVC) (Chen et al., 2011; Wang et al., 2012; Wu et al., 2016).

RENOVISCERAL ARTERY DEFORMATIONS Native Renovisceral Artery Motion Renovisceral arteries exhibit complex motion due to a combination of the heartbeat and

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TABLE 9.5 Cardiac-Induced Motion of the Proximal Renal Arteries in Healthy Subjects and Patients With Abdominal Aortic Aneurysm Before (Preop) Endovascular Aortic Repair Study

Parameter (mm)

LRA

RRA

Kaandrop et al. (2000) (healthy subjects)

AP translation

1.1 6 0.4

1.5 6 0.5

CC translation

1.7 6 0.6

1.7 6 0.5

3D translation

2.1 6 0.5

2.3 6 0.6

3D translation (preop)

2.0 6 0.6 (1.1 2 3.0)

Muhs et al. (2006) (AAA patients)

Data are shown as mean 6 standard deviation (range, Muhs et al., 2006). LRA, Left renal artery; RRA, right renal artery; AAA, abdominal aortic aneurysm; AP, anterior posterior; CC, cradio-caudal. From Kaandrop, D.W., Vasbinder, G.B., de Haan, M.W., Kemerink, G.J., van Engelshoven, J.M., 2000. Motion of the proximal renal artery during the cardiac cycle. J. Magn. Reson. Imaging 12 (6), 924 928; Muhs, B.E., Teutelink, A., Prokop, M., Vincken, K.L., Moll, F.L., Verhagen, H.J.M., 2006. Endovascular aneurysm repair alters renal artery movement: a preliminary evaluation using dynamic CTA. J. Endovasc. Ther. 13 (4), 476 480.

TABLE 9.6 Respiratory-Induced Motion of the Proximal Renal Arteries in Healthy Subjects Study

Parameter

LRA

RRA

Draney et al. (2005)

AP translation (mm)

0.3 6 0.9

0.2 6 0.7

SI translation (mm)

1.6 6 1.3

1.2 6 1.2

Coronal branch angle (degree)

565

865

Axial branch angle (degree)

21 6 8

1 6 8

Data are shown as mean 6 standard deviation. Translation was calculated from (expiration 2 inspiration). LRA, Left renal artery; RRA, right renal artery; AP, anterior posterior; SI, superior inferior. From Draney, M.T., Zarins, C.K., Taylor, C.A., 2005. Three-dimensional analysis of renal artery bending motion during respiration. J. Endovasc. Ther. 12 (3), 380 386.

breathing. Respiratory-induced vessel deformations are related to the geometry of the vessel, driving forces of adjacent structures due to breathing, and the interaction between the vessel and the driving forces (Draney et al., 2005). Likewise, cardiac pulsation distorts vessels in three dimensions (Kaandrop et al., 2000). Tables 9.5 and 9.6 summarize the measured motion of renal arteries during cardiac pulsation and respiration from published studies (Tables 9.5 and 9.6) (Draney et al., 2005; Kaandrop et al., 2000; Muhs et al., 2006). Note that from before to after

infrarenal EVAR in AAA patients, proximal renal artery 3D translation decreases slightly from 2.0 6 0.6 to 1.4 6 0.7 mm (Muhs et al., 2006). Our studies with healthy subjects and patients with small AAAs demonstrated significant deformation of the renovisceral arteries accompanied by kidney translation during respiration (Fig. 9.11) (Suh et al., 2013b, 2016). With expiration, the small AAA group exhibited upward angulation at the SMA and renal artery branch points and curvature increased for all renovisceral arteries (P , .05) (Table 9.7).

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FIGURE 9.11 Native aneurysmal aorta, renovisceral arteries, and kidneys at inspiration (yellow) and expiration (red). From Suh, G.Y., Choi, G., Herfkens, R.J., Dalman, R.L., Cheng, C.P., 2016. Three-dimensional modeling analysis of visceralarteries and kidneys during respiration. Ann. Vasc. Surg. 34, 250 260, Figure 4.

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TABLE 9.7 Branching Angles and Curvatures in Native Visceral Arteries at Inspiration and Respiratory-Induced Change in Patients With Small Abdominal Aortic Aneurysms Measurement

Celiac Artery

SMA

Branch angle (Insp., degree)

236 6 18

229 6 11

225 6 14

232 6 15

Δ(Exp. 2 Insp., degree)

21 6 9

10 6 6

666

5 6 5d,c

Mean curvature (Insp., mm21)

0.08 6 0.03a,b

0.03 6 0.02e,f

0.05 6 0.02e,g

0.07 6 0.02f,g

Δ(Exp. 2 Insp.)

0.03 6 0.02a,b,c,d

0.02 6 0.01a,d

0.01 6 0.02b,d

0.01 6 0.01c,d

Maximum curvature change (Exp. 2 Insp.)

0.10 6 0.07a,c

0.05 6 0.02a

0.07 6 0.03

0.04 6 0.03c

a,b,d

LRA

a,d

RRA

b,d

a

Indicates statistical significance between celiac and SMA. Indicates statistical significance between celiac and LRA. c Indicates statistical significance between celiac and RRA. d Indicates significant changes due to respiration (inspiration vs expiration). e Indicates statistical significance between SMA and LRA. f Indicates statistical significance between SMA and RRA. g Indicates statistical significance between LRA and RRA. Data are shown as mean 6 standard deviation. Negative branch angle indicates downward-directed branching. Positive branch angle change indicated upward-directed motion. Significance threshold was adjusted by Bonferroni Holm correction for multiple comparisons. SMA, Superior mesenteric artery; LRA, left renal artery; RRA, right renal artery. From Suh, G.Y., Choi, G., Herfkens, R.J., Dalman, R.L., Cheng, C.P., 2016. Three-dimensional modeling analysis of visceralarteries and kidneys during respiration. Ann. Vasc. Surg. 34, 250 260. b

Renovisceral Artery Motion after Complex Endovascular Abdominal Aortic Repair When a vessel is stented, additional factors are involved with vessel motion, such as the altered compliance of the stented vessel and the transition to the native vessel. In the presence of a main body aortic endograft as in cases of complex EVAR, vascular motion is also dependent on the mechanical interaction between the branch stent with the main body device (Muhs et al., 2006). The mechanical stability of the interface of the aortic main body stent-graft and the branch vessel stent affects the risk of endoleak and stent dislocation. In addition, the transition location at the end of a stent to the native vessel is preferentially prone to intimal hyperplasia, remodeling, and restenosis, possibly due to repetitive stresses from cyclic deformations and an abrupt change in mechanical properties (Muhs et al., 2006; Rachev et al., 2000). In complex EVAR patients, expiration was associated with increased angulation at the end of the branch stent and increased curvature distal

to the stent, although the branch angulation from the aorta did not significantly change with respiration. Due to the mechanical support of the stent, the stented renal arteries seemed to experience less branch angle motion compared to the native arteries (Holland et al., 1996). However, stented renal arteries have to deform distally to the branch vessel stent in order to accommodate kidney displacement during respiration. Geometric measurements and their changes from inspiration to expiration for stented renal arteries and SMAs in Sn-EVAR and F-EVAR are presented in Tables 9.8 and 9.9. The renal branches in the snorkel group were significantly more downward angled than those in the fenestrated group (P , .05). Moreover, RRAs exhibited greater end-stent angle and peak curvature in the snorkel group compared to the fenestrated group (P , .05). The endstent angle significantly increased from inspiration to expiration in Sn-LRAs (P , .05), accompanied by a significant increase in peak curvature from inspiration to expiration (P , .05) (Table 9.8) (Ullery et al., 2015).

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TABLE 9.8 Branch Angle, End-Stent Angle, and Peak Curvature of the Renal Arteries, and Their Changes From Inspiration to Expiration in Patients With Complex Endovascular Aortic Repair Measurement

Sn-LRA (n 5 9)

F-LRA (n 5 11)

Sn-RRA (n 5 9)

F-RRA (n 5 9)

Branch angle (Insp., degree)

246 6 12

213 6 12

213 6 13

216 6 16a

Δ(Exp. Insp., degree)

263

164

21 6 7

164

End-stent angle (Insp., degree)

33 6 20

26 6 16

42 6 9

32 6 8a

Δ(Exp. Insp., degree)

4 6 4c

068

568

Peak curvature (Insp., mm )

0.10 6 0.0.3

0.10 6 0.05

0.11 6 0.01

0.09 6 0.02a

Δ(Exp. Insp., mm21)

0.02 6 0.01a

0.00 6 0.01

0.01 6 0.02

0.00 6 0.01

a,b

21

a

a,b

a

165 a

a

Indicates significant difference between snorkel and fenestrated renal arteries. Indicates significant difference between LRA and RRA. c Indicates significant changes due to respiration (inspiration vs expiration). Data are shown as mean 6 standard deviation. Positive end-stent angle indicates vessel angulation with respect to the stent at its distal end. Significance threshold was set as P , .05. Sn, Snorkel; F, fenestrated; Insp., inspiration; Exp. expiration; LRA, left renal artery; RRA, right renal artery. From Ullery, B.W., Suh, G.Y., Lee, J.T., Liu, B., Stineman, R., Dalman, R.L., et al., 2015. Geometry and respiratory-induced deformation of abdominal branch vessels and stents after complex endovascular aneurysm repair. J. Vasc. Surg. 61 (4), 875 884. b

TABLE 9.9 Branch Angle, Peak Curvature, and Their Changes due to Respiration of Unstented and Stented Superior Mesenteric Arteries in Patients With Complex Endovascular Aortic Repair Measurement

U-SMA (n 5 17)

Sn-SMA (n 5 3)

Branch angle (Insp., degree)

228 6 16

237 6 15

Δ(Exp. 2 Insp., degree)

268

362

Peak curvature (Insp., mm21)

0.06 6 0.02

0.05 6 0.01

Δ(Exp. 2 Insp., mm21)

0.01 6 0.02

0.00 6 0.02

Data are shown as mean 6 standard deviation. No differences were found between inspiration and expiration, or between unstented and stent SMAs. U, Unstented; Sn, snorkel; Insp. inspiration; Exp, expiration; SMA, superior mesenteric artery. From Ullery, B.W., Suh, G.Y., Lee, J.T., Liu, B., Stineman, R., Dalman, R.L., et al., 2015. Geometry and respiratory-induced deformation of abdominal branch vessels and stents after complex endovascular aneurysm repair. J. Vasc. Surg. 61 (4), 875 884.

Respiratory-induced deformation of renal artery geometry appeared different between our two groups of complex EVAR procedures. Careful analysis of end-stent angle changes revealed that the Sn-renals were more commonly associated with increased end-stent

bending, presumably related to the cephalad motion, or superior lift, during expiration of the relatively caudally oriented renal artery. In contrast, renal arteries in fenestrated EVAR cases tended to be more perpendicular in orientation relative to the axis of the aorta and, therefore, the corresponding F-renal stents exhibited as much end-stent straightening as they did bending during expiration depending on the geometric properties of the native renal artery (Fig. 9.12). Expiration was also noted to induce a significant reduction in radius of curvature in the proximal 30 mm of the Sn-LRA. No such change in the radius of curvature was found in the remaining Sn-RRA or F-renal groups. The summation of the geometric changes observed in this analysis aids in clarifying that the Sn-LRA exhibits the most significant respiratory deformation among the other renal artery configurations in complex EVAR. Given the well-documented increased incidence of stent fractures involving the left rather than the right side (Robertson et al., 2008), our results support the cyclic deformation of the Sn-LRA as one potential mechanism of longterm clinical failure.

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FIGURE 9.12

Comparison of renal geometries between preop (gray), postop (yellow), and follow-up (blue) for example cases of Sn-EVAR (left) and F-EVAR (right) (A). Comparison of vessel geometries between inspiration (gray) and expiration (yellow) for example cases of Sn-EVAR (left) and F-EVAR (right) (B). Respiratory-induced end-stent angle change highlighted with blue circles for Sn- and F-EVAR examples. Sn, Snorkel; EVAR, endovascular aortic repair; F, fenestrated. Adapted from Ullery, B.W., Suh, G.Y., Kim, J.J., Lee, J.T., Dalman, R.L., Cheng, C.P., 2017. Dynamic geometric analysis of the renal arteries and aorta following complex endovascular aneurysm repair. Ann. Vasc. Surg. 43, 85 95, Figure 3 and Ullery, B.W., Suh, G. Y., Lee, J.T., Liu, B., Stineman, R., Dalman, R.L., Cheng, C.P., 2015. Geometry and respiratory-induced deformation of abdominal branch vessels and stents and after complex endovascular aneurysm repair. J. Vasc. Surg. 61 (4), 875 884, Figure 3.

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The SMAs in complex EVAR patients were mostly unstented (17 of 20), except for 3 SMAs which were snorkeled. No statistical significance was observed between the unstented and stented SMAs for branch angle, peak curvature, or their changes from inspiration to expiration (Table 9.9) (Ullery et al., 2015).

Acute and Long-Term Morphologic Alterations Due to Complex Endovascular Abdominal Aortic Repair We now turn our attention to geometric changes of the renovisceral arteries over time from preop to postop to follow-up after complex EVAR. While the Sn-EVAR procedure significantly angles the renal arteries downward, and the F-EVAR procedure significantly angles the renal arteries upward, there were no significant differences in branch angle from immediate postop to long-term follow-up [median follow-up 764 days (range, 7 1653 days)] (Table 9.10). This means that the major geometric change in renal branch angulation for both Sn-EVAR and F-EVAR occurs

immediately after the procedure, likely a result of initial stent configuration with no additional branch angulation remodeling over time. Interestingly, when considering the subpopulation of Sn-renal arteries implanted with selfexpanding stents, it seems that the downward angling of Sn-renals was reversed and partially recovered their natural preop geometry. Specifically, from postop to follow-up, Snrenals with self-expanding stents (n 5 7) increased their branch angle by 14 6 26 degrees, which was significantly greater than the branch angle change of 0 6 6 degrees in Snrenals with balloon-expandable stents (n 5 20) (P , .05) (Ullery et al., 2017). End-stent angulation was one additional geometric parameter that was notably different between the two procedure groups. While Frenals were observed to have reduced end-stent angulation (straightening of the distal vessel relative to the stent) early in the postoperative course, these same F-renals were noted to have significantly increased end-stent angulation in later follow-up. A very different pattern of geometric deformation occurred in the Sn-renals,

TABLE 9.10 Geometric Angle Change of Stented Renal Arteries From Preop, Postop, to Follow-Up Angle Measurement (Degree)

Preop

Postop

Follow-Up

Δ(FollowΔ(Postop 2 Preop) up 2 Postop)

Δ(Followup 2 Preop)

Branch angle (F-renal, n 5 24)

226 6 20 212 6 18a 27 6 9a

14 6 9a,b,c

5 6 11c

19 6 12a,b

Branch angle (Sn-renal, n 5 27)

225 6 22 242 6 16a 238 6 18a

217 6 19a,b,c

4 6 15c

213 6 25a,b

End-stent angle (F-renal, n 5 24)

30 6 15

26 6 14a

31 6 17

24 6 12a,c

5 6 10b,c

1 6 15a

End-stent angle (Sn-renal, n 5 27)

24 6 13

36 6 16a

37 6 19

12 6 15a,b,c

2 6 9c

14 6 15a,b

a

Indicates significant difference of renal geometry between fenestration (F) and snorkel (Sn) EVAR. Indicates significant changes between time points. c Indicates difference between Δ(postop 2 preop) and Δ(follow-up 2 postop). Data are shown as mean 6 standard deviation. Negative branch angle indicates downward branching. Positive end-stent angle indicates vessel angulation with respect to the straight stent orientation. Significance threshold was set as P , .05. Sn, Snorkel; F, fenestrated. From Ullery, B.W., Suh, G.Y., Kim, J.J., Lee, J.T., Dalman, R.L., Cheng, C.P., 2017. Dynamic geometric analysis of the renal arteries and aorta following complex endovascular aneurysm repair. Ann. Vasc. Surg. 43, 85 95. b

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whereby a greater early abrupt change in end-stent angulation was seen on initial postoperative imaging (increased angle of the distal vessel relative to the stent). Unlike F-renals, a minimal geometric change occurred in the Snrenals during the follow-up period. The overall net end-stent angle change during the entire study period, spanning preoperative to followup, was significantly less for F-renals compared to Sn-renals. The temporal and directional trends in renal artery motion following complex EVAR suggest that the interface of the distal renal stent and native vessel may serve as a dynamic location that is vulnerable to tissue stress and continued remodeling over time. Both by device design and patient/anatomic selection, branch vessel stents in F-EVAR are generally shorter, straighter, and more closely aligned with native arterial anatomy. Conversely, Sn-EVAR commonly includes branch vessel stents that are longer, more tortuous, and often with an acute bend at or near the target vessel ostium. Our previous work has suggested an anatomically and geometrically more favorable renal artery configuration in F-EVAR as a result of the significant increase of end-stent angulation and curvature observed in the Sn-EVAR group postintervention (Ullery et al., 2015, 2016). In fact, a previous investigation noted that renal stent morphology does correlate with renal function decline after Sn-EVAR (Tran et al., 2016). We hypothesize that severe geometric changes may compromise patency and longterm durability of the parallel stent graft configuration, particularly since the geometric deformations are accentuated during the respiratory cycle, an obviously nonmodifiable variable. While the infrequent occurrence of adverse target branch vessel events in the present experience limits our ability to adequately correlate respiratory-induced deformations with clinical outcome, it is interesting to note that both renal stent occlusions in our series occurred in the SnEVAR group. Moreover, all three renal stent

issues in our series (e.g., two incidental occlusions and one incidental kinking) were left-sided. Others have also noted a predilection for poorer outcomes with LRA stents in complex EVAR, including a higher incidence of stent fractures compared to the right side (Robertson et al., 2008). Based on our earlier analyses focused on respiratory deformations of the native unstented renal arteries, we opine that the stented LRA is likely more mobile than the stented RRA due to the RRA being in close proximity and mechanically supported by the inferior vena cava (Suh et al., 2013a,b). The impact of geometric change after complex EVAR, specifically with regard to its capacity to predict branch vessel failure and need for reintervention, remains poorly understood. In the only similar investigation on this topic, Sylvan et al. (2016) performed a quantitative assessment of branch vessel curvature and its effect on the durability of visceral and renal branches in 168 patients undergoing endovascular repair of Crawford Types II and III thoracoabdominal aneurysms with fenestrated/ branched endografts. Their analysis included 558 target vessels (110 celiac, 134 superior mesenteric artery, 157 left renal, 157 right renal) and found a significant difference before and after endovascular intervention for global celiac artery curvature (decreased), global LRA curvature (decreased), maximum LRA curvature (increased), and maximum right renal curvature (increased). Thirty-seven adverse events [6 branch vessel occlusions and 31 reinterventions (24 Type III endoleaks, 5 vessel stenosis, and 2 vessel occlusions)] occurred in 30 patients, with the majority ( . 70%) of these adverse events paradoxically occurring in those with low-tomedium curvature. The authors acknowledged that their analysis failed to take into account other factors, such as respiratory motion and the effect of overlapping self-expanding stents with stiffer balloon-expandable stents in higher risk vessels, which may affect the development of these adverse events.

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CONCLUSION The abdominal aorta and associated branch vessels are dynamic structures subjected to deformation from respiratory mechanics, pulsatile hemodynamics, and musculoskeletal movement. A variety of quantitative methods have been applied to better assess the geometric change that occurs in these arteries both in their native state and following complex endovascular repair. While unique temporal and directional changes in anatomy have begun to be enumerated across different patient and treatment groups, particularly in the renal artery distribution, the impact of these geometric deformations as it pertains to clinical outcome and device (stent graft) durability remains poorly defined. Continued longitudinal assessment of these anatomic changes will aid in our understanding of the natural history of vascular disease and the identification of potential failure mechanisms of the current technology owing to device fatigue.

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patients with an abdominal aortic aneurysm. J. Vasc. Surg. 67 (1), 2 77. Chen, S., Zhang, H., Shi, H., Tian, L., Jin, W., Li, M., 2011. Endovascular stenting for treatment of nutcracker syndrome: report of 61 cases with long-term follow-up. J. Urol. 186 (2), 570 575. Choi, G., Cheng, C.P., Wilson, N.M., Taylor, C.A., 2009a. Methods for quantifying three-dimensional deformation of arteries due to pulsatile and nonpulsatile forces: implications for the design of stents and stent grafts. Ann. Biomed. Eng. 37 (1), 14 33. Choi, G., Suh, G., Shin, L.K., Taylor, C.A., Cheng, C.P., 2009b. In vivo deformation of the human abdominal aorta and common iliac arteries with hip and knee flexion: implications for the design of stent-grafts. J. Endovasc. Ther. 16 (5), 531 538. Cognet, F., Ben Salem, D., Dranssart, M., Cercueil, J.P., Weiller, M., Tatou, E., et al., 2002. Chronic mesenteric ischemia: imaging and percutaneous treatment. Radiographics 22 (4), 863 879. Czermak, B.V., Fraedrich, G., Schocke, M.F., Seingruber, I.E., Waldenberger, P., Perkmann, R., et al., 2001. Serial CT volume measurements after endovascular aortic aneurysm repair. J. Endovasc. Ther. 8 (4), 380 389. de Jonge, C., Zandvoort, J.A., Vonken, E.P.A., Moll, F.L., van Herwaarden, J.A., 2015. Through-plane movement at multiple aortic levels on dynamic computed tomography angiography is limited in patients with an abdominal aortic aneurysm. J. Endovasc. Ther. 22 (5), 765 769. Delis, K.T., Gloviczki, P., Altuwaigri, M., McKusick, M.A., 2007. Median arcuate ligament syndrome: open coeliac artery reconstruction and ligament division after endovascular failure. J. Vasc. Surg. 46 (4), 799 802. Draney, M.T., Zarins, C.K., Taylor, C.A., 2005. Three-dimensional analysis of renal artery bending motion during respiration. J. Endovasc. Ther. 12 (3), 380 386. Erben, Y., Gloviczki, P., Kalra, M., Bjarnason, H., Reed, N.R., Duncan, A.A., et al., 2013. Treatment of nutcracker syndrome with open and endovascular interventions. J. Vasc. Surg. Venous Lymphat. Disord. 3 (4), 389 396. Giles, K.A., Pomposelli, F., Hamdan, A., Wyers, M., Jhaveri, A., Schermerhorn, M.L., et al., 2009. Decrease in total aneurysm-related deaths in the era of endovascular aneurysm repair. J. Vasc. Surg. 49 (3), 543 550. Goergen, C.J., Johnson, B.L., Greve, J.M., Taylor, C.A., Zarins, C.K., 2007. Increased anterior abdominal aortic wall motion: possible role in aneurysm pathogenesis and design of endovascular devices. J. Endovasc. Ther. 14 (4), 574 584. Grant, J., 1937. Anonymous Method of Anatomy. Williams & Wilkins, Baltimore, Md, p. 137. Hahne, J.D., Arndt, C., Herrmann, J., Schonnagel, B., Adam, G., Habermann, C.R., 2012. Follow-up of

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abdominal aortic aneurysm after endovascular aortic repair: comparison of volumetric and diametric measurement. Eur. J. Radiol. 81 (6), 1187 1191. Hansen, K.J., Wilson, D.B., Craven, T.E., Pearce, J.D., English, W.P., Edwards, M.S., et al., 2004. Mesenteric artery disease in the elderly. J. Vasc. Surg. 40 (1), 45 52. Harward, T.R., Smith, S., Seeger, J.M., 1993. Detection of celiac axis and superior mesenteric artery occlusive disease with use of abdominal duplex scanning. J. Vasc. Surg. 17 (4), 738 745. Hirsch, A.T., Haskal, Z.J., Hertzer, N.R., Bakal, C.W., Creager, M.A., Halperin, J.L., et al., 2006. ACC/AHA 2005 practice guidelines for the management of patients with peripheral arterial disease (lower extremity, renal, mesenteric, and abdominal aortic): a collaborative report from the American Association for Vascular Surgery/Society for Vascular Surgery, Society for Cardiovascular Angiography and Interventions, Society for Vascular Medicine and Biology, Society of Interventional Radiology, and the ACC/AHA Task Force on Practice Guidelines. Circulation 113 (11), 463 654. Holland, G.A., Dougherty, L., Carpenter, J.P., Golden, M. A., Gilfeather, M., Slossman, F., et al., 1996. Breath-hold ultrafast three-dimensional gadolinium-enhanced MR angiography of the aorta and the renal and other visceral abdominal arteries. Am. J. Roentgenol. 166 (4), 971 981. Hope, T.A., Markl, M., Wigstrom, L., Alley, M.T., Miller, D. C., Herfkens, R.J., 2007. Comparison of flow patterns in ascending aortic aneurysms and volunteers using fourdimensional magnetic resonance velocity mapping. J. Magn. Reson. Imaging 26 (6), 1471 1479. Houston, J.G., Gandy, S.J., Sheppard, D.G., Dick, J.B., Belch, J.J., Stonebridege, P.A., 2003. Two-dimensional flow quantitative MRI of aortic arch blood flow patterns: effect of age, sex, and presence of carotid atheromatous disease on prevalence of spiral blood flow. J. Magn. Reson. Imaging 18 (2), 169 714. Houston, J.G., Gandy, S.J., Milne, W., Dick, J.B., Belch, J.J., Stonebridge, P.A., 2004. Spiral laminar flow in the abdominal aorta: a predictor of renal impairment deterioration in patients with renal artery stenosis? Nephrol. Dial. Transplant. 19 (7), 1786 1791. Iezzi, R., Santoro, M., Dattesi, R., La Torre, M.F., Guerra, A., Antonuccio, E.G.M., et al., 2014. Post-EVAR aortic neck elongation: is a real phenomenon or a conformational change during the cardiac cycle. Eur. Rev. Med. Pharmacol. Sci. 18 (7), 975 980. Jawadi, N., Bisdas, T., Torsello, G., Stavroulakis, K., Donas, K.P., 2014. Endovascular treatment of isolated abdominal aortic dissections: long-term results. J. Endovasc. Ther. 21 (2), 324 328. Johnson, K.W., Rutherford, R.B., Tilson, M.D., Shah, D.M., Hollier, L., Stanley, J.C., 1991. Suggested standards for

reporting on arterial aneurysms. J. Vasc. Surg. 13 (3), 452 458. Jonker, F.H., Schlosser, F.J., Moll, F.L., Muhs, B.E., 2009. Dissection of the abdominal aorta. Current evidence and implications for treatment strategies: a review and meta-analysis of 92 patients. J. Endovasc. Ther. 16 (10), 71 80. Kaandrop, D.W., Vasbinder, G.B., de Haan, M.W., Kemerink, G.J., van Engelshoven, J.M., 2000. Motion of the proximal renal artery during the cardiac cycle. J. Magn. Reson. Imaging 12 (6), 924 928. Lee, J.T., Aziz, I.N., Lee, J.T., Haukoos, J.S., Donayre, C. E., Walot, I., et al., 2003. Volume regression of abdominal aortic aneurysms and its relation to successful endoluminal exclusion. J. Vasc. Surg. 38 (6), 1254 1263. Matsumoto, A.H., Tegtmeyer, C.J., Fitzcharles, E.K., Selby Jr, J.B., Tribble, C.G., Angle, J.F., et al., 1995. Percutaneous transluminal angioplasty of visceral arterial stenosis: results and long-term clinical follow-up. J. Vasc. Interv. Radiol. 6 (2), 165 174. Muhs, B.E., Teutelink, A., Prokop, M., Vincken, K.L., Moll, F.L., Verhagen, H.J.M., 2006. Endovascular aneurysm repair alters renal artery movement: a preliminary evaluation using dynamic CTA. J. Endovasc. Ther. 13 (4), 476 480. Nicoloff, A.D., Williamson, W.K., Moneta, G.L., Taylor, L. M., Porter, J.M., 1997. Duplex ultrasonography in evaluation of splanchnic artery stenosis. Surg. Clin. North Am. 77 (2), 339 355. Prinssen, M., Verhoeven, E.L., Verhagen, H.J., Blankensteijn, J.D., 2003. Decision-making in follow-up after endovascular aneurysm repair based on diameter and volume measurements: a blinded comparison. Eur. J. Vasc. Endovasc. Surg. 26 (2), 184 187. Rachev, A., Manoach, E., Berry, J., Moore Jr, J.E., 2000. A model of stress-induced geometrical remodeling of vessel segments adjacent to stents and artery/graft anastomoses. J. Theor. Biol. 206 (3), 429 443. Reed, N.R., Kaira, M., Bower, T., Vrtiska, T.J., Ricotta, J.J., Gioviczki, P., 2009. Left renal vein transposition for nutcracker syndrome. J. Vasc. Surg. 49 (2), 386 394. Roberts, C.S., Roberts, W.C., 1991. Aortic dissection with the entrance tear in the abdominal aorta. Am. Heart J. 121 (6 Pt 1), 1834 1835. Robertson, S.W., Jessup, D.B., Boero, I.J., Cheng, C.P., 2008. Right renal artery in vivo stent fracture. J. Vasc. Interv. Radiol. 19 (3), 439 442. Skeik, N., Gloviczki, P., Macedo, T.A., 2011. Posterior nutcracker syndrome. Vasc. Endovasc. Surg. 45 (8), 749 755. Suh, G.Y., Choi, G., Draney, M.T., Herfkens, R.J., Dalman, R.L., Cheng, C.P., 2013a. Respiratory-induced 3D deformations of the renal arteries quantified with geometric modeling during inspiration and expiration breath-

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holds of magnetic resonance angiography. J. Magn. Reson. Imaging. 38 (6), 1325 1332. Suh, G.-Y., Choi, G., Herfkens, R.J., Dalman, R.L., Cheng, C.P., 2013b. Respiration-induced deformations of the superior mesenteric and renal arteries in patients with abdominal aortic aneurysms. J. Vasc. Interv. Radiol. 24 (7), 1035 1042. Suh, G.Y., Choi, G., Herfkens, R.J., Dalman, R.L., Cheng, C.P., 2016. Three-dimensional modeling analysis of visceral arteries and kidneys during respiration. Ann. Vasc. Surg. 34, 250 260. Sultan, S., Hynes, N., Elsafty, N., Tawfick, W., 2013. Eight years experience in the management of median arcuate ligament syndrome by decompression, celiac ganglion sympathectomy, and selective revascularization. Vasc. Endovasc. Surg. 47 (8), 614 619. Sylvan, J., Brier, C., Wolski, K., Yanof, J., Goel, V., Kuramochi, Y., et al., 2016. Impact of alterations in target vessel curvature on branch durability after endovascular repair of thoracoabdominal aortic aneurysms. J. Vasc. Surg. 63 (3), 634 641. Szilagyi, D.E., Rian, R.L., Elliott, J.P., Smith, R.F., 1972. The celiac artery compression: does it exist? Surgery 72 (6), 849 863. Takach, T.J., Livesay, J.J., Reul Jr, G.J., Cooley, D.A., 1996. Celiac compression syndrome: tailored therapy based on intraoperative findings. J. Am. Coll. Surg. 183 (6), 606 610. ter Steege, R.W., Sloterdijk, H.S., Geelkerken, R.H., Huisman, A.B., van der Palen, J., Kolkman, J.J., 2012. Splanchnic artery stenosis and abdominal complaints: clinical history is of limited value in detection of gastrointestinal ischemia. World J. Surg. 36 (4), 793 799. Teutelink, A., Muhs, B.E., Vincken, K.L., Bartels, L.W., Cornelissen, S.A., van Herwaarden, J.A., et al., 2007. Use of dynamic computed tomography to evaluate preand postoperative aortic changes in AAA patients undergoing endovascular aneurysm repair. J. Endovasc. Ther. 14 (1), 44 49. Thomas, J.H., Blake, K., Pierce, G.E., Hermreck, A.S., Seigel, E., 1998. The clinical course of asymptomatic mesenteric arterial stenosis. J. Vasc. Surg. 27 (5), 840 844. Tran, K., Ullery, B.W., Lee, J.T., 2016. Snorkel/chimney stent morphology predicts renal dysfunction after complex endovascular aneurysm repair. Ann. Vasc. Surg. 30, 1 11. Ullery, B.W., Itoga, N.K., Mell, M.W., 2014. Transposition of the left renal vein for the treatment of nutcracker syndrome in children: a short-term experience. Ann. Vasc. Surg. 28 (8), 1938e5 8. Ullery, B.W., Suh, G.Y., Lee, J.T., Liu, B., Stineman, R., Dalman, R.L., et al., 2015. Geometry and respiratoryinduced deformation of abdominal branch vessels and

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stents after complex endovascular aneurysm repair. J. Vasc. Surg. 61 (4), 875 884. Ullery, B.W., Suh, G.Y., Lee, J.T., Liu, B., Stineman, R., Dalman, R.L., et al., 2016. Comparative geometric analysis of renal artery anatomy before and after fenestrated or snorkel/chimney endovascular aneurysm repair. J. Vasc. Surg. 63 (4), 922 929. Ullery, B.W., Suh, G.Y., Kim, J.J., Lee, J.T., Dalman, R.L., Cheng, C.P., 2017. Dynamic geometric analysis of the renal arteries and aorta following complex endovascular aneurysm repair. Ann. Vasc. Surg. 43, 85 95. van Keulen, J.W., Moll, F.L., Barwegen, G.K., Vonken, E.P., van Herwaarden, J.A., 2010a. Pulsatile distension of the proximal aneurysm neck is larger in patients with stent graft migration. Eur. J. Vasc. Endovasc. Surg. 40 (3), 326 331. van Keulen, J.W., Vincken, K.L., van Prehn, J., Tolenaar, J. L., Bartels, L.W., Viergever, M.A., et al., 2010b. The influence of different types of stent grafts on aneurysm neck dynamics after endovascular aneurysm repair. Eur. J. Vasc. Endovasc. Surg. 39 (2), 193 199. van Prehn, J., van Herwaarden, J.A., Vincken, K.L., Verhagen, H.J., Moll, F.L., Bartels, L.W., 2009. Asymmetric aortic expansion of the aneurysm neck: analysis and visualization of shape changes with electrocardiogram-gated magnetic resonance imaging. J. Vasc. Surg. 49 (6), 1395 1402. Velasquez, C.A., Saeyeldin, A., Zafar, M.A., Brownstein, A. J., Erben, Y., 2018. A systematic review on management of nutcracker syndrome. J. Vasc. Surg. Venous Lymphat. Disord. 6 (2), 271 278. Wang, X., Zhang, Y., Li, C., Zhang, H., 2012. Results of endovascular treatment for patients with nutcracker syndrome. J. Vasc. Surg. 56 (1), 142 148. Wilderman, M., Sanchez, L.A., 2009. Fenestrated grafts or debranching procedures for complex abdominal aortic aneurysms. Perspect. Vasc. Surg. Endovasc. Ther. 21 (1), 13 18. Wilson, N., Wang, K., Dutton, R.W., Taylor, C.A., 2001. A software framework for creating patient specific geometric models from medical imaging data for simulation based medical planning of vascular surgery. In: Niessen, W.J., Viergever, M.A. (Eds.), Medical Image Computing and Computer-Assisted InterventionMICCAI 2001. Lecture Notes in Computer Science, vol 2208. Springer, Berlin, Heidelberg. Wittek, A., Karatolios, K., Fritzen, C.P., Bereiter-Hahn, J., Schieffer, B., Moosdorf, R., et al., 2016. Cyclic threedimensional wall motion of the human ascending and abdominal aorta characterized by time-resolved threedimensional ultrasound speckle tracking. Biomech. Model. Mechanobiol. 15 (5), 1375 1388. Wu, Z., Zheng, X., He, Y., Fang, X., Li, D., Tian, L., et al., 2016. Stent migration after endovascular stenting in patients with nutcracker syndrome. J. Vasc. Surg. Venous Lymphat. Disord. 4 (2), 193 199.

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C H A P T E R

10

Lower Extremity Arteries Christopher P. Cheng Division of Vascular Surgery, Stanford University, Stanford, CA, United States

This is where it all began. It was in the lower extremities, specifically the superficial femoral artery, that a substantial incidence of stent fractures was first noticed in the early 2000s. Subsequent investigation revealed that stent fractures had a lot to do with vascular deformations induced by hip and knee flexion, which most people are partial to doing. In fact, the primary purpose of nearly all lower extremity vascular interventions is to restore blood flow and improve mobility. The fact that the first generation of lower extremity arterial stents were not specifically designed for mobile arteries is analogous to creating a tire patch for mending a blown tire even though the tire patch is unable to survive the rigor of the tire rolling on the ground. In this chapter, we will cover the anatomy and deformations of the iliac, femoropopliteal, and tibial arteries caused by cardiac pulsatility, musculoskeletal motion, as well as external influences.

Handbook of Vascular Motion DOI: https://doi.org/10.1016/B978-0-12-815713-8.00010-3

ILIAC ARTERY Anatomy The abdominal aorta bifurcates into the right and left common iliac arteries approximately at the level of the navel and fourth lumbar vertebra (Fig. 10.1). The iliac arteries are anterior to the iliac veins. In adults, the common iliac arteries are approximately 4 5 cm long with the right common iliac being slightly longer because the aorta is on the left side of the spine. The common iliac arteries bifurcate into the internal and external iliac arteries at the level of the sacroiliac joint and also give rise to smaller branches including the peritoneum, psoas major, and ureter arteries. The internal iliac arteries supply blood to the pelvic organs and the musculature of the hip and lower back. The external iliac arteries generally have larger diameters than the internal iliac arteries and travel inferiorly along the medial side of the psoas major muscle,

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FIGURE 10.1 Computed tomography arteriogram of the abdominal aorta bifurcating into the iliac arteries (left), and diagram of the left common iliac artery bifurcating into the internal and external iliac arteries (right). From commons.wikimedia.org (left) and adapted from Borley, N.R., 2008. Abdomen and pelvis. In: Standring, S. (Ed.), Gray’s Anatomy, Chapter 62, pp. 1083 1097, Churchill Livingstone/Elsevier, Edinburgh, UK (right).

eventually turning into the common femoral arteries after passing the inguinal ligament. The most dramatic musculoskeletal-induced motions concerning the iliac arteries are related to hip movement. Hip flexion is accomplished by contraction of the several muscle groups, including the iliopsoas (psoas major and iliacus), anterior compartment of the thigh (rectus femoris and sartorius), gluteal muscles (tensor fasciae latae), and medial compartment of the thigh (pectineus, adductor longus, adductor brevis, and gracilis) (Fig. 10.2). The iliopsoas group originates from the lumbar spine and various parts of the ilium and inserts into the lesser trochanter of the femur; the anterior compartment group originates from the anterior superior and inferior iliac spines and inserts into the patella and tibia; the tensor fasciae latae originates at the iliac crest and inserts into the iliotibial tract which attaches to the lateral condyle of the tibia; the medial compartment group originates from the pubis bone and inserts into various ridges and protuberances on the femur and tibia. Courses in anatomy, Greek, and Latin are needed for full comprehension of that last

FIGURE 10.2 Musculature involved with hip flexion, adduction, and abduction. From https://en.wikipedia.org/wiki/ List_of_flexors_of_the_human_body#/media/File:Anterior_Hip_ Muscles_2.PNG.

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ILIAC ARTERY

sentence, which is, luckily, not critical for our purposes. These muscles, as well as a few others, are also responsible for hip adduction and abduction, while the posterior compartment of the thigh is responsible for hip extension.

Motion From Pulsatility Pulsatile flow can cause dramatic crosssectional deformation in the iliac arteries. In patients with abdominal aortic aneurysms, aged 60 85 years, cardiac-gated computed tomography angiography and image processing were used to quantify maximum cross-sectional deformation of the iliac arteries due to pulsatile flow (van Keulen et al., 2011). Measurements were performed at the common iliac arteries at three locations: (1) 0.5 mm distal to the aortic bifurcation, (2) in the middle of the common iliac artery, and (3) 0.5 mm proximal to the iliac bifurcation. The maximum diametric and crosssectional area changes are shown in Table 10.1. These data imply that the right and left common iliac arteries essentially exhibit the same amount of cross-sectional deformation in patients with abdominal aortic aneurysm disease. The relative amount of pulsatile deformation appears to decrease from proximal to distal, which is consistent with the trend of

decreasing arterial elastin content traveling distally in the body. Note, however, the variation in pulsatile deformation along the length of the common iliac is only on the order of 0.1 0.2 mm in diameter, which may be below the measurement error. Pulsatile flow can also cause translational movement of the iliac arteries. This is demonstrated in a case study of a patient with endovascular aortic repair of an abdominal aortic aneurysm followed for 5 years (van Keulen et al., 2010). Two years after the initial endovascular aortic repair, distal migration of the right iliac limb device was observed, finally resulting in a complete limb graft dislocation and type III endoleak at 3 years (Fig. 10.3). Cardiac-gated computed tomography revealed that the aortic graft and iliac arteries were translating approximately 3 mm with every heartbeat. At this point, the endoleak was treated endovascularly with an interposition graft to reconnect the main aorta endograft and the right iliac limb device. While this was initially successful, distal migration was again noted at 4 years, and eventually there was recurrent dislocation and type III endoleak at 5 years. For illustrative animations regarding this case, see Movies 1 and 2 from this paper: http://journals.sagepub.com.laneproxy. stanford.edu/doi/suppl/10.1583/10-3058.1

TABLE 10.1 Maximum Pulsatile Cross-Sectional Iliac Artery Deformations in AAA Patients Right CIA

Left CIA

Both CIAs

MAXIMUM AVERAGE DIAMETER CHANGE IN MM [%] Level A

1.2 6 0.4 [9.2 6 1.9]

1.1 6 0.3 [9.1 6 2.3]

1.1 6 0.4 [9.2 6 2.1]

Level B

1.0 6 0.2 [8.1 6 1.7]

1.1 6 0.2 [8.9 6 2.3]

1.0 6 0.2 [8.5 6 2.0]

Level C

1.0 6 0.3 [8.2 6 1.8]

1.0 6 0.2 [7.9 6 1.9]

1.0 6 0.2 [8.1 6 1.8]

2

MAXIMUM CROSS-SECTIONAL AREA CHANGE IN MM [%] Level A

18 6 13 [12.9 6 5.2]

14 6 6 [12.0 6 5.6]

16 6 11 [12.5 6 5.4]

Level B

13 6 5 [10.8 6 3.5]

14 6 5 [11.5 6 4.7]

13 6 5 [11.2 6 4.2]

Level C

13 6 6 [10.4 6 4.1]

12 6 5 [8.7 6 3.8]

13 6 6 [9.6 6 4.0]

Data are shown as mean 6 standard deviation. AAA, Abdominal aortic aneurysm; CIA, common iliac artery. Level A—0.5 mm distal to aortic bifurcation, Level B—middle of CIA, Level C—0.5 mm proximal to iliac bifurcation.

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FIGURE 10.3 Distal migration of a right iliac limb device after the endovascular aortic repair was suspected due to pulsatile forces and motion. Immediately after endovascular repair, the right iliac limb was overlapped with the main graft gate by 20 mm (left). After 2 years, the overlap was ,14 mm (middle), and by 3 years, it was completely disconnected (right). From van Keulen, J.W., van Prehn, J., Moll, F.L., van Herwaarden, J.A., 2010. Recurrent stent-graft disintegration caused by cardiac-induced aortoiliac movements. J. Endovasc. Ther. 17 (3), 354 355, Figure.

FIGURE 10.4 Vector displacement map of an iliac stent graft in an in vitro pulsatile flow model. The middle of the stent graft moves approximately 0.3 mm with a pulse pressure of 195/ 100 mmHg with 90 degrees graft angulation, indicating pulsatile bending deformation. From Roos, H., Ghaffari, M., Falkenberg, M., Chernoray, V., Jeppsson, A., Nilsson, H., 2014. Displacement forces in ilian zones and stent graft interconnections in endovascular aortic repair: an experimental study. Eur. J. Vasc. Endovasc. Surg. 47 (3), 262 267, Figure 5.

These results are experimentally corroborated by an in vitro study investigating the forces and movement of an iliac stent graft in a pulsatile flow model at various fluid pressures, stent graft angulations, and stroke frequencies (Roos et al., 2014). While stroke frequency did not affect the pulsatile forces and graft movements, increasing fluid pressures and graft angulation significantly increased both forces and movements. The flow-induced displacement forces increased 25-fold from a pulse

pressure of 145/80 mmHg with zero graft angulation to a pulse pressure of 195/ 100 mmHg with 90 degrees angulation. The graft movement was also highest at a pulse pressure of 195/100 mmHg with 90 degrees angulation, with approximately 0.3 mm translation at the middle of the graft with every pulse (Fig. 10.4). Since the ends of the iliac stent graft were fixed, the translation of the middle of the graft indicates pulsatile bending deformation.

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Motion From Musculoskeletal Movement A number of studies have investigated the impact of hip flexion on iliac artery motion and deformation. In one study, a group of 70 patients, aged 26 75 years, was recruited consecutively and catheterized from the femoral arteries for a myriad of diagnostic and therapeutic reasons (Park et al., 2005). During each procedure, a marked catheter (with 1 cm between markings) was inserted into one femoral artery and advanced to the contralateral side where the markings could be used to measure the location of the bending point of the iliofemoral artery during hip flexion (Fig. 10.5). With approximately 90 degrees hip flexion, the peak bending point was at the external iliac artery and was located 42.8 6 28.6 mm proximal to the acetabular roof and 35.1 6 30.1 mm proximal to the inguinal ligament. Interestingly, there was a strong correlation between the location of the bending point and the patient’s age, with the bending point moving progressively more cranial with increased age.

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In a subsequent study, the marked catheter paths from these same patients were reconstructed in three dimensions by projecting the two orthogonal two-dimensional (2D) lateral and coronal X-ray images into threedimensional (3D) space, and curvatures were calculated to quantify the magnitude of bending (Cao and Cheng, 2007). The minimum radius of curvature decreased from 4.5 6 2.2 to 2.6 6 1.0 cm (P , .001) when the hip moved from straight to 85 6 18 degrees flexion, and the bending point shifted distally from 8.6 6 1.8 to 10.3 6 2.0 cm (P , .001) distal to the aortic bifurcation (Fig. 10.6). Note that in the previous two studies, geometric information was derived from the in situ marked catheters in the iliac artery, rather than tracking the arteries themselves. Choi et al. (2009) performed gadolinium-enhanced 3D magnetic resonance angiography of healthy subjects, aged 34 6 11 years old, in the supine and fetal (maximum hip and knee flexion) positions, and quantified deformation of the abdominal aorta and iliac arteries. From supine

FIGURE 10.5 Calculation of the bending point location on the iliac artery during hip flexion. This patient had right femoral artery access and a marked catheter was advanced into the left iliofemoral artery. Bending of the iliac artery can be seen from the lateral view when moving the hip from a straight position to approximately 90 degrees flexion, and the bending point is selected as shown (left). The angle formed by two lines, one each parallel to the catheter above and below the bending point, is bisected and the intersection of the bisecting line and the catheter is selected as the bending point (left, black arrow). Then, from coronal views of the hip flexed position, the bending point (as referenced to the catheter markings) is measured in distance from the acetabular roof and the inguinal ligament (right). Adapted from Park, S.I., Won, J.H., Kim, B.M., Kim, J.K., Lee, D.Y., 2005. The arterial folding point during flexion of the hip joint. Cardiovasc. Interv. Radiol. 28 (2), 173 177, Figure 1.

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FIGURE 10.6 Depiction of increased curvature and distal shifting of the iliac bending point when the hip moves from the straight position to approximately 90 degrees flexion. From Cao, E., Cheng, C.P., 2007. In vivo 3D deformations of the human iliac artery due to hip flexion. In: 2007 Transcatheter Cardiovascular Therapeutics Conference, Abstract #587.

FIGURE 10.7 Magnetic resonance angiography of a subject moving from supine to the fetal position (left) and accompanying geometric models demonstrating the iliac arteries curving upward with hip flexion (right). Adapted from Choi, G., Suh, G., Shin, L.K., Taylor, C.A., Cheng, C.P., 2009. In vivo deformation of the human abdominal aorta and common iliac arteries with hip and knee flexion: implications for the design of stent-grafts. J. Endovasc. Ther. 16 (5), 531 538, Figures 1 and 5.

to the fetal position, the iliac arteries expectedly curved upward (Fig. 10.7). The common iliac arteries shortened from supine (4.48 6 1.27 cm) to fetal (4.26 6 1.25 cm) position by 5.2 6 4.6% (P , 0.05) and twisted 4.5 6 2.7 degree/cm in magnitude (P , 0.05) (Choi et al., 2009). Curvature was calculated at

every point of the iliac artery centerline path as the inverse of the radius of a circumscribed circle fit to the centerline (Fig. 10.8). Mean curvature of the common iliac arteries increased from supine (0.19 6 0.06 cm21) to fetal (0.34 6 0.10 cm21) position by 0.15 6 0.07 cm21 (P , 0.001), representing an increase of

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FIGURE 10.9 The angle between the right and left common iliac arteries increases from proximal to distal, and the increase is more dramatic in the fetal as compared to the supine position (top). This translates to an increasing change in angle between the two arteries in more distal locations, which means the right and left common iliac arteries curve away from each other with hip flexion (bottom). Adapted from Choi, G., Suh, G., Shin, L.K., Taylor, C.A., Cheng, C.P., 2009. In vivo deformation of the human abdominal aorta and common iliac arteries with hip and knee flexion: implications for the design of stent-grafts. J. Endovasc. Ther. 16 (5), 531 538, Figure 8.

FIGURE 10.8 Example illustration of curvature calculation along the iliac artery centerlines, using fitted circles to compute curvature (inverse of the radius of fitted circles) (top row), and the variation in curvature along the iliac artery centerline paths (bottom row). The maximum curvature (and hence minimum circle radius) locations are shown for the supine (left column) and fetal (right column) positions using green circles (top images) and black arrowheads (bottom graphs) for the left and right iliac arteries. Adapted from Choi, G., Suh, G., Shin, L.K., Taylor, C.A., Cheng, C.P., 2009. In vivo deformation of the human abdominal aorta and common iliac arteries with hip and knee flexion: implications for the design of stent-grafts. J. Endovasc. Ther. 16 (5), 531 538, Figure 6.

85 6 44%. Maximum local curvature increased from supine (0.38 6 0.13 cm21) to fetal (0.69 6 0.22 cm21) position, representing an increase of approximately 80%. Note that the maximum curvature is approximately double

that of the mean curvature for the entire length of the common iliac arteries in each of the body positions. Furthermore, the data demonstrate that the right and left iliac arteries curve away laterally from each other during hip flexion, as evidenced by the increasing angle change between them moving in the distal direction (Fig. 10.9). Some of the preceding iliac deformation data, measured in vivo, are corroborated by experimental data. First, in a cadaver study, the external iliac artery was observed to exhibit cranial displacement during hip flexion (Kim et al., 2010). In addition, Young et al. (2012) performed simulations of lower extremity joint motion associated with walking, stair climbing, and standing up from a seated position using a graphics-based anatomic and kinematic model.

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Healthy adults aged 23 69 years were analyzed with an eight-camera video motion capture system, and inverse kinematic simulations were performed to calculate hip and knee joint angles during the aforementioned activities. Next, forward kinematic simulations were performed to quantify length changes of the iliac and femoropopliteal arteries in combination with arterial branch markers (Fig. 10.10). In the iliac artery, the motions of walking, stair climbing, and sitting to standing were associated with maximum arclength shortening of 5.6 6 1.0%, 12.8 6 2.0%, and 16.0 6 1.9%, respectively. Also during these motions, the maximum arclength elongations observed were 4.6 6 1.5%, 3.6 6 1.7%, and 1.4 6 1.6%, respectively. Note that these simulated axial length changes are likely to be on the upper bound of actual deformations since they assume that the arteries never exceed the point of slack and kink due to redundant length. Since hip motion appears to cause iliac artery deformation, it stands to reason that extreme hip position or excessive motion could cause overuse arterial disease. In fact, this is observed in elite-level athletes. In a large

systematic review of the literature, endofibrosis and iliac artery kinking were found in competitive cyclists, speed skaters, endurance runners, triathletes, rugby players, soccer players, and cross-country skiers (Peach et al., 2012). These pathologies were all associated with extreme hip flexion and extremely high repetitions (Bender et al., 2004).

Motion From External Influences External influences have also been implicated in iliac artery deformations. In a case study, a patient experienced repeat occlusion of the iliac artery which was accompanied by stent compression and recurrent intermittent claudication symptoms (Ihara et al., 2015). The patient was using a powerful massage machine to alleviate his spondylotic back pain, and it was suspected that the massage, in combination with the protruding hyperstatic lumbar vertebral body, caused the recurring stent compression and deformation (Fig. 10.11). There has also been some investigation on the impact of intravascular device insertion into the iliac arteries. Most interventional

FIGURE 10.10

Anatomic and kinematic modeling of the lower extremity musculoskeletal system with the iliac and femoropopliteal arteries (left), combined with simulation of hip and knee joint motion based on in vivo human motion capture (right), produce estimations of arterial length change. Adapted from Young, M.D., Streicher, M.C., Beck, R.J., van den Bogert, A.J., Tajaddini, A., Davis, B.L., 2012. Simulation of lower limb axial arterial length change during locomotion. J. Biomech. 45 (8), 1485 1490, Figure 1.

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FIGURE 10.11 Computed tomography showing common iliac artery stent compression in an axial view (left), and probable compression from a protruding hyperstatic lumbar vertebral body from oblique lateral views (right). Adapted from Ihara, M., Ueno, A., Tsuda, Y., Takahashi, H., Yamazaki, T., Kudo, M., et al., 2015. A case of repeated occlusion in the common iliac artery due to an unexpected stent deformation. Cardiovasc. Interv. Ther. 30 (2), 162 167, Figure 2.

FIGURE 10.12 The centerline of an endovascular aorta repair delivery system is estimated from combining two 2D fluoroscopy views (left, middle). This delivery system centerline (light purple line) was then compared to a co-registered pre-operative 3D computed tomography image of the abdominal aorta and iliac arteries (right). The iliac artery is dramatically straightened with the added stiffness of a guidewire and delivery system. From Kauffmann, C., Douane, F., Therasse, E., Lessard, S., Elkouri, S., Gilbert, P., et al., 2015. Source of errors and accuracy of a two-dimensional/three-dimensional fusion road map for endovascular aneurysm repair of abdominal aortic aneurysm. J. Vasc. Interv. Radiol. 26 (4), 544 551, Figure 2.

arterial procedures are performed via femoral artery access, and the guidewires and catheters inserted through the femoral arteries invariably deform the iliac arteries. This is an important topic because sometimes minimally invasive procedures utilize previous computed tomography or fluoroscopy images as roadmaps to help with spatial orientation in an effort to reduce the use of contrast and radiation during the procedure. If these images, taken preoperatively or in the catheterization lab prior to device insertion, are

used for procedure guidance, and the vasculature is in fact translated or deformed after device insertion, then the pre-insertion images may be inaccurate and lead to malpositioning of the device. For example, there was a study about the effect of stiff guidewire and delivery system insertion of an endovascular aortic repair device on iliac artery motion in patients aged 66 85 years (Fig. 10.12) (Kauffmann et al., 2015). Compared to the native iliac arteries, the internal iliac artery ostia shifted by 5.6 6 2.0

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and 4.3 6 3.0 mm in the x- and z-axes for the ipsilateral iliac artery (side of main endograft insertion), respectively, and 6.1 6 3.3 and 5.5 6 4.2 mm in the x- and z-axes for the contralateral iliac artery, respectively. However, the maximum measured iliac artery centerline translation was 38.3 6 15.6 mm (range 5 13 61 mm). This much higher maximum centerline translation as compared to ostia translation demonstrates that the iliac artery can be dramatically deformed with the added stiffness of guidewires and device delivery systems, and that the iliac bifurcation point is relatively fixed compared to other parts of the iliac artery.

FEMOROPOPLITEAL ARTERY Anatomy The external iliac artery becomes the common femoral artery as it passes the inguinal ligament (Fig. 10.13). The common femoral artery bifurcates into the superficial femoral artery (SFA) medially and the profunda femoris branches laterally usually slightly below and posterior to the inguinal ligament. Approximately 15 cm inferior to the femoral bifurcation and inguinal ligament, the adductor canal begins, which is delineated laterally by the vastus medialis muscle, posteromedially by the adductor longus and adductor

FIGURE 10.13 Anatomy of the femoropopliteal artery and its branches. From https://en.wikipedia.org/wiki/ Pudendal_arteries#/media/File:Thigh_arteries_schema.svg.

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magnus muscles, and anteriorly by the sartorius muscle that crosses inferior obliquely from lateral to medial. The adductor canal ends at the adductor hiatus in the tendon of the adductor magnus muscle, is approximately 15 cm in length, and contains the SFA, femoral vein, and saphenous nerve. The SFA and femoral vein exit the adductor canal at the adductor hiatus. As the SFA leaves the adductor canal through the adductor hiatus, it passes posterior-medially of the femur and behind the knee into the popliteal fossa. At this point, the artery becomes the popliteal artery. Along the length of the SFA, variable numbers of small muscle branches help feed the adjacent musculature. The genicular arteries provide blood supply to the knee, with the descending genicular artery (the most

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superior geniculate) bifurcating from the SFA just superior to the adductor hiatus. The descending genicular artery bifurcates into the saphenous (medially dives with saphenous nerve and vein into sartorius) and articular (laterally dives into vastus medialis) branches. Further down the popliteal artery at the level of the knee, the other genicular arteries (superior lateral, superior medial, middle, inferior lateral, and inferior medial) branch off. The muscles responsible for knee flexion include the biceps femoris, gastrocnemius, sartorius, semimembranosus, and semitendinosus (Fig. 10.14). The hamstring group (biceps femoris, semimembranosus, and semitendinosus) run in the superior inferior direction and are in the posterior portion of the thigh. They FIGURE 10.14 Posterior (left) and anterior (right) muscles of the thigh. In general, the posterior thigh muscles are responsible for knee flexion (e.g., the long head of biceps femoris in red), and the anterior muscles are responsible for knee extension. From commons. wikimedia.org, originally from Gray 1918, Anatomy of the Human Body.

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originate from the ischial tuberosity and insert into the tibial or fibula. Sartorius is in the front of the thigh, originates from the anterior superior iliac spine, travels obliquely in the inferiormedial direction, and joins the tendons of the gracilis and semitendinosus muscles before inserting into the tibia. Gastrocnemius is the posterior muscle in the calf, whose two heads originate from the medial and lateral condyles of the femur and forms into the Achilles tendon which inserts into the heel bone. The muscles responsible for knee extension include the rectus femoris, vastus intermedius, vastus lateralis, vastus medialis, and tensor vastus intermedius (Fig. 10.14). The quadriceps femoris is a large muscle group in the anterior portion of the thigh that includes the four muscles rectus femoris, vastus intermedius, vastus lateralis, and vastus medialis. The rectus femoris originates at the ilium while the vasti

muscles originate from the body of the femur, and they all converge into the quadriceps tendon before attaching to the patella and inserting in the tuberosity of the tibia. The fifth knee extensor is the tensor vastus intermedius, which runs between the vastus intermedius and vastus lateralis, originates at the greater trochanter, and joins the quadriceps tendon before inserting into the patella. Interestingly, this muscle was only confirmed in recent cadaver studies published in 2016 (Grob et al., 2016). This shows that there are still basic discoveries to be made in human anatomy.

Motion from Pulsatility There have been a large number of studies that have quantified the diametric deformation of the femoral arteries due to cardiac pulsatility. Table 10.2 summarizes the data from

TABLE 10.2 Femoral Artery Pulsatile Diametric Deformations Study

Population

Pulse Pressure (mmHg)

Diametric Distention

Hansen et al. (1993)

Healthy, 39 (range 18 70) years

46 6 12

4.0 6 1.3%

Kawasaki et al. (1987)

Healthy 0 19 years

45

7 6 3%

20 39 years

48

6 6 2%

40 59 years

48

5 6 1%

$ 60 years

51

4 6 1%

,35 years

44 6 10

2.6 6 0.1

35 60 years

45 6 14

1.9 6 0.1

.60 years

54 6 23

1.7 6 0.1

Willekes et al. (1998)

Healthy women, 18 35 years

47 6 6

3.4 6 2.0%

Benetos et al. (1993)

Healthy/hypertensive, 47 6 6 years

62.5 6 2.5

3.5 6 0.2%

Henry et al. (2003)

Healthy/hypertensive, 68.7 6 6.1 years

68 6 17

2.4 6 0.7%

Henry et al. (2003)

Impaired glucose metabolism, 70.3 6 6.3 years

70 6 16

1.7 6 0.6%

Henry et al. (2003)

Type 2 diabetic, 67.3 6 8.1 years

74 6 18

1.9 6 0.7%

Mozersky et al. (1972)

Healthy

Data are shown as mean 6 standard deviation.

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several representative studies (Table 10.2). Note that these studies report pulse pressure and diametric distension for common femoral arteries; no literature data were found specifically regarding pulse pressure or diametric distension in the SFA or popliteal artery. However, the SFA and popliteal arteries should experience relatively similar pulsatile diametric deformation compared to the common femoral artery. These studies include healthy volunteers and patients who have risk factors related to cardiovascular disease, and all use similar ultrasound imaging methods to quantify vessel diameter. In studies conducted on healthy volunteers, common femoral artery diametric deformation ranged from approximately 2% to 7%, depending on age group and publication (Table 10.2). Hansen et al. (1993) reported a 4.0 6 1.3% diametric distension in subjects aged 39 years old (range 18 70), with a corresponding pulse pressure of 46 6 12 mmHg. Kawasaki et al. (1987) investigated the effect of age on femoral artery distensibility and found that increasing age correlated with lower pulsatile deformation, with 7 6 3% diametric distension for subjects aged 0 19 years decreasing down to 4 6 1% diametric distension for subjects aged $ 60 years. A similar trend was found by Mozersky et al. (1972); however, the distension values were uniformly lower, with diametric deformations of 2.6 6 0.1% and 1.7 6 0.1% for the age groups ,35 and .60 years, respectively. Willekes et al. (1998) studied healthy female adults only (aged 18 35 years) and measured 3.4 6 2.0% diametric distension with 47 6 6 mmHg pulse pressure. For studies that also included patients with cardiovascular disease, the subjects were generally older and the diametric deformations were generally lower (Table 10.2). For example, Benetos et al. (1993) reported on a mix of healthy and hypertensive subjects aged 47 6 6 years and found that the common femoral artery exhibited 3.5 6 0.2%

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diametric distension with 62.5 6 2.5 mmHg pulse pressure. Henry et al. (2003) investigated a similar mixed group of healthy and hypertensive subjects, although 20 years older at 68.7 6 6.1 years, and reported 2.4 6 0.7% diametric distension with 68 6 17 mmHg pulse pressure. The same study also measured the diametric distension of the femoral artery in patients with impaired glucose metabolism and those with type 2 diabetes, and found that diametric distension was lower at 1.7 6 0.6% and 1.9 6 0.7%, respectively. Recall from Chapter 2, Deciding What Vascular Motions You Need, that pulsatile flow can cause non-radial deformations as well. While these have not been described for the femoropopliteal artery in the literature yet, note that a curved or bent artery can experience cyclic straightening/bending when subjected to pulsatile flow and that an artery undergoing significant diametric expansion may experience concomitant axial deformations.

Native Artery Deformations from Musculoskeletal Movement Logically, it makes sense that hip and knee joint motion contribute to the deformation of the femoropopliteal artery, which spans the length of the thigh. While as recently as the early 2000s it was not known what hip and knee flexion would do to the femoropopliteal artery, it has now been very well described in numerous studies. The following table summarizes the most relevant studies about deformation of native, unstented femoropopliteal arteries due to musculoskeletal motion (Table 10.3). Cheng et al. (2006) used gadoliniumenhanced magnetic resonance angiography to investigate the centerline deformations of the native SFA due to extreme hip and knee flexion. In this study, healthy adults aged 27 6 10 years were scanned in the supine position (no hip and knee flexion) and again in the fetal

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TABLE 10.3

Axial Length, Curvature, and Axial Twist Metrics of the Native Femoropopliteal Artery With Hip and Knee Flexion Anatomic Location

Axial Shortening (%)

Straight Leg Curvature (cm21)

Bent Leg Curvature (cm21)

Axial Twist ( /cm)

120 6 9 hip 134 6 3 knee

SFA

13 6 11

N/A

N/A

2.8 6 1.7

39 6 6 hip 86 6 6 knee

Prox SFA

5.9 6 3.0

0.11 6 0.05Max

0.21 6 0.07Max

1.3 6 0.8

Mid SFA

6.7 6 2.1

0.08 6 0.01

0.14 6 0.06

1.8 6 1.1

Dist SFA

8.1 6 2.0

0.11 6 0.06

0.47 6 0.24

2.1 6 1.3

All SFA

6.9 6 1.9

0.14 6 0.06

0.47 6 0.24

1.7 6 1.1

SFA

6.1 6 4.5

0.08 6 0.02

0.11 6 0.03

1.7 6 1.0

PA

15.8 6 6.0

0.10 6 0.02

0.31 6 0.10

3.5 6 1.9

SFA/PA

10.0 6 2.6

0.09 6 0.02

0.20 6 0.06

N/A

PA

5.9 6 2.5

0.06 6 0.02,

0.12 6 0.07,

3.8 6 2.2

0.12 6 0.04

0.24 6 0.09

N/A

0.50Max

Population and Condition

Flexion Angles

Cheng et al. (2006)

Healthy subjects, 27 6 10 years, Native

Cheng et al. (2010)

Healthy subjects, 56 6 5 years, Native

Study

Klein et al. (2009)

Gokgol et al. (2013)

*MacTaggart et al. (2014)

*Poulson et al. (2018)

*Poulson et al. (2018)

*Poulson et al. (2018)

Leg PAD, 57 6 10 years, Native

Leg PAD, 69 (56 79) years, Native Cadaver, Native

Cadaver, Native

Cadaver, Native

Cadaver, Native



B45 hip B120 knee



20 hip 70 knee 

37 6 3 hip 108 6 2 knee



70 knee

90 knee

120 knee

Max Max Max

Max

Prox SFA

767

Dist SFA

19 6 10

PA

30 6 8

SFA/PA

12 6 11

Prox SFA

9.3

Max Max Max

Max

066

Max

28 6 9

Max

77 6 27

1.00 1.67

4 6 16

Max

1.67 N/A

0.37, 0.42

Max Max

Dist SFA

10.6

0.53, 0.56

PA

13.3

0.59, 0.91Max

Prox SFA

12.5

N/A

0.43, 0.53Max

N/A

Max

Dist SFA

13.7

0.83, 0.91

PA

17.3

0.91, 1.43Max

Prox SFA

15.2

N/A

N/A

0.48, 0.59Max

N/A

Max

Dist SFA

18.5

1.11, 1.43

PA

25.1

1.25, 2.00Max

Data are shown as mean or mean 6 standard deviation. SFA, superficial femoral artery; PA, popliteal artery; Prox, proximal; Mid, middle; Dist, Distal; PAD, peripheral artery disease; Max, local maximum curvature. * Curvature values converted from radius of curvature values in the publication.

FEMOROPOPLITEAL ARTERY

position (86 6 6 degrees hip flexion and 120 6 9 degrees knee flexion). The subjects had to be relatively small (height 5 164 6 7 cm, weight 5 59 6 10 kg) and flexible to fit into the bore of the MRI in the fetal position. Let us call this the “young adult” group (also known as graduate students). From these volumetric scans, centerline paths of the iliofemoropopliteal arteries were identified, along with the profunda femoris and descending genicular arteries (Fig. 10.15). The segment of the artery between the profunda and descending genicular was considered the SFA and was used for analysis. With hip and knee flexion, the SFA arclength shortened by 13 6 11% and twisted by 2.8 6 1.7 degree/cm. For this population, the SFA was very straight for both supine and fetal positions, indicating that it did not curve appreciably even with extreme hip and knee flexion. Even though there is substantial variation in anatomy between subjects including artery lengths, branch locations, and muscular geometry, some interesting trends arose from this study (Cheng et al., 2006). The fact that there is

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consistent SFA shortening with hip and knee flexion was itself a non-obvious finding at the time. There are more than a dozen muscles that control hip and knee motion, and their interactions are complex. In fact, upon consultations with prominent surgeons, radiologists, and anatomists, there was disagreement about whether the SFA would shorten, lengthen, or stay the same length with hip and knee flexion. As an example of this complexity, the SFA is mostly contained in the adductor canal, formed laterally by vastus medialis, posteromedially by adductor longus and adductor magnus, and anteriorly by sartorius. Hip flexion is expected to shorten the vastus medialis muscle while knee flexion lengthens it; however, both hip and knee flexion shorten the sartorius muscle. This means that it is unclear how these two muscles, which act very differently for the same motion, will load the SFA during hip and knee flexion. However, taking a step back from the complex musculature of the adductor canal and the rest of the thigh, and just noting that the iliofemoral artery is anterior to the hip joint, and that the popliteal artery dives

FIGURE 10.15 Gadolinium-enhanced magnetic resonance angiography (left) was used to isolate the lower extremity arteries (middle) and digitize the centerline paths of the iliofemoropopliteal arteries and the profunda femoris and descending genicular artery branches (right). From Cheng, C.P., Wilson, N.M., Hallett, R.L., Herfkens, R.J., Taylor, C.A., 2006. In vivo MR angiographic quantification of axial and twisting deformations of the superficial femoral artery resulting from maximum hip and knee flexion, J. Vasc. Interv. Radiol. 17, 979 987, Figure 1.

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FIGURE 10.16 The iliofemoral artery is anterior to the hip joint and the femoropopliteal artery dives posterior to the femur until it tucks between the femoral condyles behind the knee. Thus, it makes sense that hip and knee flexion cause femoropopliteal artery shortening from the superior and inferior aspects, respectively. Adapted from MacTaggart, J.N., Phillips, N.Y., Lomneth, C.S., Pipinos, I.I., Bowen, R., Baxter, B.T., et al., 2014. Three-dimensional bending, torsion and axial compression of the femoropopliteal artery during limb flexion. J. Biomech. 47, 2249 2256, Figure 2.

posterior to the femur and tucks behind the knee, tells us that both hip and knee flexion should shorten both the proximal and distal regions of the SFA, respectively (Fig. 10.16). This seems so obvious that the controversy among experts in the early 2000s seems utterly silly now. But hindsight is 20/20. At the time, axial twist of the SFA due to hip and knee flexion was a completely unexpected finding since hip and knee flexion happens largely within the sagittal plane (Cheng et al., 2006). However, considering the complexity of musculature and oblique angles in which the muscles act, torsional forces on the SFA seem entirely possible. For example, the descending genicular artery bifurcates and inserts into vastus medialis via its articular branch and into sartorius via its saphenous branch. While vastus medialis runs in the superior inferior direction, it has a very oblique pennation angle, and sartorius itself runs at an oblique angle. Thus, with these oblique forces on an artery branch at the distal end of

the SFA, axial twist could result. It was also discovered that the left SFA tends to twist in the counter-clockwise direction, while the right SFA tends to twist in the clockwise direction. It is possible that the articular branch of the descending genicular artery, which is pulled laterally by vastus medialis during knee flexion, would cause an external rotational force on the inferior portion of the SFA, hence the tendency for counter-clockwise twisting of the left SFA and clockwise twisting of the right SFA. Note again that since arterial branching and insertion into muscles are so highly variable between people, the forces on the SFA can vary widely. In a similar subsequent study, Cheng et al. (2010) reported on an older population of subjects (56 6 5 years), also with no history of peripheral artery disease. However, due to the older subjects being larger (height 5 178 6 9 cm, weight 5 87 6 9 kg) and less flexible than the younger subjects from the previous study, they were scanned in the supine position and with their hip and knee flexed as much as possible while still fitting in the bore of the MRI (39 6 6 degrees hip flexion and 86 6 6 degrees knee flexion). Let us call this the “distinguished adult” group (also known as professors and industry executives). Additional small muscular branch arteries were identified between the profunda femoris and descending genicular arteries, enabling resolution of deformation variation along the length of the SFA. The axial shortening of the proximal, middle, and distal thirds of the SFA was 5.9 6 3.0%, 6.7 6 2.1%, and 8.1 6 2.0%, respectively, with an average shortening of 6.9 6 1.9%. The axial twist of the proximal, middle, and distal thirds of the SFA was 1.3 6 0.8, 1.8 6 1.1, and 2.1 6 1.3 degree/cm, respectively, with an average axial twist of 1.7 6 1.1 degree/cm. In the supine position, the maximum curvature of the proximal, middle, and distal thirds of the SFA was 0.11 6 0.05, 0.08 6 0.01, and 0.11 6 0.06 cm21, respectively,

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while in the flexed position it was 0.21 6 0.07, 0.14 6 0.06, and 0.47 6 0.24 cm21, respectively. Compared to the young adults, the distinguished adults exhibited less axial shortening and axial twist; however, this could partially be due to the lesser degrees of hip and knee flexion (Cheng et al., 2010). But this is not the whole story. One striking observation was the visual difference between the femoropopliteal arteries of the young and distinguished group while their legs were flexed (Fig. 10.17). While a young adult’s femoropopliteal artery appears to stay straight with hip and knee flexion, the distinguished adult’s artery exhibits locations of high curvature and buckling. This is because,

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for the young adults, the femoropopliteal arteries are highly tensioned in the supine body position, so much so that even with dramatic shortening when flexing into the fetal position, they continue to be under tension and stay straight. During childhood and adolescence, as body length increases, arteries get stretched and are tensioned. With this growth, tissue is laid down and artery length is increased in order to maintain a certain level of healthy tension. However, during adulthood, the body ceases to grow longer and the arteries do not get increasingly stretched anymore and, simultaneously, elastin degradation causes the arteries to stiffen and lengthen (Avolio et al., 1983;

FIGURE 10.17

Magnetic resonance angiograms of the femoropopliteal arteries in the supine (left column) and flexed hip and knee (right column) positions of a 31-year-old (top row) and a 52-year-old (bottom row). While the younger adult’s femoropopliteal arteries remain straight with hip and knee flexion, the older adult’s arteries curve and buckle because they shorten beyond the point of axial slack. The greatest buckling is observed at the proximal and distal locations not constrained by the adductor canal (arrows). Adapted from Cheng, C.P., Wilson, N.M., Hallett, R.L., Herfkens, R.J., Taylor, C.A., 2006. In vivo MR angiographic quantification of axial and twisting deformations of the superficial femoral artery resulting from maximum hip and knee flexion. J. Vasc. Interv. Radiol. 17, 979 987, Figure 6.

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Greenwald 2007). Thus, distinguished adults’ arteries are “kinkier” because their arteries pass the point of slack during hip and knee flexion, and the excessive artery length causes curving and buckling. This is especially apparent in the top and bottom thirds of the SFA, while the middle third of the SFA stays relatively straight. This is because the top and bottom thirds of the SFA are in close proximity to the flexed hip and knee, respectively, and because the middle third is more highly constrained by the tight tunnel of the adductor canal. In fact, axial length, axial twist, and bending deformations are all greatest in the distal third of the SFA due to freedom from the adductor canal inferior to the adductor hiatus and vicinity to the flexed knee (which was flexed more than the hip). Moving on to the patients diagnosed with non-calcific lower extremity peripheral arterial disease, Klein et al. (2009) studied patients aged 57 6 10 years in the supine position and with approximately 45 degrees hip flexion and 120 degrees knee flexion. 3D analysis was performed by projecting two 2D angiography views (left anterior oblique and right anterior oblique, at least 30 degrees apart) into 3D space. Instead of pure in-plane flexion, patients crossed their bent leg over the other leg, causing some simultaneous external hip rotation (Fig. 10.18). With leg motion, the SFA, popliteal artery, and combined femoropopliteal artery experienced 6.1 6 4.5%, 15.8 6 6.0%, and 10.0 6 2.6% axial shortening, respectively, and the SFA and popliteal arteries experienced 1.7 6 1.0 and 3.5 6 1.9 degree/cm axial twist, respectively. Mean curvature increased for the SFA, popliteal artery, and combined femoropopliteal artery from 0.08 6 0.02, 0.10 6 0.02, and 0.09 6 0.02 cm21 to 0.11 6 0.03, 0.31 6 0.10, and 0.20 6 0.06 cm21, respectively. These deformations match very well with the healthy older subjects from Cheng et al. (2010) for axial shortening (6.1% vs 6.9%) and axial twist (1.7 vs 1.7 degrees) of the SFA, indicating that noncalcific peripheral artery disease may not

FIGURE 10.18 Patients from Klein et al. achieved approximately 45/120 degrees flexion of the hip/knee by crossing the bent leg. Adapted from Klein, A.J., Chen, S.J., Messenger, J.C., Hansgen, A.R., Plomondon, M.E., Carroll, J.D., et al., 2009. Quantitative assessment of the conformational change in the femoropopliteal artery with leg movement. Cathet. Cardiovasc. Interv. 74, 787 798, Figure 2.

significantly affect SFA deformations due to hip and knee flexion. Also, these data suggest that the amount of external hip rotation in this study may not have contributed much to femoropopliteal artery deformation. In another study with peripheral artery disease patients, this time with varying levels of calcification, patients aged 56 79 years were imaged using rotational C-arm computed tomography in the supine position and with 20 degrees hip and 70 degrees knee flexion (Gokgol et al., 2013). Flexion angles of 20 degrees hip and 70 degrees knee are approximately commensurate with peak joint flexion angles during walking. The popliteal artery experienced 5.9 6 2.5% axial shortening and 3.8 6 2.2 degree/cm axial twist, relatively consistent with the aforementioned studies considering the leg flexion angles.

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Mean curvature of the popliteal artery increased from 0.06 6 0.02 to 0.12 6 0.07 cm21 while peak curvature within the segment increased from 0.12 6 0.04 to 0.24 6 0.09 cm21. Interestingly, as the severity of calcification increased, peak curvature of the popliteal artery in the straight leg increased from 0.08 to 0.17 cm21, and in the flexed leg increased from 0.17 to 0.39 cm21, indicating that greater calcification increases popliteal artery bending severity in both leg straight and flexed positions. This makes sense since calcium is hard and will tend to concentrate deformations at its borders. Young et al. (2012) used computer simulations of walking, stair climbing, and sit-tostand motion to better understand the axial length deformations of the femoropopliteal artery during the entire span of these body motions (Fig. 10.10). Using data from video motion tracking of actual subjects walking, climbing stairs, and standing up from a seated position, the simulations calculated maximum femoropopliteal arterial shortening of 8.3 6 0.6%, 11.9 6 2.2%, and 14.7 6 3.8%, respectively. While these arterial shortening

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values were substantial and relatively consistent for all subjects, femoropopliteal artery elongation was not. For example, maximum elongation values only reached 0.9%, 0.6%, 1.0% for walking, stair climbing, and sit-tostand motion, respectively. Not only are these deformations small (e.g., 1% equals 4 mm of length change over 40 cm of arterial length), but the elongation was not consistent as many subjects did not produce any elongation at all during any of these activities. In order to achieve very high resolution measurements of femoropopliteal artery deformations, rather than rely only on arterial branches as fiducial markers, a series of studies were performed on cadavers where metallic markers were implanted into the artery and imaged with 3D computed tomography (MacTaggart et al., 2014; Poulson et al., 2018) (Fig. 10.19). In the first study, the cadaver was moved into a position with 37 6 3 degrees hip and 108 6 2 degrees knee flexion (MacTaggart et al., 2014). The proximal SFA, distal SFA, popliteal artery, and combined femoropopliteal artery experienced 7 6 7%, 19 6 10%, 30 6 8%, and 12 6 11%

FIGURE 10.19 Small, disconnected V-shaped markers were deployed into the femoropopliteal arteries of cadavers for tracking highly localized deformations of the artery during leg flexion. From MacTaggart, J.N., Phillips, N.Y., Lomneth, C.S., Pipinos, I.I., Bowen, R., Baxter, B.T., et al., 2014. Three-dimensional bending, torsion and axial compression of the femoropopliteal artery during limb flexion. J. Biomech. 47, 2249 2256, Figure 2.

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axial shortening, and 0 6 6, 28 6 9, 77 6 27, and 4 6 16 degree/cm axial twist with leg flexion, respectively. In addition, the maximum curvature for the proximal SFA, distal SFA, popliteal artery, and combined femoropopliteal artery in the flexed leg position was 0.50, 1.00, 1.67, and 1.67 cm21, respectively. This study showed that deformations are highly localized in the femoropopliteal artery during hip and knee flexion, with axial length, axial twist, and curvature deformations being 2.5-, 19-, and 3.7-fold greater, respectively, than previously published. Note, however, that this study was performed on lightly embalmed cadavers, with no arterial tension or active muscular support, and that all of these high deformations were measured at the adductor hiatus, where the femoropopliteal artery just leaves the constraint of the adduct canal. In a related study, Poulson et al. (2018) quantified femoropopliteal artery deformations in cadavers at increasing angles of knee flexion. With 70 degrees of knee flexion (to represent walking), the proximal SFA, distal SFA, and popliteal artery experienced 9.3%, 10.6%, and 13.3% axial shortening, and the maximum curvature in the flexed leg position was 0.42, 0.56, and 0.91 cm21, respectively. With 90 degrees of knee flexion (to represent stair climbing or sitting), the proximal SFA, distal SFA, and popliteal artery experienced 12.5%, 13.7%, and 17.3% axial shortening, and the maximum curvature in the flexed leg position was 0.53, 0.91, and 1.43 cm21, respectively. With 120 degrees of knee flexion (to represent squatting), the proximal SFA, distal SFA, and popliteal artery experienced 15.2%, 18.5%, and 25.1% axial shortening, and the maximum curvature in the flexed leg position was 0.59, 1.43, and 2.00 cm21, respectively. These data tell us that femoropopliteal artery axial lengths and curvatures deform increasingly with greater knee flexion angles, and that the trend of greater deformation in the distal portions of the artery persists regardless of the flexion angle.

Stented Artery Deformations from Musculoskeletal Movement In the next group of publications, we examine the femoropopliteal artery deformations due to hip and knee flexion in the presence of implanted stents (Table 10.4). The beauty of these studies is that the stents themselves could be used as fiducial markers to quantify deformations, along with the incidental arterial branches. Nikanorov et al. (2008) measured axial length deformations of the femoropopliteal artery in cadavers implanted with single Absolutes stents (Abbott Vascular, Santa Clara, California) using lateral X-ray plain films. These cadavers did not have any apparent peripheral vascular disease. With 20 degrees hip and 70 degrees knee flexion, the middle SFA, distal SFA/proximal popliteal, and popliteal arteries exhibited 3 6 2%, 4 6 1%, and 6 6 4% axial shortening, respectively. And with 90 degrees hip and 90 degrees knee flexion, the middle SFA, distal SFA/proximal popliteal, and popliteal arteries exhibited 3 6 3%, 6 6 3%, and 11 6 5% axial shortening, respectively. As compared to native arteries in the absence of peripheral artery disease, these axial deformations are lower for similar hip and knee flexion angles (Cheng et al., 2010; Poulson et al., 2018). This makes sense because the added axial stiffness of the stent should reduce the axial deformation of the femoropopliteal artery when it is subjected to the same stimulus. Note that this study was performed on cadavers, and since the quantification was performed only with 2D lateral views, the axial lengths measured may have been underestimations. In a follow-up study, the same group performed similar measurements in patients treated for lower extremity occlusive disease (Nikanorov et al., 2013). These patients were 73 6 10 years old, treated with single or overlapping stents (all Absolutes stents, Abbott Vascular, Santa Clara, California), and imaged with lateral X-ray plain films two days after stent implantation. Axial length and curvature

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TABLE 10.4 Axial Length and Curvature Metrics of the Stented Femoropopliteal Artery With Hip and Knee Flexion

Study

Population and Condition

Flexion Angles

Anatomic Location

Axial Shortening (%)

Bent Leg Straight Leg Curvature Curvature (cm21) (cm21)

Nikanorov et al. (2008)

Cadaver, Single stents (Absolutes stent)

20 hip 70 knee

mSFA

362

N/A

N/A

dSFA/pPA

461

PA

664

mSFA

363

N/A

N/A

dSFA/pPA

663

PA

11 6 5

mSFA

1.7 6 1.7

N/A

N/A

dSFA/pPA

2.4 6 0.4

N/A

PA

3.5 6 2.7

0.11

mSFA

3.1 6 1.8

dSFA/pPA

5.3 6 0.5

PA

8.5 6 3.2

SFA/PA

463

Nikanorov et al. (2008)

*Nikanorov et al. (2013)

*Nikanorov et al. (2013)

*Ganguly et al. (2011)

Cadaver, Single stents (Absolutes stent)

Leg PAD, 73 6 10 years Single & Overlap (Absolutes stent) Leg PAD, 73 6 10 years Single & Overlap (Absolutes stent)



90 hip 90 knee



20 hip 70 knee



90 hip 90 knee



Leg PAD, 67 6 8.5 years, B60 hip Single & Overlap (Mixed B120 knee designs)

N/A

0.07 N/A 0.45 Max

0.09, 0.27

0.12, 0.33Max

Data are shown as mean or mean 6 standard deviation. SFA, superficial femoral artery; PA, popliteal artery; p, proximal; m, middle; d, Distal; PAD, peripheral artery disease; Max, local maximum curvature. * Curvature values converted from radius of curvature values in the publication.

measurements were quantified with the stent itself in the straight leg, 20 degrees hip and 70 degrees knee flexion, and 90 degrees hip and 90 degrees knee flexion positions (Fig. 10.20). With 20 degrees hip and 70 degrees knee flexion, the middle SFA, distal SFA/proximal popliteal, and popliteal arteries shortened by 1.7 6 1.7%, 2.4 6 0.4%, and 3.5 6 2.7%, respectively, and the maximum curvature in the bent leg position at the popliteal artery was 0.11 cm21. With 90 degrees hip and 90 degrees knee flexion, the middle SFA, distal SFA/proximal popliteal, and popliteal arteries shortened by 3.1 6 1.8%, 5.3 6 0.5%, and 8.5 6 3.2%, respectively, and the maximum curvature in the bent leg position at the middle SFA and the popliteal artery was 0.07 and 0.45 cm21, respectively. These axial deformations are somewhat lower than those

measured in the cadavers; however, this could be due to the longer stented lengths in the patients (hence longer regions of increased axial stiffness). Another finding of this study was that even after dwelling for an additional 7 months, when the measurements were performed again, the femoropopliteal artery deformations were largely unchanged. This is a particularly important finding because it has often been assumed (as usual, in the absence of supporting data) that substantial arterial remodeling post-intervention would reduce arterial deformations. On the contrary, this study suggests that long-term stent deformations may be well predicted with immediate post-intervention data. Ganguly et al. (2011) performed 3D C-arm computed tomography of patients aged 67 6 8.5 years treated with femoropopliteal artery stents.

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FIGURE 10.20 With 2D lateral X-ray plain films, implanted femoropopliteal stent lengths (top row) and maximum curvatures (bottom row) were measured in the straight leg (left column), 20 degrees hip and 70 degrees knee flexion (middle column), and 90 degrees hip and 90 degrees knee flexion (right column) positions. Note that the top and bottom rows are two different patients. Adapted from Nikanorov, A., Schillinger, M., Zhao, H., Minar, E., Schwartz, L.B., 2013. Assessment of self-expanding nitinol stent deformation after chronic implantation into the femoropopliteal arteries. EuroIntervention 9, 730 737, Figures 2 and 3.

The patients were scanned in the supine position and with approximately 60 degrees hip and 120 degrees knee flexion (Fig. 10.21). With leg flexion, the femoropopliteal stented segments shortened by 4 6 3%, and the mean and maximum curvatures of the stent centerlines were 0.09 and 0.27 cm21, respectively, for the straight leg, and 0.12 and 0.33 cm21, respectively, for the flexed leg. The stented regions were highly variable in terms of anatomic location and length, which are reported individually in the publication. While the previous publications provide a rich description of femoropopliteal artery

deformations due to various angles of hip and knee flexion, in both native and stented arteries, they do not address how percutaneous interventions change arterial deformations in the same individuals. In two recent publications, the authors do just that (Gokgol et al., 2017; Schumann et al., 2017). Table 10.5 shows the axial length and curvature metrics of the femoropopliteal artery before and after balloon angioplasty in one set of patients, and before and after angioplasty and stenting in another (Table 10.5). Patients aged 69 6 10 years with lower extremity arterial disease were imaged via two views of 2D angiography (45 60

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FIGURE 10.21

C-arm computed tomography of stented patients in the supine (top row) and flexed leg (bottom row) positions. In this example, overlapped femoropopliteal artery stents are shown next to the femur (right column). Adapted from Ganguly, A., Simons, J., Schneider, A., Keck, B., Bennet, N. R., Herfkens, R.J., et al., 2011. In vivo imaging of femoral artery nitinol stents for deformation analysis. J. Vasc. Interv. Radiol. 22: 244 249, Figure 2.

degrees apart) and the two views were projected into 3D space to identify the centerline path of the femoropopliteal artery. The arteries were imaged in the straight leg and 20 degrees hip and 70 degrees knee flexion positions before and after the intervention. Before angioplasty, the arterial regions proximal to the lesion, at the lesion segment, and distal to the lesion experienced axial length shortening of 5.0 6 2.3%, 4.6 6 3.0%, and 11.5 6 4.0%, respectively, mean curvature increase of 0.02 6 0.01, 0.05 6 0.07, and 0.11 6 0.15 cm21, respectively, and maximum curvature increase of 0.08 6 0.05, 0.18 6 0.16,

and 0.24 6 0.25 cm21, respectively, when moving from straight to flexed leg. After angioplasty, the same leg flexion caused the regions proximal to the lesion, at the lesion segment, and distal to the lesion to shorten by 4.4 6 3.6%, 7.4 6 5.3%, and 11.6 6 4.3%, respectively, have a mean curvature increase of 0.01 6 0.02, 0.06 6 0.06, and 0.15 6 0.17 cm21, respectively, and have a maximum curvature increase of 0.05 6 0.05, 0.19 6 0.12, and 0.25 6 0.21 cm21, respectively. Analogously, before angioplasty and stenting, the arterial regions proximal to the lesion, at the lesion segment, and distal to the lesion experienced axial length shortening

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TABLE 10.5 Axial Length and Curvature Metrics of the Femoropopliteal Artery With Hip and Knee Flexion Before and After Intervention Axial Shortening (%)

Straight Leg Mean Curve (cm21)

Bent Leg Mean Curve (cm21)

Change in Mean Curve (cm21)

Straight Leg Max Curve (cm21)

Bent Leg Max Curve (cm21)

Change in Max Curve (cm21)

PRE-INTERVENTION ANGIOPLASTY pLesion

5.0 6 2.3

0.05 6 0.02

0.07 6 0.02

0.02 6 0.01

0.10 6 0.03

0.14 6 0.05

0.08 6 0.05

@Lesion

4.6 6 3.0

0.07 6 0.02

0.12 6 0.08

0.05 6 0.07

0.13 6 0.05

0.26 6 0.17

0.18 6 0.16

dLesion 11.5 6 4.0

0.06 6 0.02

0.17 6 0.16

0.11 6 0.15

0.11 6 0.04

0.30 6 0.25

0.24 6 0.25

STENTING pLesion

8.0

0.06

0.17

0.11

0.11

0.34

0.28

@Lesion

6.4 6 3.4

0.05 6 0.02

0.09 6 0.04

0.04 6 0.03

0.12 6 0.04

0.19 6 0.08

0.12 6 0.04

dLesion 12.9 6 3.6

0.06 6 0.02

0.16 6 0.05

0.10 6 0.06

0.13 6 0.05

0.33 6 0.12

0.28 6 0.14

POST-INTERVENTION ANGIOPLASTY pLesion

4.4 6 3.6

0.04 6 0.02

0.06 6 0.01

0.01 6 0.02

0.08 6 0.02

0.11 6 0.03

0.05 6 0.05

@Lesion

7.4 6 5.3

0.07 6 0.02

0.13 6 0.07

0.06 6 0.06

0.13 6 0.03

0.25 6 0.15

0.19 6 0.12

dLesion 11.6 6 4.3

0.06 6 0.02

0.20 6 0.18

0.15 6 0.17

0.11 6 0.04

0.29 6 0.23

0.25 6 0.21

STENTING pLesion

8.7 6 8.7

0.05 6 0.02

0.13 6 0.09

0.08 6 0.10

0.10 6 0.04

0.24 6 0.19

0.18 6 0.19

@Lesion

3.2 6 2.9

0.06 6 0.02

0.09 6 0.05

0.03 6 0.04

0.11 6 0.05

0.21 6 0.16

0.16 6 0.14

dLesion

9.3 6 6.7

0.07 6 0.02

0.16 6 0.08

0.09 6 0.07

0.13 6 0.04

0.30 6 0.16

0.24 6 0.18

Data are shown as mean or mean 6 standard deviation. Mean Curve, Mean curvature of the segment; Max Curve, local maximum curvature; pLesion, proximal to the lesion; @Lesion, at location of the lesion; dLesion, distal to lesion.

of 8.0%, 6.4 6 3.4%, and 12.9 6 3.6%, respectively, mean curvature increase of 0.11, 0.04 6 0.03, and 0.10 6 0.06 cm21, respectively, and maximum curvature increase of 0.28, 0.12 6 0.04, and 0.28 6 0.14 cm21, respectively, when moving from straight to flexed leg. After angioplasty and stenting, the same leg flexion caused the regions proximal to the lesion, at the lesion segment, and distal to the lesion to shorten by 8.7 6 8.7%, 3.2 6 2.9%, and 9.3 6 6.7%, respectively, exhibit a mean curvature increase of 0.08 6 0.10, 0.03 6 0.04, and

0.09 6 0.07 cm21, respectively, and exhibit a maximum curvature increase of 0.18 6 0.19, 0.16 6 0.14, and 0.24 6 0.18 cm21, respectively. Considering these data, angioplasty alone appears to increase the amount of axial shortening of the treated segment of the artery compared to pre-intervention, while angioplasty and stenting appear to decrease the amount of axial shortening of the treated segment of the artery compared to preintervention. This makes sense because angioplasty should disrupt the stiff calcium of the

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FIGURE 10.22

Two examples of increased femoropopliteal curvature in the leg flexed position after stenting (white arrows in right images) as compared to the pre-intervention state (left images). Adapted from Gokgol, C., Schumann, S., Diehm, N., Zheng, G., Buchler, P., 2017. In vivo quantification of the deformations of the femoropopliteal segment: percutaneous transluminal angioplasty vs nitinol stent placement. J. Endovasc. Ther. 24 (1), 27 34, Figure 1.

femoropopliteal artery lesion, leading to a more compliant and axially flexible artery. On the other hand, implantation of stents should add stiffness to the treated segment, leading to a more axially stiff artery. In other words, these data suggest that the stent adds more axial stiffness to the femoropopliteal artery than the balloon angioplasty subtracts. In general, increasing the capacity for arterial length change decreases the chance of arterial kinking, which has been correlated with disease progression in the form of restenosis or reocclusion. Fig. 10.22 shows two examples of increased maximum curvature in the femoropopliteal artery after stenting in the flexed leg position (Fig. 10.22). Once again, the location and extent of stenting were highly variable and

described in more detail in the papers (Gokgol et al., 2017; Schumann et al., 2017).

Cross-Sectional Compression The femoropopliteal artery is subject to cross-sectional compression forces due to normal muscle contraction. Three-dimensional MRI scanning was performed on the thighs of a series of healthy adults, aged 27 6 4 years, with the thigh relaxed and with maximal isometric thigh contraction (Brown et al., 2009). In order to measure cross-sectional compression, the aspect ratio of the arterial cross-section was computed as a minor axis diameter/major axis diameter of a fitted ellipse (Fig. 10.23). Vessel

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FIGURE 10.23 Representative cross-sectional MRI images of the thigh in the relaxed state (left column) and during maximal isometric contraction (right column) inferior to the adductor canal (top row, “inferior to AC”), in the distal portion of the adductor canal (middle row, “distal AC”), and in the proximal portion of the adductor canal (bottom row, “proximal AC”). Solid arrowheads indicate the femoropopliteal artery and open arrowheads indicate the femoropopliteal vein. AC, Adductor canal; AM, adductor magnus muscle; BFL, long head of biceps femoris muscle; b/a, minor to major axis diameter ratio; BFS, short head of biceps femoris muscle; d, normalized location from femoral condyle to femoral head; F, femur; G, gracilis muscle; RF, rectus femoris muscle; S, sartorius muscle; SM, semimembranosus muscle; ST, semitendinosus muscle; VI, vastus intermedius muscle; VL, vastus lateralis muscle; VM, vastus medialis muscle. Adapted from Brown, R., Nguyen, T.D., Spincemaille, P., Prince, M.R., Wang, Y., 2009. In vivo quantification of femoral-popliteal compression during isometric thigh contraction: assessment using MR angiography. J. Magn. Reson. Imaging 29 (5), 1116 1124, Figure 3.

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FIGURE 10.24 Average femoropopliteal cross-sectional lumen aspect ratios plotted against normalized location from d 5 0.09 (B4 cm superior to femoral condyle) to d 5 0.41 (B18 cm superior to femoral condyle) (top graph). The aspect ratio change (cross-sectional compression) was statistically significant (p , 0.05) in the region 0.21 # d # 0.32, which is approximately the 5 cm segment just proximal to the adductor hiatus (bottom graph). Source: BrownFPAspectRatio, from Brown, R., Nguyen, T. D., Spincemaille, P., Prince, M.R., Wang, Y., 2009. In vivo quantification of femoral-popliteal compression during isometric thigh contraction: assessment using MR angiography. J. Magn. Reson. Imaging 29 (5), 1116 1124, Figure 4.

boundary geometries were transformed into new coordinate systems to ensure that the cross-sectional measurements were taken orthogonal to the vessel centerline. As can be seen in Fig. 10.23, the vastus medialis muscle causes considerable compression on the femoropopliteal artery at the distal portion of the adductor canal, just superior to the adductor hiatus. In this region, the aspect ratio significantly decreased from 0.88 6 0.06 during thigh relaxation to 0.77 6 0.09 during maximal isometric thigh contraction, while the proximal portion of the adductor canal and inferior to the adductor canal experienced no significant change in aspect ratio (0.87 6 0.07 vs 0.83 6 0.09). To state this another way, significant cross-sectional compression of the femoropopliteal artery, as measured by significant change in lumen aspect

ratio, occurred in the 5 cm span just proximal to the adductor hiatus (Fig. 10.24). Another source of cross-sectional compression in the femoropopliteal artery is related to popliteal entrapment syndrome, a relatively rare disease. The most common forms of popliteal entrapment syndrome involve compressing the popliteal artery, caused by abnormal medial migration of the medial head of the gastrocnemius muscle or popliteus muscle (Czihal et al., 2015) (Fig. 10.25). This results in pain due to chronic leg ischemia and/or pinching the tibial nerve in the popliteal fossa. It is believed that repetitive compression as a result of lower leg motion (often plantar flexion of the ankle during walking or running) can cause intimal damage and lead to thrombus, stenosis, or aneurysm formation. While

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FIGURE 10.25

Plantar flexion causes bilateral popliteal artery compression in the popliteal fossa (left), partially due to the hypertrophied medial head of the gastrocnemius muscle (right, # symbol). Adapted from Czihal, M., Banafsche, R., Hoffmann, U., Koeppel, T., 2015. Vascular compression syndromes. Vasa 44, 419 434, Figure 7.

hypertrophy of the gastrocnemius muscle in highly trained athletes has been associated with popliteal entrapment syndrome, the link has not been definitively proven.

TIBIAL ARTERIES Anatomy The popliteal artery turns into the tibial arteries posterior to the tibia at the knee (Fig. 10.26). At this location, the popliteal artery bifurcates into the anterior tibial artery which feeds the anterior compartment of the shank and the top of the foot, and the tibialperoneal trunk (also known as the tibialfibular trunk). The anterior tibial artery runs anterior to the popliteus muscle and then descends between the tibia and fibula bones and

between the tibialis anterior and extensor digitorum longus muscles. The tibial-peroneal trunk bifurcates into the posterior tibial artery which feeds the posterior compartment of the shank and the underside of the foot, and the peroneal artery (also known as the fibular artery) which feeds the lateral compartment of the leg. The posterior tibial artery runs posterior to the tibia between the flexor digitorum longus and soleus muscles, while the peroneal artery runs medial to the fibula and also between the flexor digitorum longus and soleus muscles. Ankle flexion and extension are likely the musculoskeletal actions that work to deform the tibial arteries the most. Ankle flexion is also known as dorsiflexion and is driven by contraction of the tibialis anterior muscle. The tibialis anterior muscles originate at the upper lateral

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FIGURE 10.26 Lower leg arteries. The popliteal artery bifurcates into the anterior tibial artery and the tibial-peroneal trunk, and the tibial-peroneal trunk bifurcates into the peroneal and posterior tibial arteries. From commons.wikimedia.org/ wiki/File:2129ab_Lower_Limb_Arteries_Anterior_Posterior.jpg.

surface of the tibia and insert into bones in the foot. Ankle extension is also known as plantar flexion and is driven by contraction of the gastrocnemius and soleus muscles (the calf), and the flexor hallucis longus, flexor digitorum longus, and tibialis posterior muscles. The gastrocnemius originates at the posterior surfaces of the femoral condyles and inserts into the heel bone, while soleus originates from the posterior surfaces of the tibia and fibula and also inserts into the heel bone. The flexor hallucis longus, flexor digitorum longus, and tibialis posterior muscles all originate from the posterior surfaces of the tibia and fibula and insert into various bones in the foot. While dorsiflexion is merely responsible for lifting the foot, plantar flexion is responsible for lifting the weight of the entire body. It is no wonder that the musculature for plantar flexion is so much more robust than for

dorsiflexion (i.e., the calf is more muscular than the front of the shank).

Tibial Artery Motion There are extremely scant published data concerning tibial artery motion. In fact, no studies have focused on pulsatile deformations of the tibial arteries at all. It has long been assumed that the tibial arteries do not pulse significantly since they are far away from the beating heart, are less elastic than the larger arteries proximal to it, and are buried deep in strong, compartmentalized muscles in the calf. Whether these assumptions are true will require future investigation. However, since the tibial arteries are adjacent to the strong, compartmentalized muscles

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in the calf, it stands to reason that they could be influenced during ankle motion, especially during the weight-bearing action of plantar flexion. In a single case study presented at the 2008 Stent Summit at the Cleveland Clinic, magnetic resonance angiography was performed on a weight-bearing subject using an alternating repetition time steady state free precession sequence (Cheng et al., 2008). An MRI-compatible supine weight-bearing device was used to enforce 50 pounds of isometric plantar flexion load for the duration of the scans, where the posterior tibial, anterior tibial,

and peroneal arteries, as well as minor muscle branches, were resolved (Fig. 10.27). While calf muscle contraction was easily observed, unfortunately the spatial resolution was not sufficient to measure cross-sectional deformation of the arteries. Tibial artery length changes were also not detected with isometric plantar flexion; however, an axial twist of more than 10 degrees/cm was measured for certain segments. Ankle flexion and extension were studied in the context of below the ankle vascular interventions (Katsanos et al., 2013). Using contrast-

FIGURE 10.27 Magnetic resonance angiography of the lower leg while the calf is relaxed (left column) and during 50 pounds of isometric plantar flexion contraction (right column). While there is a visible contraction of the gastrocnemius and soleus muscles (top row), the tibial arteries were not visibly deformed (bottom row).

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CONCLUSION

FIGURE 10.28 The ankle joint imaged with X-ray angiography undergoing dorsiflexion (left column) and plantar flexion (right column). During dorsiflexion, the distal anterior tibial and dorsalis pedis arteries are kinked (top left) while the distal posterior tibial artery is straight (bottom left), and conversely during plantar flexion, the distal anterior tibial and dorsalis pedis arteries are straight (top right) while the distal posterior tibial artery is kinked (bottom right). Adapted from Katsanos, K., Diamantopoulos, A., Spiliopoulos, S., Karnabatidis, D., Siablis, D., 2013. Below-the-ankle angioplasty and stenting for limb salvage: anatomical considerations and longterm outcomes. Cardiovasc. Interv. Radiol. 36 (4), 926 935, Figures 5 and 6.

enhanced 2D X-ray angiograms, patients with infrapopliteal interventions for critical limb ischemia were imaged in dorsiflexion (ankle flexion) and plantar flexion (ankle extension) (Fig. 10.28). The study found that the distal region of the anterior tibial artery, as it transitions into the dorsalis pedis artery, kinks during dorsiflexion while the posterior tibial artery is straight. Conversely, during plantar flexion, the distal posterior tibial artery is kinked while the anterior tibial and dorsalis

pedis arteries are straight. The authors hypothesize that both anterior and posterior arteries are straight in the neutral position.

CONCLUSION The lower extremity arteries undergo deformations induced by cardiac pulsatility and musculoskeletal movements at the hip, knee, and ankle. These deformations are a

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consequence of complex vascular and musculoskeletal anatomy and physiology of the lower extremities, especially due to joint flexion and extension. The iliac, femoropopliteal, and tibial arteries behave differently in healthy arteries, diseased native arteries, and in diseased arteries after endovascular interventions. While there is a relatively large bank of published studies about the dynamics of the lower extremity arteries, with data based on medical image analysis, computational simulation, and cadaver testing, there is still much to be learned about these complex motions.

References Avolio, A.P., Chen, S.G., Wang, R.P., Zhang, C.L., Li, M.F., O’Rourke, M.F., 1983. Effects of aging on changing arterial compliance and left ventricular load in a northern Chinese urban community. Circulation 68, 50 58. Bender, M.H.M., Schep, G., de Vries, W.R., Hoogeveen, A. R., Wijn, P.F.F., 2004. Sports-related flow limitations in the iliac arteries in endurance athletes: aetiology, diagnosis, treatment and future developments. Sports Med. 34 (7), 427 442. Benetos, A., Laurent, S., Hoeks, A., Boutouyrie, P., Safar, M., 1993. Arterial alterations with aging and high blood pressure. Arterioscler. Thromb. Vasc. Biol. 13, 90 97. Borley, N.R., 2008. Abdomen and pelvis. In: Standring, S. (Ed.), Gray’s Anatomy, Chapter 62, pp. 1083 1097. Churchill Livingstone/Elsevier, Edinburgh, UK. Brown, R., Nguyen, T.D., Spincemaille, P., Prince, M.R., Wang, Y., 2009. In vivo quantification of femoralpopliteal compression during isometric thigh contraction: assessment using MR angiography. J. Magn. Reson. Imaging 29 (5), 1116 1124. Cao, E., Cheng, C.P., 2007. In vivo 3D deformations of the human iliac artery due to hip flexion. In: 2007 Transcatheter Cardiovascular Therapeutics Conference, Abstract #587. Cheng, C.P., Choi, G., Cukur, T., 2008, Tibial Artery Biomechanics. In: 2008 Stent Summit at the Cleveland Clinic. Cheng, C.P., Wilson, N.M., Hallett, R.L., Herfkens, R.J., Taylor, C.A., 2006. In vivo MR angiographic quantification of axial and twisting deformations of the superficial femoral artery resulting from maximum hip and knee flexion. J. Vasc. Interv. Radiol. 17, 979 987.

Cheng, C.P., Choi, G., Herfkens, R.J., Taylor, C.A., 2010. The effect of aging on deformations of the superficial femoral artery due to hip and knee flexion: potential clinical implications. J. Vasc. Interv. Radiol. 21 (2), 195 202. Choi, G., Suh, G., Shin, L.K., Taylor, C.A., Cheng, C.P., 2009. In vivo deformation of the human abdominal aorta and common iliac arteries with hip and knee flexion: implications for the design of stent-grafts. J. Endovasc. Ther. 16 (5), 531 538. Czihal, M., Banafsche, R., Hoffmann, U., Koeppel, T., 2015. Vascular compression syndromes. Vasa 44, 419 434. Ganguly, A., Simons, J., Schneider, A., Keck, B., Bennet, N. R., Herfkens, R.J., et al., 2011. In vivo imaging of femoral artery nitinol stents for deformation analysis. J. Vasc. Interv. Radiol. 22, 244 249. Gokgol, C., Diehm, N., Kara, L., Buchler, P., 2013. Quantification of popliteal artery deformation during leg flexion in subjects with peripheral artery disease: a pilot study. J. Endovasc. Ther. 20 (6), 828 835. Gokgol, C., Schumann, S., Diehm, N., Zheng, G., Buchler, P., 2017. In vivo quantification of the deformations of the femoropopliteal segment: percutaneous transluminal angioplasty vs nitinol stent placement. J. Endovasc. Ther. 24 (1), 27 34. Greenwald, S.E., 2007. Ageing of the conduit arteries. J. Pathol. 211 (2), 157 172. Grob, K., Ackland, T., Kuster, M.S., Manestar, M., Filgueira, L., 2016. A newly discovered muscle: the tensor of the vastus intermedius. Clin. Anat. 29 (2), 256 263. Hansen, F., Berggvist, D., Mangell, P., Ryden, A., Sonesson, B., Lanne, T., 1993. Non-invasive measurements of pulsatile vessel diameter change and elastic properties in human arteries: a methodological study. Clin. Physiol. 13 (6), 631 643. Henry, R.M.A., Kostense, P.J., Spijkerman, A.M.W., Dekker, J.M., Nijpels, G., Heine, R.J., et al., 2003. Arterial stiffness increases with deteriorating glucose tolerance status. Circulation 107, 2089 2095. Ihara, M., Ueno, A., Tsuda, Y., Takahashi, H., Yamazaki, T., Kudo, M., et al., 2015. A case of repeated occlusion in the common iliac artery due to an unexpected stent deformation. Cardiovasc. Interv. Ther. 30 (2), 162 167. Katsanos, K., Diamantopoulos, A., Spiliopoulos, S., Karnabatidis, D., Siablis, D., 2013. Below-the-ankle angioplasty and stenting for limb salvage: anatomical considerations and long-term outcomes. Cardiovasc. Interv. Radiol. 36 (4), 926 935. Kauffmann, C., Douane, F., Therasse, E., Lessard, S., Elkouri, S., Gilbert, P., et al., 2015. Source of errors and accuracy of a two-dimensional/three-dimensional fusion road map for endovascular aneurysm repair of abdominal aortic aneurysm. J. Vasc. Interv. Radiol. 26 (4), 544 551.

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Kawasaki, T., Sasayam, S., Yagi, S., Asakawa, T., Hirai, T., 1987. Non-invasive assessment of the age related changes in stiffness of major branches in the human arteries. Cardiovasc. Res. 21, 678 687. Kim, M.K., Kwak, D.S., Jeun, S.S., Park, C.K., Oh, S.M., Lee, S.W., et al., 2010. Changes in abdominal vascular tension associated with various leg positions in the anterior lumbar approach. Spine 35 (10), 1026 1032. Klein, A.J., Chen, S.J., Messenger, J.C., Hansgen, A.R., Plomondon, M.E., Carroll, J.D., et al., 2009. Quantitative assessment of the conformational change in the femoropopliteal artery with leg movement. Cathet. Cardiovasc. Interv. 74, 787 798. MacTaggart, J.N., Phillips, N.Y., Lomneth, C.S., Pipinos, I.I., Bowen, R., Baxter, B.T., et al., 2014. Three-dimensional bending, torsion and axial compression of the femoropopliteal artery during limb flexion. J. Biomech. 47, 2249 2256. Mozersky, D.J., Sumner, D.S., Hokanson, D.E., Strandness Jr., D.E., 1972. Transcutaneous measurement of the elastic properties of the human femoral artery. Circulation 46 (5), 948 955. Nikanorov, A., Smouse, H.B., Osman, K., Bialas, M., Shrivastava, S., Schwartz, L.B., 2008. Fracture of selfexpanding nitinol stents stressed in vitro under simulated intravascular conditions. J. Vasc. Surg. 48, 435 440. Nikanorov, A., Schillinger, M., Zhao, H., Minar, E., Schwartz, L.B., 2013. Assessment of self-expanding nitinol stent deformation after chronic implantation into the femoropopliteal arteries. EuroIntervention 9, 730 737. Park, S.I., Won, J.H., Kim, B.M., Kim, J.K., Lee, D.Y., 2005. The arterial folding point during flexion of the hip joint. Cardiovasc. Interv. Radiol. 28 (2), 173 177. Peach, G., Schep, G., Palfreeman, R., Beard, J.D., Thompson, M.M., Hinchliffe, R.J., 2012. Endofibrosis

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and kinking of the iliac arteries in athletes: a systematic review. Eur. J. Vasc. Endovasc. Surg. 43 (2), 208 217. Poulson, W., Kamenskiy, A., Seas, A., Deegan, P., Lomneth, C., MacTaggart, J., 2018. Limb flexion-induced axial compression and bending in human femoropopliteal artery segments. J. Vasc. Surg. 67, 607 613. Roos, H., Ghaffari, M., Falkenberg, M., Chernoray, V., Jeppsson, A., Nilsson, H., 2014. Displacement forces in ilian zones and stent graft interconnections in endovascular aortic repair: an experimental study. Eur. J. Vasc. Endovasc. Surg. 47 (3), 262 267. Schumann, S., Gokgol, C., Diehm, N., Buchler, P., Zheng, G., 2017. Effect of stent implantation on the deformations of the superficial femoral artery and popliteal artery: in vivo three-dimensional deformational analysis from two-dimensional radiographs. J. Vasc. Interv. Radiol. 28, 142 146. van Keulen, J.W., van Prehn, J., Moll, F.L., van Herwaarden, J.A., 2010. Recurrent stent-graft disintegration caused by cardiac-induced aortoiliac movements. J. Endovasc. Ther. 17 (3), 354 355. van Keulen, J.W., Moll, F.L., Vonken, E.J.P., Tolenaar, J. L., Muhs, B.E., van Herwaarden, J.A., 2011. Pulsatility in the iliac artery is significant at several levels: implications for EVAR. J. Endovasc. Ther. 18 (2), 199 204. Willekes, C., Hoogland, H.J., Hoeks, A.P.G., Reneman, R.S., 1998. Bladder filling reduces femoral artery wall distension and strain: beware of a full bladder. Ultrasound Med. Biol. 6, 803 807. Young, M.D., Streicher, M.C., Beck, R.J., van den Bogert, A. J., Tajaddini, A., Davis, B.L., 2012. Simulation of lower limb axial arterial length change during locomotion. J. Biomech. 45 (8), 1485 1490.

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C H A P T E R

11

Veins of the Upper Body A. Carr1 and Christopher P. Cheng2 1

Intensive Care Medicine, Southern District Health Board and University of Otago, Otago & Southland, New Zealand 2Stanford University, Stanford, CA, United States

Familiarity with the normal venous anatomy and more common variations within the thorax, lower neck, upper limbs, and upper abdomen is essential to understanding the dynamic changes that occur in the position and size of the vessels during the respiratory cycle, movement of the limbs relative to the thorax, and movement of the head and neck relative to the thoracic inlet. As the anatomy is dynamic, placement of lines and devices into the venous tree can present greater challenge than is often appreciated. Wires and tubes that have a point of origin outside the venous tree, and subsequently enter and traverse it to pass into the great veins of the thorax, often move relative to the veins and the veins can move relative to them. The position of distal tips, the proximity to venous walls, the forces upon the venous walls, and the stresses on the devices as they navigate junctions can often be predicted, as can the likely associated complications. Many clinicians learn venous device insertion techniques and “tricks of the trade” instinctively or from texts and mentors without appreciating the dynamic anatomical and physiological

Handbook of Vascular Motion DOI: https://doi.org/10.1016/B978-0-12-815713-8.00011-5

changes they are using to facilitate their tasks. Examples include: 1. Guiding a line from the cephalic vein through the junction with the axillary vein into the subclavian vein is often difficult owing to the sharp turn and passage through the clavipectoral fascia as well as the intermittent presence of valves at the distal end. The passage can be aided by abducting the arm between 80 and 130 degrees and the patient taking a maximal inspiratory effort as the device is advanced. Abduction reduces the acuity of the angle of the junction and deep inspiration transiently increases forward flow of blood helping carry the line forward. 2. Reducing the risk of cephalad passage into the ipsilateral jugular vein of a line inserted via the subclavian vein, and preferentially favoring its passage into the superior vena cava (SVC), is aided by having the patient turn the head maximally to either side and taking a deep inspiratory breath at the time that the device should be passing the jugular venous junction. The mechanical action reduces the caliber of the lumen of the

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jugular near its junction with the subclavian vein, and inspiration increases blood flow into the SVC carrying the line along with it. 3. Reducing the risk of later dynamic catheter tip migration into the right atrium, tricuspid valve, or right ventricle with associated dysrhythmias is aided by monitoring a continuous electrocardiogram while having patients maximally inspire and expire and moving the arm through abduction and adduction arcs at the time of peripherally inserted central catheter (PICC) insertion. In those patients in whom dysrhythmias occur, the PICC is pulled back by 2 cm and the maneuvers repeated to check that cardiac irritation is no longer evidenced. The aim of this chapter is to facilitate an understanding of the dynamic venous anatomy of the chest and its tributaries, common variants, and common complications of device insertion that can result.

UPPER BODY VENOUS ANATOMY The basic anatomy of the thoracic venous system including upper arms, lower neck, and upper abdomen is illustrated in Fig. 11.1 including some common (abnormal) variants. Within the chest, the veins may be categorized as: 1. Systemic veins carrying deoxygenated blood from the upper body and chest back to the right side of the heart. These veins may be further (somewhat artificially) subcategorized as: a. deep systemic: jugular, subclavian, brachiocephalic/innominate, SVC and b. superficial systemic: azygos, hemiazygos, paraspinal, internal thoracic, esophageal. 2. Pulmonary veins carrying oxygenated blood from the lungs to the left side of the heart

FIGURE 11.1

A simplified schematic illustration of the major central veins. Some of the more common abnormal variants are shown such as an anomalous pulmonary venous drainage (dotted red line) and how a left-sided persistent vena cava (dotted blue line) would most commonly occur through failure of involution of the embryonic anterior cardinal vein with drainage into the coronary sinus via a patent ligament of the left vena cava. From Gibson, F., Bodenham, A., 2013. Misplaced central venous catheters: applied anatomy and practical management. Br. J. Anaes. 110 (3), 333 346.

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UPPER BODY VENOUS ANATOMY

On each side of the body, the vertebral and external jugular veins drain into the subclavian vein. The subclavian and internal jugular veins subsequently join to form the brachiocephalic (also called innominate) vein. Finally, the left and right brachiocephalic veins join to form the SVC just behind the junction of the first right rib and the sternum. The SVC then runs caudad, anterior to the right main bronchus and right pulmonary artery before being enveloped in the pericardium and entering the right atrium. The azygos vein is formed from the union of ascending lumbar veins and right subcostal veins around the level of the first lumbar vertebra (L1). It is unilateral, runs posteriorly up to the mediastinum to the right of the vertebral column and behind the right main bronchus. It then arches anteriorly over the superior border of the bronchus to enter the posterior aspect of the SVC, effecting the joining of superficial and deep thoracic venous systems—the arch of the azygos vein. Anatomical variants include drainage into the right brachiocephalic or subclavian veins as well as into the intrapericardial SVC or directly into the right atrium. Multiple other venous tributaries enter the azygos vein throughout its course: esophageal, posterior right intercostal, right bronchial, tracheal, superior right phrenic, and pericardial veins from the right side of the vertebral column, in addition to the hemiazygos and accessory hemiazygos veins from the left side of the vertebral column. The azygos vein acts as an alternative conduit for blood from the lower body to the heart via the SVC when occlusion of the inferior vena cava (IVC) occurs. Indeed, around 0.5% of the population have congenital absence of the hepatic portion of the IVC, with the IVC instead bypassing the liver to enter the azygos vein thereby draining into the SVC, and the liver draining directly into the right atrium by the hepatic veins (Fig. 11.2). Equally, in SVC syndrome, where there is obstruction of blood

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FIGURE 11.2 A portal venous phase computed tomography image demonstrating interruption of the inferior vena cava with azygos continuity. The azygos vein is markedly distended (black arrow). Courtesy of Dr. Abdallah Al Khateeb, Radiopaedia.org, rID: 43635.

flow from the SVC into the heart due to external compression or internal obstruction (usually thrombus but occasionally due to foreign body or stenosis), the azygos venous system is the most important route for decompression of the SVC with either anterograde flow if SVC obstruction is proximal to entry of the azygos vein into the SVC or retrograde flow if the SVC obstruction is distal. Another relatively common anomaly of thoracic venous anatomy is the persistence of a left-sided SVC (Fig. 11.3). An estimated 0.3% of the general population have persistence of their left-sided SVC and of these, 80% have bilateral SVCs. The frequency rises 10-fold in patients with congenital heart disease, especially those with atrial septal defects. Where bilateral SVCs exist, the right usually drains directly into the right atrium. A more important consideration is where a persistent left SVC drains to: Whereas 92% drain into the right atrium via the coronary sinus, 8% drain into the left atrium (Higgs et al., 1998).

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central venous lines in the upper body. Namely, air embolism or thromboembolism may cause cerebrovascular accidents or embolic, ischemic injuries to end organs that would not occur with right-sided lines in the absence of a patent foramen ovale—the lungs normally filter out air and other embolic materials.

CHANGES IN VENOUS ANATOMY WITH POSTURE

FIGURE 11.3 Persistent left-sided superior vena cava illustrated by the left paramediastinal passage of pacing wires (white arrow). An estimated 0.3% of the population have this venous abnormality. Courtesy of Prof Frank Gaillard, Radiopaedia.org, rID: 8965.

Drainage of a left SVC via the coronary sinus into the right atrium is not necessarily a problem; many consider it an acceptable practice to leave a central venous drug delivery catheter terminating in the lower left SVC. However, if it is left in too close proximity to a narrow coronary sinus, it may cause occlusion or dysrhythmias. Placement of a pulmonary artery flotation catheter via this route, traversing the coronary sinus, is particularly hazardous; the benefits must be weighed against the risks of thrombosis, dysrhythmias, and hypotension. Drainage of a left SVC into the left atrium creates a shunt. However, it is not always recognized; unless the percentage of blood flow returning deoxygenated blood from the left upper body is sufficiently high, the reduction in arterial oxygen saturation may be minor. If left atrial drainage of a left SVC is not recognized, significant risks arise from left-sided

The influence of posture on the degree of venous distension in the upper body veins has been recognized for centuries: The medical art of assessing jugular venous pressure requires that the patient recline on an examination surface with the legs horizontal, parallel to the ground, and the upper body at an angle of 45 degrees to the horizontal, bending at the hips. At this angle, the site of the pulsatile venous distension observed in the internal jugular vein affords an estimate of the intravenous pressure and is used to derive estimates of intravascular filling, as well as myocardial and tricuspid valvular function. If the patient reclines too far, e.g., only 30 degrees to the horizontal, the jugular venous pressure will be overestimated. Conversely, sit too upright and the jugular venous pressure will be underestimated. The dynamic effect of the posture on the volume of blood in the upper body and chest is easily demonstrated (Fig. 11.4) and therapeutically utilized in a variety of clinical situations. In otherwise cardiovascularly well patients having implanted central venous access devices such as portacaths or PICCs, it is readily apparent that access to the internal jugular, subclavian, or axillary veins is facilitated by those veins lying at or below the level of the heart, with gravity aiding increased pressure within and subsequent filling and distension of the veins. Unless in right heart failure, operators have their patients lie flat or even in

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FIGURE 11.4 Two ultrasound images of the left internal jugular vein in a healthy nonfasted man in his late 20s at end expirations in a sitting position at 45 degrees (left) and lying supine at 180 degrees (right). The center arrows indicate the selected focal points of the ultrasound beam in a zone 0.5 cm across. The vein collapses approximately 40% in maximum anteroposterior diameter on sitting. With permission of and thanks to Dr. Gurmeet Sani.

head-down postures to aid filling of the veins and ease of access to them during Seldinger wire placement. In cardiovascularly unwell patients such as those with congestive cardiac failure, the dynamic effects of posture also come into play. When a patient lies flat, the veins of the chest fill as a result of the increased pressure gradient between the lower limbs and right atrium, compared to the standing posture. This increased pressure leads to increased filling of the right atrium and thus increased right ventricular end-diastolic volume. This, in turn, increases the stroke volume and pushes more blood into the lungs, in turn increasing pulmonary venous return to the left heart. The overall volume of intrathoracic blood and the left ventricular preload increases. If the left heart is unable to push the additional blood forward, congestion results with back pressure into the lungs, causing development of pulmonary edema.

Patients with cardiac failure generally derive increased benefit from sitting up compared to lying flat. Orthopnea describes the development of dyspnea on lying flat. A crude assessment of the severity of cardiac failure is derived from the number of pillows a patient requires to elevate the head above the level of the mattress in order to avoid dyspnea; “fourpillow orthopnea” implies more severe cardiac failure than “two-pillow orthopnea.” Sitting up causes blood to pool in venous capacitance vessels of the legs under the influence of gravity. This, in turn, reduces venous return to the heart, intrathoracic blood volume (ITBV), and myocardial preload. In a study group of anesthetized patients, the reduction in ITBV on sitting from lying supine was 14%, by causing relative filling of venous capacitance vessels, despite fluid loading designed to reduce the postural effects of sitting (Buhre et al., 2000). An associated fall in

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cardiac output of 24% was noted. In a much earlier study with less fluid loading but bandaging of the legs in an attempt to reduce venous capacitance, a fall in cardiac output of 37% was noted when anesthetized patients were moved to the sitting position, implying a greater magnitude of effect in the absence of fluid loading; however, ITBV per se was not measured (Dalrymple et al., 1979). The degree to which anesthesia may have exaggerated a normal physiological response to a postural change in these studies is difficult to determine. While a degree of vasodilatation is normal under general anesthesia, fluid loading and mechanical reduction of venous capacitance would be expected to counterbalance these effects.

RESPIRATION AND ITS EFFECTS ON VENOUS CALIBER Positional changes of the veins relate predominantly to the diaphragm moving caudad on inspiration and cephalad on expiration, and to a lesser extent on chest wall movements. In addition to the vessel position, venous caliber also changes dynamically throughout the respiratory cycle. The caliber is determined by the dynamic interplay of intrapleural, intraabdominal, and intravenous pressures. As such, posture, intravascular filling state, and ventilatory state all affect the expected vessel caliber. The effects of the respiratory cycle on venous volume and flow in the chest vary with multiple actors: 1. predominantly chest wall (intercostal and accessory muscle) breathing versus predominantly diaphragmatic breathing; 2. posture—supine versus erect body posture; 3. negative pressure ventilation versus positive pressure ventilation; 4. intravascular filling state; 5. myocardial function and dysfunction; and 6. body habitus

The effects of the ventilatory state are relatively complex in their influences—patients can be breathing spontaneously unassisted or have mechanically assisted breathing. Not uncommonly, they are anesthetized, lying in a supine position, and have mechanically assisted ventilation applied at the time of venous device insertion, often through the application of positive pressure to the lungs. Shortly thereafter, they are conscious and breathing spontaneously through the generation of negative intrathoracic pressures. In addition, they tend to move from a supine to a sitting or erect position. With mechanically assisted breathing, the assist may come from either a positive pressure applied to the airways (common) or a negative pressure applied to the outside of the chest (uncommon—cuirass/iron lung), or both. Mechanically assisted breathing may be entirely spontaneous in origin or have a mixture of patient-initiated breaths and machine-initiated breaths or have entirely machine-initiated breaths. In each instance, the expected venous caliber seen at the different stages of the respiratory cycle at a given level of intravascular filling will alter. At its simplest, during spontaneous, unassisted breathing, the calibers of the major systemic veins in the upper body reduce on inspiration and increase on expiration (Fig. 11.5). This effect is exaggerated in erect and semierect postures, reduced on lying supine, and may be negated in a head-down posture. During ventilator-initiated, positive pressure ventilation, the opposite occurs: On inspiration, the calibers of the veins increase and on expiration, they decrease. Spontaneous respiration results from movements of the chest wall and diaphragm that, in turn, lead to changes in the volume of the thoracic cavity. The inside of the ribcage and mediastinum is lined by a continuous membrane, the parietal pleura. At the points of the branches of the bronchial tree and pulmonary

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FIGURE 11.5 Two ultrasound images of the left internal jugular vein of a healthy male volunteer lying supine at the end of maximal inspiration (left) and end expiration (right)—at the end of maximal inspiration, the vein can be seen to have collapsed more than 50% in maximal anteroposterior diameter. The center arrows indicate the selected focal point of the ultrasound beam in a zone 0.5 cm across. With permission of and thanks to Dr. Gurmeet Sani.

vessels exiting their origin within the mediastinum to move peripherally into the chest cavity, the parietal pleura reflects back on itself to cover the outside of the lungs as the visceral pleural. Between the two layers of pleura lies a potential space normally containing a few milliliters of lubricant pleural fluid. On normal inspiration, as the thoracic cavity expands, expansion of the potential space lying between the parietal pleura on the inside of the ribcage and the visceral pleura on the outside of the lungs also occurs. The elasticity of the lung tissue opposes their outward expansion while the negative pressure generated in the pleural potential space produces a counteracting force leading to lung expansion and a transference of the negative pressure to the blood vessels and airways within the lung substance. This negative pressure is also transferred to the structures within the mediastinum and is estimated by the measurement of esophageal pressure using a transducer lying in the esophagus.

During respiration in supine patients, the diaphragmatic excursion of up to 7 cm (normal 0.9 1.6 cm in quiet respiration) may occur (Cohen et al., 1994; Boussuges et al., 2009). Together with chest wall expansion, lung volumes may increase fivefold from resting values, and intrapleural pressures fall from 23 to 210 cmH2O (22.2 to 27.4 mmHg) with larger breaths. If the maximal respiratory effort is employed, the volume and pressure changes are more marked still. Central venous pressure plots are shown for normal spontaneous respiration, spontaneous respiration with partial inspiratory obstruction, spontaneous respiration with partial expiratory obstruction, and intermittent positive pressure ventilation (Fig. 11.6). During positive pressure ventilation, the opposite effects are seen. Movement of the diaphragm downward and the chest wall outward occurs via the application of a positive pressure to the lungs, which have to generate a

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+5 mmHg

0 mmHg

Inspiration

Expiration

Inspiration

–5 mmHg

Inspiration Normal spontaneous respiration

Expiration

Inspiration

Spontaneous respiration with partial inspiratory obstruction

+5 mmHg

0 mmHg

Inspiration

Expiration

Inspiration

Inspiration

Expiration

Inspiration

–5 mmHg

Spontaneous respiration with partial expiratory obstruction

Intermittent positive pressure ventilation

FIGURE 11.6

Changes in central venous pressure during the respiratory cycle during normal spontaneous respiration (top left), during spontaneous respiration with partial obstruction during inspiration (top right), during spontaneous respiration with partial obstruction on expiration (e.g., asthma) (bottom left), and during normal mechanically assisted positive pressure ventilation (bottom right).

transpleural pressure sufficient to push against the inward elastic forces of the lungs and resistive forces of the chest wall, as well as those of the abdominal contents pushing cephalad against the diaphragm. In a normal healthy 70 kg adult, this force may be relatively modest—with pressures of 10 cmH2O (7.4 mmHg) sufficing to produce changes in the volume of 500 600 mL. However, in morbidly obese patients where chest wall resistance (secondary to the weight of adipose tissue) is increased and abdominal mass resists caudad diaphragmatic motion, airway pressures as high as 35 cmH2O (25.7 mmHg) may need to be applied to expand the lungs and achieve similar tidal volumes. This pressure is also applied across the capillaries, pulmonary arteries, and intrathoracic veins, resulting in reduced forward blood flow in inspiration. Furthermore, as high positive end expiratory pressures are required to prevent the collapse of dependent lung areas at the end of expiration, end

expiratory pressures are often kept deliberately high: 15 cmH2O (11 mmHg) would not be unusual. In consequence, higher thoracic venous and pulmonary arterial pressures are required to minimize venous collapse, alveolar capillary collapse, and shunting. The effects of spontaneous respiration on the venous pressure and volume can be exaggerated by obstructing the airway during respiratory effort. Obstructing the airway on inspiration will result in exaggeratedly negative intrathoracic and, therefore, thoracic venous pressures. Obstructing the airway on expiration will similarly result in significantly increased intrathoracic pressures and therefore thoracic venous pressures (Fig. 11.7)—this “Valsalva maneuver” is used to enlarge veins for central venous cannulation in patients with reduced venous filling where a head-down posture would not be tolerated. In patients with obstructive sleep apnea, these changes would be expected to occur routinely during obstructed breathing.

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FIGURE 11.7 Two ultrasound images of the left internal jugular vein in a healthy nonfasted man in his late 20s lying supine at maximal inspiration (left) and maximal expiratory effort against an obstructed airway (Valsalva maneuver, right). The center arrows indicate the selected focal point of the ultrasound beam in a zone 0.5 cm across. The vein collapses to approximately 2 mm in maximum anteroposterior diameter at the maximal inspiratory effort and expands to around 9 mm at the maximal expiratory effort. With permission of and thanks to Dr. Gurmeet Sani.

PATHOLOGICAL CONDITIONS AND VENOUS DEVICES A variety of pathological and pathophysiological abnormalities can change both the anatomical position and the caliber of the veins. Acute pathologies such as acute severe asthma (breath-stacking and chest hyperinflation), pneumothorax, tension pneumothorax (mediastinal shift and chest hyperinflation with lung compression), hemothorax, phrenic nerve disruption (ipsilateral hemi-diaphragmatic paralysis), and cardiac tamponade all result in rapid changes in normal vessel motion and/or caliber and/or position. Chronic pathologies such as cor pulmonale with pulmonary hypertension, right ventricular failure, and tricuspid regurgitation similarly change normal venous pressures during the respiratory cycle. One classic example is Kussmaul’s sign of a rising

jugular venous pressure on inspiration when it would normally be expected to fall. While these facts may be interesting in and of themselves, there is a significant clinical relevance to understanding both normal dynamic venous anatomy and pathophysiologically altered anatomy. Medical personnel place a multitude of devices (Fig. 11.8) into or through the thoracic venous tree to facilitate drug administration, pressure monitoring, cardiac output monitoring, central venous oxygen saturation monitoring, blood sampling, cardiac pacing or defibrillation, and clot thrombolysis. In addition, devices are implanted to impede distal clots migrating centrally (central venous filters) and to repair leaks or manage stenosis (stents). Those unfamiliar with the anatomy and its changes are more likely to struggle during device placement and cause both immediate and later

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Anjiojets Catheter directed therapy (CDT) lines Caval filters Central lines Dialysis lines Drumcaths Hickman lines Implanted cardiac defibrillators Midline catheters PAFC introducers PAFC catheters Pacemakers Pacing introducer

Caval filter

Pacemaker

Dialysis lines (temporary)

Pulmonary artery flotation catheter

Hickman line

PICC line

PICCs Portacaths SvO2 catheters SjO2 catheters Trellis catheters Venous stents Portacath

FIGURE 11.8

Venous stent

Trellis catheter

List and pictures of a variety of venous access lines and devices.

inadvertent complications to patients than are those aware of normal and pathophysiological changes that occur during respiration, normal postural changes, and in commonly encountered clinical conditions. The types of devices placed into the venous tree vary in size, composite materials, stiffness, outer coating, and distal tip characteristics (Curelaru et al., 1983; Bersten et al., 1988). These together with venous anatomical characteristics such as site of insertion, intravenous route of passage, and site of distal termination are all related to the nature and frequency of development of well-recognized complications such as venous thrombosis, venous occlusion, venous stenosis (Agarwal et al., 2007), allergy, venous perforation, right atrial perforation, cardiac tamponade (Collier et al., 1998), displacement/migration, malposition, catheter fracture, intimal integration, and cardiac dysrhythmias. Less common complications such as left atrial perforation also

share some of the same predisposing factors (Wong et al., 2016). Other complications such as infection, hemorrhage at the insertion site, and device failure (luminal occlusion, displacement, increased pacing impedance) are also recognized but are less related to the venous anatomical characteristics. For example, device infection relates to the insertion technique, the characteristic of the device coating (antimicrobial vs standard), and attention to hygiene in the area of insertion before, during, and following insertion. The intravenous devices that commonly lie within the thoracic venous tree are generally of four types: 1. Devices fixed at their distal end and proximal end: permanent pacemakers and implantable cardiac defibrillators. As the line is fixed at both ends, it is likely to rub against the venous wall and may alter the normal venous deformations during the respiratory cycle (Fig. 11.9).

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PATHOLOGICAL CONDITIONS AND VENOUS DEVICES

235 FIGURE 11.9 A pacing wire is shown during insertion via the left subclavian vein. The wire has been fixed at the insertion site and is visualized on gentle inspiration (left) and expiration (right). Note the change in contour of the veins and slight elevation of the wire tip within the superior vena cava on inspiration compared with expiration. Images reproduced with patient permission and captured by Prof. M William.

2. Devices fixed at their proximal end but not fixed at their distal end: portacaths, Hickman lines, PICCs, temporary and permanent venous dialysis lines, temporary transvenous pacing wires, standard central venous catheters (CVCs), and central venous introducer catheters providing access for placement of temporary pacing wires and pulmonary artery flotation catheters. Provided these lines are sufficiently compliant, little alteration in normal venous deformation with respiration would be expected although movement of the line or line tip against the venous wall may occur as the vein moves around the device. With less compliant catheters, there may be recurring abrasion of the catheters against the venous walls with the natural movements of the veins during the respiratory cycle. This is most notable for devices entering the venous circulation via the left internal jugular (LIJ) and subclavian veins that follow a path to the right atrium; less notable are those entering via the right internal jugular vein with a much straighter route to the atrium. Recurrent abrasion may cause inflammation with vessel wall hypertrophy and stenosis, or thrombosis at the sites of abrasion. It is desirable that the last few centimeters of the catheter and catheter tip lie parallel to the vessel wall in

which the catheter terminates. Where tips are recurrently abutting a vein at an acute angle ( . 40 degrees) during normal respiratory movement, the risk of perforation may rise (Booth et al., 2001; Stonelake and Bodenham, 2006). 3. Devices with temporary fixation near their distal end: Pulmonary artery flotation catheters traverse the central venous system and the right heart to terminate in the pulmonary artery. The distal tip is usually “free-floating” but can be temporarily fixed within the pulmonary arterial tree by the inflation of a balloon just proximal to the tip—this braces the end of the catheter (ideally centrally) within the pulmonary arterial lumen and disrupts the continuity of the bloodstream in the pulmonary artery. The pressure on the distal side of the balloon is taken to reflect the pulmonary venous and left atrial pressures as it forms a continuous column of blood from catheter tip to left atrium, and that column is now isolated from normal pulmonary arterial pressure and flows by the inflated balloon occluding the artery. Another example of this type of device is the Trellis device used to perform pharmaco-mechanical thrombolysis to manage venous thrombosis. This uses both proximal and distal balloons to isolate thrombus within the venous

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lumen that is subsequently subjected to both thrombolytic pharmacotherapy and mechanical maceration. 4. Devices that are entirely contained within the vein and are “fixed” at their point of deployment: vena cava filters and venous stents. These are expected to move with the segment of vein they are in during the respiratory cycle but may displace if incorrectly deployed or where venous diameter increases beyond that of the device, for example, during Valsalva maneuver. These devices can be both directly and indirectly thrombogenic and may also directly or indirectly (via associated thrombus formation) cause later venous stenosis (Stein et al., 2004).

effects of inspiration and erect posture may cause even more significant elevation of catheter position. The change is more marked in obese patients, women, and in lines entering via the subclavian vein (compared with jugular venous entry) (Wyschkon et al., 2016). This may account for some of the marked migrations of catheter tip positions reported where initial post-insertion radiological confirmation of tip position in the lower SVC is replaced by relatively marked malposition days or weeks later. Examples of migration within the venous tree include but are not limited to:

CENTRAL LINE MOVEMENTS WITH RESPIRATION AND POSTURAL CHANGE

Migrations to sites outside the venous system include but are not limited to:

As the diaphragm rises and falls, intravenous devices that are not fixed at their distal end float freely inside the vascular compartment with only the proximal end fixed at the point of skin and/or venous insertion entry. On normal inspiration, the diaphragm descends, elongating the SVC and superior mediastinum but not the distance between the superior and inferior cava-atrial junctions. Thus the SVC moves relative to the tip of the device. On average, there is a mean movement of around 9 mm between inspiration and expiration for central venous lines entering the thoracic venous system from internal jugular or subclavian veins (range 0 25 mm) when measured in a supine position during spontaneous respiration (Pan et al., 2013). As most line tips move cephalad when the patient moves from supine to erect postures as the diaphragm falls with the postural reduction of upward pressure in the diaphragm from the abdominal contents (Nazarian et al., 1997), the combined

1. SVC to LIJ (Oliver et al., 2017), 2. SVC to contralateral subclavian to a site of insertion (author experience), and 3. SVC to azygos (Talari et al., 2018).

1. the mediastinum (Shah et al., 2014), 2. the pleural space (Maisniemi and Koljonen, 2006), 3. the pericardial space (Azevedo et al., 2018), and 4. the left atrium (Wong et al., 2016). Migration within the venous tree is particularly seen with soft compliant catheters such as PICC lines or portacaths; the tip can rise up the vessel wall on inspiration and enter a tributary vein. On expiration, the tip may remain lodged in the tributary vein and the proximal portion bend in a loop akin to a hockey stick. Initially, no harm may arise but the tip may act as a partial occlusion of the narrower tributary vein leading to thrombus formation, inflammation, or perforation—particularly where irritant drugs are being administered via the line. The range of movement seen with respiration and posture may be affected by patient height, abdominal mass, intraabdominal pressure, and scale of diaphragmatic excursion; the degree of diaphragmatic excursion correlates

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CENTRAL LINE MOVEMENTS WITH RESPIRATION AND POSTURAL CHANGE

well with the degree of tip movement with respiration. On lying supine, a morbidly obese patient can have marked increase in the upward pressure on the diaphragm and with consequently reduced respiratory excursion and falling tidal volumes. In obese (mean body mass index (BMI) 46.8) subjects, end expiratory mean esophageal pressures (at functional residual capacity) were 5.2 cmH2O sitting and 14.0 cmH2O supine, while in non-obese (mean BMI 23.2) subjects, end expiratory mean esophageal pressures were 22 cmH2O sitting and 5.4 cmH2O supine (Steier et al., 2014). Even when the position of the tip of a line does not move greatly with respiration, the shape of the veins within the chest alters slightly and can result in increased tension of stiffer lines or wires against the vessel wall and increased abrasion—probably one of the reasons that the development of venous stenosis is so common following line insertion via the thoracic great veins. The change in venous shape with respiration is illustrated in Fig. 11.9. PICC lines inserted via upper arm veins also demonstrate tip movement within the central veins during inspiration and expiration. One recent study of 123 patients demonstrated a mean caudad migration of 12.3 mm (range

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2.3 mm cephalad to 26.9 mm caudad) from rest position on full expiration of the subject (De Carvalho and Eagar, 2018). In addition, PICC tips move with adduction and abduction of the arm and may result in dysrhythmias if caudad migration causes irritation of the right atrium, tricuspid valve, or right ventricle (Basu et al., 2015). The same 123 patients studied above also demonstrated a mean migration (from control position) of 12.9 mm on adduction of the arm (range 2.3 mm cephalad to 28.1 mm caudad) and 6.5 mm on abduction of the arm (range 12.1 mm cephalad to 25.1 mm caudad) (De Carvalho and Eagar, 2018). A similar study was conducted on PICC tip migration during the same phase of respiration when the arm was moved from a 90-degree abducted position to an adducted position parallel to the chest wall; the tip migrated an average distance of 21 mm, again with most moving caudad but some moving cephalad (Forauer and Alonzo, 2000). Movement tends to be greater in right arm than left arm PICCs. Fig. 11.10 shows PICC migration with respiration and arm movement. As the direction of the tip movement with respiration and arm motion is unpredictable at the time of insertion, it is useful both to

FIGURE 11.10 Example of peripherally inserted central catheter tip movement relative to carina: (A) control position, (B) expiration, (C) adduction of arm, and (D) abduction of arm. In this example, abduction results in movement of the tip into the right atrium. From De Carvalho, B.R., Eagar, G.M., 2018. Immediate post-insertion tip migration of peripherally inserted central catheters dependent on arm position and depth of inspiration. J. Med. Imaging Radiat. Oncol. 62 (3), 324 329.

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(1) move the arm from abducted to adducted and (2) ask the patient to maximally inspire and expire at the time of insertion to check tip position on the X-ray image intensifier or echocardiogram, or to check that ectopic beats are not seen on the electrocardiogram if real-time imaging of the tip is not employed. The author commonly witnessed dysrhythmias during pediatric PICC insertion on moving the arm or maximal breathing, and routinely tested for this before final adjustment and fixation.

DEEP VERSUS SUPERFICIAL FIXATION AND THE EFFECTS OF BODY HABITUS The tip of venous lines may move independently of both respiration and arm movement for lines entering the jugular or subclavian veins according to where the proximal end is fixed and the posture of the patient at the time of fixation. Whereas implanted cardiac pacemaker units can be fixed relatively deeply and close to the chest wall, thereby minimizing movement of the device and the wires relative to the subclavian vein through which the wires enter, portacaths are classically placed

relatively superficial to the chest wall in order to facilitate easy placement of access needles through the skin and into the devices at times of chemotherapy delivery. However, this presents major challenges in obese patients or where the tissues to which the port is fixed are very mobile. If the port is fixed to relatively superficial tissues, there can be significant mobility of these tissues over the chest wall with postural changes—for instance, breast tissue may lie lateral to the chest wall in a supine patient but anterior to the chest wall when the patient sits. Equally, the effect of gravity on mobile tissues may pull the port caudad relative to the vein entry point. This, in turn, pulls the catheter further out of the vein with an absolute rise of the tip in the SVC, in addition to the relative rises caused by stretching of the SVC on inspiration and fall of the diaphragm on standing. The combination can result in the marked rise and displacement of the tip from the lower SVC to as high as the innominate veins. It can also result in catheter torsion and kinking (Fig. 11.11). To overcome these issues, experienced operators may choose either to (1) fix the port onto deeper tissues with far less movement relative to the chest wall and thus less catheter

FIGURE 11.11 A portacath placed in a 70-year-old woman with BMI 33 kg/m2 for the administration of chemotherapy. (A) At the time of placement, the catheter tip lies in the right atrium. (B) A later image shows cephalad displacement of the catheter tip with looping of the extravenous portion of the catheter due to excessive tissue motion and abducted arm position. From Aberle, D., Charles, H., Hodak, S., O’Neill, D., Oklu, R., Deipolyi, A.R., 2017. Optimizing care for the obese patient in interventional radiology. Diagn. Interv. Radiol. 23, 156 162.

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COMPLICATIONS OF DEVICE PLACEMENT

movement between port and venous entry site or (2) place the catheter in far deeper at the time of initial placement, deliberately citing the end in the right atrium (Kowalski et al., 1997). Both have their challenges; the former is less comfortable for the patient and makes accessing the port more difficult, while the latter increases the risk of both cardiac dysrhythmias and atrial perforation.

COMPLICATIONS OF DEVICE PLACEMENT The planned duration of device placement may be short term (,14 days), medium term ( . 14 days), or permanent. The risks of complications—other than acute hemorrhage, acute right atrial perforation/cardiac tamponade, and cardiac dysrhythmias—increase with the duration of device implantation. However, complications that are normally seen early following insertion can also occur later. Right atrial perforation may occur weeks or even years following transvenous device placement, and may occur with rigid devices such as pacing wires (Velavan and Chauhan, 2003) or soft devices such as silicone catheters (Banerjee et al., 2010). Although placement of totally implantable venous access devices increasingly occurs using percutaneous techniques under real-time ultrasound, early studies suggested that this technique was associated with more complications than those placed using open surgical cut-down (Di Carlo et al., 2010). However, later studies suggested comparable complication rates, with the exception of pneumothorax which occurs more frequently after percutaneous techniques. Furthermore, there is a suggestion that devices placed percutaneously had a lower medium and long-term failure rate than those placed using a surgical cut-down (Orci et al., 2014; Hsu et al., 2016). Of lines inserted percutaneously, those placed under real-time

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ultrasound guidance are associated with significantly fewer complications than those placed using anatomical landmarks without ultrasound. For lines placed using the internal jugular vein, a Cochrane meta-analysis in 5,108 patients found improved implantation success (97.6% vs 87.6%) and far lower complication rate (4% vs 13.5%) with ultrasound guidance (Brass et al., 2015). The ideal position of the tip of a CVC terminating within the thoracic venous system is a matter of contention and debate (Vesely, 2003). The optimum position should be determined by the suitability and design of the catheter for its particular purpose. However, for short-term lines placed emergently in a critical care environment, a degree of pragmatism is applied. If a morbidly obese patient has a great vein identified 6 cm beneath the skin in a perpendicular plane and an angle of approach of 45 degrees is used to access the vein in order to minimize the risk of kinking the catheter or stressing the vein at catheter entry point, around 8.5 cm of catheter will be expended just in the passage through subcutaneous tissues to reach the vein. As the prevalence of morbid obesity increases, these challenges are increasingly common. If the only catheters available to a team are traditional 16 and 20 cm catheters, the longer one will be used. With a 20 cm line, only 11.5 cm of the catheter will be in the venous system and the tip will lie where it lies. If a left approach has been used, this may be in the innominate vein, possibly abutting the lateral wall of the SVC (Fig. 11.12). This route is accompanied by a higher risk of complications (thrombosis and SVC perforation) and is accepted as a trade-off for the necessity of urgently securing central vascular access, administration of life-saving drugs, or performance of urgent hemodialysis. In less emergent situations, placement of more customizable lines under X-ray screening may be undertaken and a line with poor tip

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position would be replaced and optimized. It is worth noting that where a tip lies at an acute angle to the vein, it may not only perforate but has the potential to lead to a tear in the vein. The layers of the vein wall are organized longitudinally and thus a perforation may extend leading to a larger than anticipated defect (Gibson and Bodenham, 2013) with major hemorrhage resulting.

FIGURE 11.12

Despite the use of a 20 cm temporary dialysis line via a left internal jugular approach, the tip lies in a poor position at a too acute angle to the superior vena cava (black arrow). While such a line may be used in the emergent acute phase of an admission, the line need will need to be moved within 24 hours to reduce the risk of superior vena cava perforation and line tip migration into the mediastinum.

While there is a general clinical preference for right internal jugular line placement in emergencies (there being fewer angles for the catheter to negotiate and a lower risk of complications such as venous stenosis, venous perforation, and thrombosis), in certain instances, the right internal jugular is unavailable for use due to anatomical problems (e.g., stenosis, thrombosis, or occlusion after previous use) or is deliberately kept free for insertion of other, more critically important, devices such as an extracorporeal membrane oxygenation cannula. Obesity presents significant challenges both to insertion and subsequent risk of catheter migration and other complications. In the above example, had the shorter 16 cm catheter been used, only 7.5 cm of the catheter would lie within the vein. For multilumen catheters where the proximal lumen may exit 5 cm from the tip, there is only 2.5 cm of the catheter between the venous entry site and the luminal exit into the vein. Postural movement or respiratory effort may well result in the catheter migrating that distance out of the vein with subsequent extravasation of potentially astringent drugs into the extravascular tissues. Tissue damage (Fig. 11.13) including skin loss and permanent nerve injury may result.

FIGURE 11.13 Extravasation of irritant drugs from the proximal lumen of a multilumen central line with secondary tissue necrosis 4 days after the event. The proximal lumen was believed to have migrated out of the vein following initial insertion. From Bronshteyn, Y.S., Bittner, E.A., 2017. Images in anesthesiology: examining the edges of extravasation. Anesthesiology 126, 716.

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UPPER LIMB DEEP VENOUS THROMBOSIS

Critical factors for long-term complication rates are: 1. The final resting place of the tip of the venous line in the venous circulation a. Catheters with their tips lying low in the SVC or right atrium have a lower risk of causing thrombosis compared to those with their tip lying in the subclavian, upper SVC, or azygos vein. This is likely due to the higher blood flow rates, the greater the proximity to the right atrium. The entire cardiac output passes through the right atrium and thus blood flow rates there equal cardiac output. Assuming normal venous anatomy, the farther one travels peripherally back along tributary veins, the lower the flow rates become. Where irritant drugs enter the circulation from catheters into areas of low blood flow, the high concentrations may lead to venous irritation, phlebitis, and thrombus formation. When drugs exit the catheters into areas of very high flow, the drugs are rapidly diluted and vessel irritation is therefore reduced. b. Conversely, catheters whose tips lie very centrally in the low SVC or right atrium have a higher risk of provoking cardiac dysrhythmias and atrial perforation/ pericardial tamponade. 2. The diameter of the line a. Multilumen, wider diameter PICCs have a higher association with upper limb deep vein thrombosis than narrower ones (Chopra et al., 2014). This is perhaps unsurprising as the blood flow rates in the veins of the arm are relatively low compared with central veins, and the combination of low flow rates and vessel wall irritation by large diameter lines that partially occlude the veins is likely to result in thrombus formation.

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3. The route taken by the line a. Basilic venous PICCs have significantly higher thrombosis risk than brachial venous PICCs (Marnejon et al., 2012). b. Left-sided venous PICCs have greater thrombosis risk than right venous PICCs (Marnejon et al., 2012). 4. The purpose of the line’s use a. PICC lines used for antibiotic therapy (especially vancomycin) and total parenteral nutrition are more likely to be associated with the development of thrombosis than those used for fluid administration (Marnejon et al., 2012). 5. The stiffness of the catheter and its tip a. Stiff tipped catheters are more likely to perforate vessels or the atrium. b. Soft catheters are more likely to kink, occlude, and migrate within the venous tree or migrate out of the vein. c. Stiff catheters are more likely to cause venous stenosis and more likely to fracture.

UPPER LIMB DEEP VENOUS THROMBOSIS Upper extremity deep venous thrombosis (UEDVT) is often initially asymptomatic (Fallouh et al., 2015) and historically has been characterized as enjoying a lower risk of causing symptomatic pulmonary thromboembolism (PTE) than lower extremity DVT (LEDVT). Recent evidence suggests that, at least in intensive care patients, this is not true and that UEDVT may have a higher incidence of PTE than LEDVT (Lamontagne et al., 2014). UEDVT may lead to long-term and often disabling sequelae; the functional impact on patients can be profound. UEDVTs are broadly classified as primary [Paget Schroetter syndrome (effort thrombosis), or idiopathic UEDVT] or secondary (thrombosis secondary to the venous

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catheter, malignant disease, or chemotherapy associated thrombosis). Paget Schroetter syndrome is usually associated with upper limb exercise leading to inflammation of muscle and perivascular tissues as well as inflammation of the vein in the axillary and/or periclavicular areas. This can lead to thrombosis and/or venous stenosis. Compression of the vein between the first rib and clavicle similarly results in stenosis and thrombosis (thoracic venous outlet obstruction). The ratio of primary-to-secondary UEDVT is approximately 1:4. Although often asymptomatic, PICC lines have been associated with UEDVT rates of up to 72% (Itkin et al., 2014). In a meta-analysis, postthrombotic syndrome was found to develop in 15% of all patients following UEDVT but in only around 8% of the patients with catheter-associated UEDVT (Thiyagarajah et al., 2017). However, in individual studies and case series, rates vary from 7% to 46% (Elman and Kahn, 2006). The symptoms commonly include upper limb edema, pain, reduced movement, burning sensations, skin thickening, and hyperpigmentation. Reduced function, reduced sleep secondary to pain, and reduced long-term quality of life are also described (Kahn et al., 2014). Where anticoagulation alone is the sole therapy for UEDVT, up to 50% of the patients may have postthrombotic syndrome at five years (Heron et al., 1999). Rarely, phlegmasia cerulea dolens (i.e., painful blue edema) has also been described and may be a precursor to the development of gangrene and loss of limb (Greenberg et al., 2016). Given the degree of disability that results from UEDVT followed by postthrombotic syndrome, active rather than conservative management of the DVT is recommended. Anticoagulation, catheter-directed thrombolysis, and combined pharmaco-mechanical thrombolysis have all been advocated (Carlon and Sudheendra, 2017). It is not without some irony that complex intravenous devices such as

the Trellis or Angiojet catheters have been necessitated to treat the complications and long-term sequelae of much simpler intravenous devices such as PICC lines. In primary UEDVT, there is a suggestion that surgical treatment with or without thrombolysis may be required in addition to anticoagulation to improve long-term outcomes (Vasquez et al., 2017).

CHALLENGES OF VASCULAR ACCESS FOR RENAL REPLACEMENT THERAPIES In order to conduct renal replacement therapy using hemodialysis or hemodiafiltration, vascular access is required that can easily support flow rates of the blood of 200 500 mL/ min across the membrane. Blood flow rates ,250 mL/min have been associated with poorer outcomes independently of treatment time and dose, meaning that stenosis, thrombosis, and occlusion are of critical concern for dialysis efficacy. Three types of vascular access for hemodialysis are commonly used:

Arteriovenous Fistulae Arteriovenous fistulae (AVFs) are generally recommended ahead of other options as they are associated with lower complication rates (thrombosis, stenosis, occlusion, infection) and higher longevity. However, high technical skill is required to fashion AVFs and this is increasingly challenging in multimorbid elderly and obese patients with significant atheromatous and calcific vascular disease, reduced vessel compliance, and vessels lying deep under adipose tissue. In many instances, the renal failure is a consequence of underlying diabetes and associated disease. When the technique of AVF formation was first described in 1966 by

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Brescia et al. (1966), the patients tended to be far younger, with renal failure secondary to glomerulonephritis. AVFs are usually fashioned in the nondominant arm to reduce impediment to normal living. The preferred site for AVF formation is the distal arm at the wrist (radio-cephalic fistula) as distal limb ischemia is less likely as is excessively high fistula flow rates that may lead to cardiovascular problems. However, the smaller caliber vessels at the wrist increase the risks of inadequate vein maturation, thrombosis, stenosis, occlusion, and insufficient fistula flow rate. More proximal AVF formation in the upper arm with either brachiocephalic or brachiobasilic fistulas is second in preference. With larger diameter vessels, time to maturation tends to fall and one-year patency rates tend to be higher, but steal syndromes and excessive fistula flow are more commonly problematic. In addition, the vascular motion due to respiration and neck and upper arm movement, as described in this chapter, needs to be considered for long-term AVF viability.

Arteriovenous Grafts Arteriovenous grafts (AVGs) join the artery and vein, usually in the upper arm. These are typically less complicated to fashion than AVFs as the graft can join two vessels a moderate distance apart without having to mobilize and move the vessels. They may be made of synthetic (e.g., PTFE, Gore-Tex, Dacron) or biological (e.g., human, bovine) materials. Both synthetic and biological grafts tend to induce stenosis in the vessels they join, in part due to compliance mismatch. Thrombosis may occur secondary to stenosis, resulting in reduced blood flow and hypotension, which is far more common in AVGs than AVFs. Patency rates can be improved by making the anastomoses angles less perpendicular (i.e., more parallel with the native vessels), decreasing turbulent

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flow and intimal hyperplasia. Surgeons should be cognizant of AVG location relative to the elbow joint and amount of slack in the graft to ensure the ability to accommodate joint motion.

Central Venous Catheters CVCs tend to be of two types: 1. Temporary venous dialysis lines that may either comprise one line with integrated dual (or triple) lumens or two single lines (e.g., the Tessio system) placed to facilitate acute or emergency dialysis. Temporary lines can also occasionally be placed pending the creation of long-term AVF or AVG in patients with end-stage renal failure going onto long-term dialysis. 2. “Permanent” venous dialysis lines usually comprising dual-lumen lines with a Dacron (or other material) cuff that integrates into the subcutaneous tissues, presenting a physical barrier to the ingress of skin flora and other bacteria down the outside of the catheter and into the venous system. There are short-term advantages to CVCs, but also higher long-term risks. Their relative simplicity to place means they can be inserted on short notice by a variety of medical specialists including radiologists, nephrologists, and intensive care doctors without the need to wait for pre-placement surgical assessment and than an operating room appointment. There is no additional demand upon the cardiac output except during dialysis itself, and they can be used immediately following insertion without the need to wait on surgical site healing or fistula maturation. However, the higher risks are local and systemic infection, thrombosis, and venous stenosis as compared to AVFs or AVGs. In addition, they carry a risk of catheter migration with caval and atrial perforation described earlier in this chapter. These risks

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should not be taken lightly—patients with CVC dialysis access are 40% more likely to die of infection than those with AVF access.

CONCLUSION The veins of the upper body are incredibly mobile structures, with cross-sectional geometry, vessel lengths, and vessel paths influenced by respiration, Valsalva maneuver, blood volume, body posture, and upper extremity motion. Furthermore, these geometries and motions are affected by abnormal variations in venous anatomy, pathology, pathophysiology, and the imposition of artificial forces, such as from ventilators. These motions can complicate acute and long-term venous access and central line position, potentially causing vein wall irritation, thrombosis, stenosis, and wall perforations. However, these motions can also be leveraged to facilitate venous access by performing controlled respiration, body habitus, Valsalva, arm abduction or adduction, or neck turning during invasive procedures. While many tricks of the trade for venous interventions have been discovered and are commonly utilized, quantitative data are still lacking. The area is ripe for a revolution in upper body vein motion research.

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Bersten, A.D., Williams, D.R.G., Philips, G.D., 1988. Central venous catheter stiffness and its relation to vascular perforation. Anaesth. Inten. Care 16 (3), 342 350. Booth, S.A., Norton, B., Mulvey, D.A., 2001. Central venous catheterization and fatal cardiac tamponade. Br. J. Anaesth. 87 (2), 298 302. Boussuges, A., Gole, Y., Blanc, P., 2009. Diaphragmatic motion studied by m-mode ultrasonography: methods, reproducibility, and normal values. Chest 135 (2), 391 400. Brass, P., Hellmich, M., Kolodziej, L., Schick, G., Smith, A. F., 2015. Ultrasound guidance versus anatomical landmarks for internal jugular vein catheterization. Cochrane Database Syst. Rev. 1, CD006962. Brescia, M.J., Cimino, J.E., Appel, K., Hurwich, B.J., 1966. Chronic hemodialysis using venipuncture and a surgically created arteriovenous fistula. N. Engl. J. Med. 275 (20), 1089 1092. Bronshteyn, Y.S., Bittner, E.A., 2017. Images in anesthesiology: examining the edges of extravasation. Anesthesiology 126, 716. Buhre, W., Weyland, A., Buhre, K., 2000. Effects of the sitting position on the distribution of blood volume in patients undergoing neurosurgical procedures. Br. J. Anaesth. 84 (3), 3 54 357. Carlon, T.A., Sudheendra, D., 2017. Interventional therapy for upper extremity deep vein thrombosis. Semin. Interven. Radiol. 34 (1), 54 60. Chopra, V., Ratz, D., Kuhn, L., Lopus, T., Lee, A., Krein, S., 2014. Peripherally inserted central catheter-related deep vein thrombosis: contemporary patterns and predictors. J. Thromb. Haemost. 12 (6), 847 854. Cohen, E., Mier, A., Heywood, P., Murphy, K., Boultbee, J., Guz, A., 1994. Excursion-volume relation of the right hemidiaphragm measured by ultrasonography and respiratory airflow measurements. Thorax 29, 885 889. Collier, P.E., Blocker, S.H., Graff, D.M., Doyle, P., 1998. Cardiac tamponade from central venous catheters. Am. J. Surg. 176 (2), 212 214. Curelaru, I., Gustavsson, B., Hansson, A.H., Linder, L.E., Stenqvist, O., Wojciechowski, J., 1983. Material thrombogenicity in central venous catheterization II. A comparison between plain silicon elastomer, and plain polyethylene, long, antebrachial catheters. Acta Anaesthesiol. Scand. 27 (2), 158 164. Dalrymple, D.G., MacGowan, S.W., MacLeod, G.F., 1979. Cardiorespiratory effects of the sitting position in neurosurgery. Br. J. Anaesth. 51 (11), 1079 1082. De Carvalho, B.R., Eagar, G.M., 2018. Immediate postinsertion tip migration of peripherally inserted central catheters dependent on arm position and depth of inspiration. J. Med. Imaging Radiat. Oncol. 62 (3), 324 329. Di Carlo, I., Pulvirenti, E., Mannino, M., Toro, A., 2010. Increased use of percutaneous technique for totally implantable venous access devices. Is it real progress?

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A 27-year comprehensive review on early complications. Ann. Surg. Oncol. 17 (6), 1649 1656. Elman, E.E., Kahn, S.R., 2006. The post-thrombotic syndrome after upper extremity deep venous thrombosis in adults: a systematic review. Thromb. Res. 117 (6), 609 614. Fallouh, N., McGuirk, H.M., Flanders, S.A., Chopra, V., 2015. Peripherally inserted central catheter-associated deep vein thrombosis: a narrative review. Am. J. Med. 128 (7), 722 738. Forauer, A.R., Alonzo, M., 2000. Change in peripherally inserted central catheter tip position with abduction and adduction of the upper extremity. J. Vasc. Interven. Radiol. 11 (10), 1315 1318. Gibson, F., Bodenham, A., 2013. Misplaced central venous catheters: applied anatomy and practical management. Br. J. Anaes. 110 (3), 333 346. Greenberg, J., Troutman, D.A., Shubinets, V., Dougherty, M.J., Calligaro, K.D., 2016. Phlegmasia cerulea dolens in the upper extremity: a case report and systematic review and outcomes analysis. Vasc. Endovascular. Surg. 50 (2), 98 101. Heron, E., Lozinguez, O., Emmerich, J., Laurian, C., Fiessinger, J.N., 1999. Long-term sequelae of spontaneous axillary-subclavian venous thrombosis. Ann. Intern. Med. 131, 510 513. Higgs, A.G., Paris, S., Potter, F., 1998. Discovery of left sided superior vena cava during central venous catheterization. Br. J. Anaes. 81 (2), 260 261. Hsu, C.C., Kwan, G.N., Evans-Barns, H., Rophael, J.A., van Driel, M.L., 2016. Venous cutdown versus the Seldinger technique for placement of totally implantable venous access ports. Cochrane Database Syst. Rev. 21 (8), CD008942. Itkin, M., Mondshein, J.I., Stavropoulos, S.W., ShlanskyGoldberg, R.D., Soulen, M.C., Trerotola, S.O., 2014. Peripherally inserted central catheter thrombosis reverse tapered versus non-tapered catheters: a randomized controlled study. J. Vasc. Interv. Radiol. 25 (1), 85 91. e1. Kahn, S.R., Comerota, A.J., Cushman, M., Evans, N.S., Ginsberg, J.S., Goldenberg, N.A., et al., 2014. The postthrombotic syndrome: evidence-based prevention, diagnosis, and treatment strategies: a scientific statement from the American Heart Association. Circulation 130 (18), 1636 1661. Kowalski, C.M., Kaufman, J.A., Rivitz, S.M., Geller, S.C., Waltman, A.C., 1997. Migration of central venous catheters: implications for initial catheter tip positioning. J. Vasc. Interven. Radiol. 8 (3), 443 447. Lamontagne, F., McIntyre, L., Dodek, P., , et al.,Prophylaxis for Thromboembolism in Critical Care Trial Investigators; Canadian Critical Care Trials Group; Australian and New Zealand Intensive Care Society Clinical Trials Group. 2014. Non-leg venous thrombosis

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in critically ill adults: a nested prospective cohort study. JAMA Intern. Med. 174 (5), 689 696. Maisniemi, K.J., Koljonen, V.S., 2006. Tension hydrothorax induced by central venous catheter migration in a patient with burns. Br. J. Anaes. 97 (3), 423 424. Marnejon, T., Angelo, D., Abu Abdou, A., Gemmel, D., 2012. Risk factors for upper extremity venous thrombosis associated with peripherally inserted central venous catheters. J. Vasc. Access 13 (2), 231 238. Nazarian, G.K., Bjarnason, H., Dietz Jr, C.A., Bernadas, C. A., Hunter, D.W., 1997. Changes in tunneled catheter tip position when a patient is upright. J. Vasc. Interv. Radiol. 8 (3), 437 441. Oliver, J.J., Connor, R.E., Powell, J.R., Oliver, J.M., Long, B., 2017. Delayed migration and perforation of the jugular vein by a peripherally inserted central catheter. Clin. Pract. Cases Emergency Med. 1 (4), 384 386. Orci, L.A., Meier, R.P., Morel, P., Staszewicz, W., Toso, C., 2014. Systematic review and meta-analysis of percutaneous subclavian vein puncture versus surgical venous cutdown for the insertion of a totally implantable venous access device. Br. J. Surg. 101 (2), 8 16. Pan, P.P., Engstrom, B.I., Lungren, M.P., Seaman, D.M., Lessne, M.L., Kim, C.Y., 2013. Impact of phase of respiration on central venous catheter tip position. J. Vasc. Access 14 (4), 383 387. Shah, B.K., Tandukar, S.S., Shrestha, S., Sanchirico, P., 2014. A rare case of portacath migration into the mediastinum. West Indian Med. J. 63 (6), 676 677. Steier, J., Lunt, A., Hart, N., Polkey, M.I., Moxham, J., 2014. Observational study of the effect of obesity on lung volumes. Thorax 69 (8), 752 759. Stein, P.D., Kayali, F., Olsom, R.E., 2004. Twenty-one-year trends in the use of inferior vena cava filters. Arch. Intern. Med. 164 (14), 1541 1545. Stonelake, P.A., Bodenham, A.R., 2006. The carina as a radiological landmark for central venous catheter tip position. Br. J. Anaesth. 96 (3), 335 340. Talari, G., Talari, P., Parasramka, S., Mirrakhimov, A.E., 2018. Recurrent migration of peripherally inserted central catheter into the azygos vein. BMJ Case Rep. Available from: https://doi.org/10.1136/bcr-2017221184. Thiyagarajah, K., Ellingwood, L., Endres, K., Hegazi, A., Radford, J., Lansavitchene, A., et al., 2017. Postthrombotic syndrome and recurrent thromboembolism in patients with upper extremity deep vein thrombosis: a systematic review and meta-analysis of proportions. Blood 130 (Suppl. 1), 4724. Vasquez, F.J., Paulin, P., Poodts, D., Gandara, E., 2017. Preferred management of primary deep arm vein thrombosis. Eur. J. Vasc. Endovasc. Surg. 53 (5), 744 751. Velavan, P., Chauhan, A., 2003. An unusual presentation of delayed cardiac perforation caused by atrial screw-in lead. Heart 89 (4), 364.

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Vesely, T.M.J., 2003. Central venous catheter tip position: a continuing controversy. Vasc. Interven. Radiol. 14 (5), 527 534. Wong, K., Marks, B.A., Qureshi, A., Stemm, J.J., 2016. Migration of a central venous catheter in a hemodialysis patient resulted in left atrial perforation and thrombus

formation requiring open heart surgery. A & A Case Rep. 7 (1), 21 23. Wyschkon, S., Lo¨schmann, J.P., Scheurig-Mu¨nkler, C., Nagel, S., Hamm, B., Elgeti, T., 2016. Apparent migration of implantable port devices: normal variations in consideration of BMI. J. Vasc. Access 17 (2), 155 161.

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Inferior Vena Cava and Lower Extremity Veins Christopher P. Cheng Division of Vascular Surgery, Stanford University, Stanford, CA, United States

The inferior vena cava (IVC) and lower extremity veins are adjacent to the aorta and lower extremity arteries, respectively; however, due to the dramatically lower blood pressures and different vessel wall structures, the biomechanical motions are apt to be different. While venous stenting is one of the fastest growing fields in cardiovascular devices, so far there has been much more experience concerning endovascular interventions in the arterial circulation compared to the venous circulation. Many experts believe that peripheral venous stents are technologically about 10 15 years behind those of peripheral arterial stents. Analogously, we know as much about venous motion and deformations as we did about arterial motion and deformations about 10 15 years ago, which is to say, we know very little. That is why it will only take one chapter to review the deformations of the IVC and lower extremity veins while the corresponding arterial topics occupy three chapters.

Handbook of Vascular Motion DOI: https://doi.org/10.1016/B978-0-12-815713-8.00012-7

VEINS VERSUS ARTERIES In the systemic circulation, blood flows along the following path: heart-aorta-arteries-arterioles-capillaries-venules-veins-venae cavae-heart. Blood is pumped out of the heart in a pulsatile fashion and the elastic aorta and arteries help to continue pushing the blood forward by expanding and recoiling. As the blood continues on its path being driven by pressure, the pressure decreases as energy is lost to friction and heat. By the time the blood reaches the venous circulation, the pressure is dramatically lower than that of the arterial circulation. Simultaneously, by the time the blood passes through the arterioles and capillaries, the pulsatility experienced in the arteries has been damped nearly to zero, which means the venous system does not experience substantial cardiac-induced pressure changes. These differences in blood pressure and pressure pulsatility between the arteries and veins lead to dramatic differences in vessel morphology.

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© 2019 Elsevier Inc. All rights reserved.

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Since cardiovascular devices are only implanted in the larger arteries and veins, we will discuss the tissue structure only of these larger blood vessels. Veins and arteries are composed of the same three concentric layers from inner to outer (Fig. 12.1):

1. Tunica intima is the inner single layer of endothelial cells mounted on a layer of extracellular matrix. The endothelial cell layer is the signaling pathway through which the blood communicates with the rest of the vessel wall.

FIGURE 12.1 Arteries and veins both contain three layers: intima, media, and adventitia. As compared to the arteries (top left), veins (top right) typically have thinner walls, with relatively less media/adventitia thickness ratio. In addition, the veins lack much of the elastic fiber and membrane components that are in the arteries, which are present for the sake of propelling blood forward. Note the larger circumference and thinner walls of the veins as compared to the arteries (bottom). Adapted from https://en.m.wikipedia.org/wiki/File:2102_Comparison_of_Artery_and_Vein.jpg.

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2. Tunica media is the middle layer of smooth muscle cells and elastin. This muscular layer is responsible for controlling the caliber of the vessel, either by relaxing and increasing diameter or contracting and decreasing diameter. 3. Tunica adventitia is the outer layer of collagen and elastin. This outer layer is composed of tough connective tissue and contains the vasa vasorum, which is the blood supply for the blood vessel itself. While the three layers in veins and arteries have the same names and approximately the same types of cells and tissues, they contain different absolute amounts and proportions of these components due to their different blood pressure environments and functions. Veins typically have much thinner walls, with the medial layer constituting the main difference. The medial layer of veins contains much less smooth muscle and elastic tissue compared to the arteries because healthy veins only have to hold blood pressure of approximately 10 mmHg or less, while arteries typically need to contain blood pressures above 100 mmHg. Since blood pressure is so much lower in the veins, much less smooth muscle is needed to regulate the caliber of the vein. In addition, since there is much less cardiac-induced pulsatility in the veins, not as much muscular and elastic tissue is needed to deal with the pressure variation. Healthy arteries contain a lot of elastin, and hence elasticity, which works to provide an extra push to the blood with elastic recoil during diastole. And since arterial blood pressure is so high, even during diastole, this extra push is predominantly in the forward direction (although it can be retrograde in some cases). However, since the venous driving pressure is so low, vein valves are needed to prevent the backward flood of blood, especially in the lower extremities where venous return also needs to fight the downward force of gravity. Veins also have larger lumen diameters as compared to

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their corresponding arteries and hence have very low resistance to flow, which is necessary since the venous driving pressure is low. Note that since the veins can change caliber easily, the venous system acts as a very flexible reservoir of blood, able to contain anywhere from 25% 70% of the entire circulation’s blood volume at a particular time (Greenway and Lautt, 1986). This flexibility is important because the body has variable needs for “active” systemic blood depending on the circumstance. In normal, basal physiology, only about 40% of the blood volume is in the arterial circulation. However, in states of stress, such as during intense exercise or adrenaline rush, the veins can constrict to contain only 25% of the blood such that 75% of the blood can be utilized actively in the arterial circulation. In some cases of hemorrhage, systemic venoconstriction occurs to compensate for the hemorrhage by pushing relatively more blood to the arterial circulation. Conversely, venodilation can occur in certain situations of shock where blood is pooled into the venous system to avoid massive blood loss via arterial bleeding. While the peripheral arteries are commonly subject to atherosclerosis, which is the main pathology that necessitates endoarterial intervention and stenting, the veins are virtually not affected by atherosclerosis. It is hypothesized that the lower blood pressures, wall tensions, and oscillations in wall shear stress found in the venous environment may somehow encourage different endothelial behavior and protect the veins from atherosclerosis. However, the veins may be subject to pathologic compression, slow flow, and hypoxia that can cause thrombosis and fibrosis, which also result in occlusive disease. The added complexity of venous disease impacting vein valve function exacerbates the problem. Vascular experts believe that the number of cases of venous disease exceeds those of arterial disease, and that the venous device market could eventually surpass that of the arterial market.

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INFERIOR VENA CAVA AND RENAL VEINS Anatomy and Pathology The IVC is the largest vein of the body, formed by the left and right common iliac veins approximately at the level of the navel, and running along the right side of the spine, up the abdomen, into the thorax, and into the right atrium of the heart (Fig. 12.2). The lumbar, gonadal, renal, suprarenal, and hepatic veins drain into the IVC, which carries the lower body’s venous return back to the heart to get pumped into the lungs for oxygenation. The IVC is situated posterior to the peritoneum of the posterior abdominal wall and anterior to the vertebral bodies of the spine.

From a medical device perspective, the main pathologies that concern the IVC are IVC syndrome and lower extremity venous thrombosis. IVC syndrome is used to describe a variety of obstructive IVC diseases, including external compression from the aorta, uterus, and tumors, or occlusion within the IVC from thrombosis or tumors. In certain cases, IVC syndrome can be treated by venoplasty and stenting. In the case of lower extremity deep vein thrombosis, embolic debris from thrombus in the legs can travel up the IVC, into the lungs, and cause pulmonary embolism. In cases of smaller emboli where small pulmonary arteries are blocked, sections of the lung may experience infarction, damaging the tissue. In cases of large emboli where major pulmonary arteries are obstructed, hypoxia, low

FIGURE 12.2 Major veins of the body draining into the venae cavae. From https://commons.wikimedia.org/wiki/ File:2132_Thoracic_Abdominal_Veins.jpg.

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blood pressure, and even death can result. A common defense against massive pulmonary embolism is the intravenous placement of an IVC filter to catch these emboli before they reach the lung (Fig. 12.3).

FIGURE 12.3 A filter device can be implanted into the inferior vena cava to catch large embolic debris from lower extremity thrombus in order to prevent massive pulmonary embolism. From https://commons.wikimedia.org/ wiki/File:Inferior_Vena_Cava_Filter.png.

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Inferior Vena Cava Motion with Respiration Both stents and IVC filters have been reported to deform and fracture inside of the IVC, and deformations of the IVC have been blamed for causing the fractures. The most important IVC deformations are induced by intrathoracic pressure changes during respiration and Valsalva maneuver, and visceral organ movement from diaphragmatic displacement during respiration. During normal breathing, inhalation causes thoracic cavity expansion and abdominal cavity compression. This combination of intrathoracic pressure decrease and intraabdominal pressure increase encourages a rise in venous return from the IVC to the heart, causing the IVC in the abdomen to compress its crosssection. Conversely, during expiration, intrathoracic pressure increases while intraabdominal pressure decreases, forcing blood into the right atrium from the thorax and encouraging venous return from the lower extremities into the IVC, causing IVC cross-sectional expansion. Thus with every respiratory cycle of inspiration and expiration, the cross-section of the IVC in the abdomen compresses and expands, respectively. Table 12.1 shows a summary of representative studies that quantified IVC diametric deformations due to respiration (Table 12.1). In these studies, IVC deformation was measured as diametric collapse from expiration to inspiration, that is, (expiration diameter 2 inspiration diameter)/expiration diameter. In healthy children, the IVC diameter decrease was measured to be 30 6 13% just proximal to the hepatic veins using B-mode ultrasound (Kutty et al., 2014). This is nearly exactly the same as the collapsibility of 30 6 21% measured at the same location in healthy adults in the anterior posterior axis (Wallace et al., 2010). In healthy adults, the diametric collapse from expiration to inspiration

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TABLE 12.1 Inferior Vena Cava Diametric Deformation with Respiration Study

Population/Location

Kutty et al. (2014)

Healthy children Hepatic vein IVC

Wallace et al. (2010)

Kircher et al. (1990)

Krause et al. (2001)

Inspiration

Expiration

Collapse

0.89 6 0.38 cm

1.21 6 0.38 cm

30 6 13%

Healthy adults

(AP axis)

Diaphragm IVC

20 6 16%

Hepatic vein IVC

30 6 21%

Left renal vein IVC

35 6 22%

Cardiology patients

(Minor axis)

(Major axis)

Diaphragm IVC

1.2 6 0.7 cm

1.9 6 0.5 cm

0.98 6 0.39 cm/m2

1.26 6 0.38 cm/m2

24.1 6 11.4%

0.61 6 0.23 cm/m

0.89 6 0.30 cm/m

29.0 6 11.4%

Pre-ultrafiltration

N/A

2.60 6 0.57 cm

12.5 6 3.6%

Post-ultrafiltration

N/A

2.47 6 0.59 cm

23.6 6 5.3%

Major axis

N/A

2.32 6 0.35 cm

4.3%

Minor axis

N/A

1.43 6 0.41 cm

7.0%

42 6 25%

Hemodialysis patients Diaphragm IVC Pre-hemodialysisa a

Post-hemodialysis Guiotto et al. (2010)

2

2

Heart failure patients Diaphragm IVC

Murphy et al. (2008)

IVC filter patients Infrarenal IVC

a

Data represented as IVC diameter normalized to body surface area. IVC, Inferior vena cava; AP, anterior posterior.

appears to increase distally, with 20 6 16%, 30 6 21%, and 35 6 22% collapsibility at the levels of the diaphragm, hepatic vein, and left renal vein, respectively. In some patient groups, the diametric collapsibility of the IVC can vary more dramatically. In a series of cardiology patients admitted for cardiac catheterization, the IVC diametric collapsibility near the diaphragm was measured via B-mode ultrasound at 42 6 25% (Kircher et al., 1990); however, this value may be an overestimate since the expiration and inspiration diameter measurements

may not have been performed on the same axis. For example, if the expiration diameter was measured on the major axis and inspiration diameter was measured on the minor axis, the IVC percent collapse would be overestimated. In a series of pediatric hemodialysis patients, the IVC diametric deformation just posterior to the diaphragm was relatively similar to those of healthy subjects at 24.1 6 11.4% and 29 6 11.4% before and after hemodialysis, respectively (Krause et al., 2001). For heart failure patients, the IVC diametric collapse near the diaphragm was 12.5 6 3.6%

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and 23.6 6 5.3% before and after ultrafiltration, respectively (Guiotto et al., 2010). The lower IVC collapsibility before ultrafiltration makes sense because the veins experience volume overload with acute decompensated heart failure, and the IVC is thus more consistently dilated with a more circular cross-section. In a study with patients just prior to IVC filter implantation, the cross-section of the infrarenal IVC was measured by intravascular ultrasound in patients who were anesthetized (Murphy et al., 2008). With normal mechanical ventilation, major and minor axis collapsibility were 4.3% and 7.0%, respectively. These deformations are substantially lower than in the other reports, potentially because these patients were under general anesthesia and were mechanically ventilated. It is also possible that the patients were under venous volume overload, subjecting the IVC to higher pressure and lower collapsibility. In an interesting study comparing normal breathing with abdominal breathing, IVC collapsibility was compared between a group of highly trained abdominal breathers (average 9.6 years of training) and a control group (Byeon et al., 2012). Abdominal breathing, also known as diaphragmatic breathing, consists of relaxed, deliberate breathing where diaphragmatic descent during inspiration causes the belly to expand outward, as opposed to chest breathing where the ribcage expands upward and outward. In the trained abdominal breathers, the IVC exhibited diametric collapsibility of 62 6 19% and 48 6 19% during abdominal breathing and normal respiration, respectively. When compared to a control group, the abdominal breathers exhibited greater IVC collapsibility even during normal breathing (48 6 19% vs 26 6 12%). This suggests that not only does diaphragmatic breathing encourage greater IVC collapsibility due to larger changes in intraabdominal pressure, but the abdominal breathers somehow retain some of this extra

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IVC collapsibility when they try to perform ribcage breathing. In general, respiratory-induced changes to vein diameter are greater with deeper breathing (Abu-Yousef et al., 1997), diaphragmatic breathing versus ribcage breathing (Byeon et al., 2012; Miller et al., 2005), supine versus upright position (Reeves et al., 1961; Wade and Bishop, 1962; Jager et al., 1989), head up versus head down position (Moneta et al., 1988), lower blood volume physiology (Guiotto et al., 2010; Krause et al., 2001), lower flow physiology (Cheng et al., 2003), and lower pressure physiology (Jardin and Vieillard-Baron, 2006). The IVC also displaces as a whole during respiration. Using B-mode ultrasound in long-axis and cross-sectional views, IVC translation was recorded at the confluence of the hepatic veins and was measured to translate inferiorly 21.7 mm (95% confidence interval 5 18.3 25.1 mm) and laterally 3.9 mm (95% confidence interval 5 3.3 4.5 mm) during inspiration (Blehar et al., 2012). While the IVC may experience axial deformations during breathing, they have not been reported in the literature. However, evidence suggests that only the cross-sectional flattening of the vein causes IVC filter fractures, while axial motions are not implicated (Kuo et al., 2013). Meanwhile, the motion of respiration itself can cause motion in the visceral veins that empty into the IVC. During inhalation, the diaphragm contracts, descending and flattening into the abdominal cavity. This means that visceral organs, and the visceral vessels in contact with these organs, are pushed downward during inhalation. During expiration, the lungs recoil inward, making the diaphragm curve upward to expand the abdominal cavity. This causes the visceral organs, and associated visceral vessels, to rebound upward. While there have not been any quantitative studies specifically defining the deformation of visceral veins

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during respiration, it is perhaps reasonable to use the visceral artery branch angle and curvature deformations defined in Chapter 9, Abdominal Aorta and Renovisceral Arteries, as first-order approximations.

Inferior Vena Cava Motion with Valsalva and Other Influences During Valsalva maneuver, or “bearing down” with forceful exhalation against a closed airway, IVC cross-sectional deformations are more dramatic compared to respiration due to greater intrathoracic and

intraabdominal pressure changes (Fig. 12.4). Note that venous pressures during Valsalva can be nearly one order of magnitude higher than those exhibited during normal respiration. Upon initiating Valsalva, increased intrathoracic pressure decreases venous return and the IVC tends to expand as the blood is “dammed” back. This expanded IVC crosssection persists for the duration of the maneuver. When the forced exhalation pressure is released, intrathoracic pressure drops to normal, enabling venous return to flood back toward the heart, causing a cross-sectional collapse of the IVC.

FIGURE 12.4 As compared to respiration (top row), Valsalva maneuver (bottom row) causes greater cross-sectional compression of the inferior vena cava as seen from posterior (right column), left (middle column), and axial (right column) views. Adapted from Laborda, A., Sierre, S., Malve, M., De Blas, I., Ioakeim, I., Kuo, W.T., et al., 2014. Influence of breathing movements and Valsalva maneuver on vena caval dynamics. World J. Radiol. 6 (10), 833 839, Figures 5 and 6.

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TABLE 12.2 Inferior Vena Cava Diametric and Area Deformation With Valsalva Study

Population/Location

Minimum

Maximum

Collapse

Murphy et al. (2008)

Pre-IVC filter Infrarenal IVC, Major diameter

2.32 6 0.35 cm

2.40 6 0.12 cm

3.4 6 2.2%

Infrarenal IVC, Minor diameter

1.43 6 0.41 cm

1.96 6 0.12 cm

30.9 6 4.8%

Laborda et al. (2015)

2

2.61 cm

3.69 cm

3 cm above renal veins, CX area

0.87 6 0.18 cm2

3.94 6 0.86 cm2

77.83%

At renal veins, CX area

0.93 6 0.15 cm

3.80 6 0.75 cm

75.63%

3 cm below renal veins, CX area

0.70 6 0.10 cm

2

3.43 6 0.50 cm

79.56%

3 cm above filter struts, CX area

0.46 6 0.15 cm2

4.40 6 0.40 cm2

89.57%

At IVC filter struts, CX area

1.61 6 0.13 cm

4.31 6 0.50 cm

62.55%

3 cm below filter struts, CX area

0.47 6 0.12 cm

4.09 6 0.52 cm

88.58%

Infrarenal IVC, CX area Laborda et al. (2014)

2

29.3%

Pre-IVC filter

2 2

2

Post-IVC filter

2 2

2 2

IVC, Inferior vena cava; CX area, cross-sectional area.

IVC collapsibility data related to Valsalva maneuver are shown in a set of representative studies (Table 12.2). In these studies, IVC deformation was measured as diametric or area collapse from maximum to minimum crosssection, for example, (maximum diameter 2 minimum diameter)/maximum diameter. In a study conducted by Murphy et al. (2008) using intravascular ultrasound, the infrarenal IVC experienced 3.4 6 2.2% and 30.9 6 4.8% major axis and minor axis diametric collapse, respectively, with “simulated” Valsalva maneuver. Assuming an elliptical cross-section, this translates into a 29.3% area collapse due to Valsalva. This is substantially lower than the IVC cross-sectional area collapsibility as reported by Laborda et al. (2014), which measured 77.83%, 75.63%, and 79.56% collapse at the suprarenal, juxtarenal, and infrarenal locations on the IVC, respectively (Laborda et al., 2014). This may be due to the fact that the patients in the Murphy et al. study were anesthetized and Valsalva was simulated

by applying 40 mmHg of ventilation pressure. In these anesthetized patients, intrathoracic and intraabdominal pressures may not have been as dramatic as with actual Valsalva, and the abdominal muscles were not contracted. In another study, patients with implanted IVC filters were scanned with computed tomography venography for IVC area collapsibility (Laborda et al., 2015). The IVC crosssectional area collapsed by 62.55% at the IVC filter struts, and 89.57% and 88.58% 3 cm above and below the IVC filter struts, respectively. Even though IVC filters are designed to be flexible in the radial direction, these data show that the filters provided enough radial stiffness to substantially reduce cross-sectional area collapse. In addition, when compared to Laborda et al. (2014), these data show that a reduction in cross-sectional collapse at the filter struts is concomitant with elevated crosssectional collapse above and below the filter struts (Laborda et al., 2014). This suggests that while the normal IVC without a filter tends to

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collapse uniformly along its length during Valsalva, in the presence of localized stiffness added by a filter, it will collapse more than normal at adjacent unsupported locations to compensate for decreased collapse at the supported location. Murphy et al. (2009) investigated the changes in cross-sectional geometry of the IVC in severe blood-loss trauma patients before and after fluid resuscitation using computed tomography. The minor diameter of the IVC at locations 1 and 5 cm below the renal veins increased from 9.2 6 3.0 to 16.8 6 4.1 mm and 10.9 6 3.2 to 17.3 6 3.7 mm, respectively, with fluid resuscitation. The major diameter of the IVC at locations 1 and 5 cm below the renal veins increased from 24.9 6 3.9 to 26.7 6 3.8 mm and 23.5 6 2.5 to 24.7 6 2.1 mm, respectively, with fluid resuscitation. This means that while the minor diameter of the IVC increased on average by 70% 80%, the major diameter only increased on average by

5% 7%. In some patients, the minor axis expanded to five times the diameter. This makes sense because as the flaccid, low pressure venous system is pressurized with more fluid, the cross-section of the veins becomes more circular to hold more volume (Fig. 12.5). This study also found that the IVC major axis in all patients was tilted left-anterior oblique on average 26 degrees, and that the fluid resuscitation did not change this cross-sectional orientation. In a topic much less studied, the crosssection of the IVC also deforms during the cardiac cycle. Nakamura et al. (2013) imaged healthy volunteers with mild hypovolemia (to amplify changes such that they could be detected) with B-mode ultrasound in the supine position, with legs raised, and with pneumatic anti-shock trousers. The IVC crosssectional area collapsed a maximum of 24 6 3%, 11 6 1%, and 12 6 1% in the supine position, with legs raised, and with pneumatic FIGURE 12.5 Three examples (one per row) of the IVC cross-section minor diameter expanding more than the major diameter in massive blood-loss trauma patients from before (left column) to after (right column) fluid resuscitation. Note that the left-anterior oblique orientation of the IVC cross-section remains the same after fluid resuscitation. Adapted from Murphy, E., et al., 2009. Volume associated dynamic geometry and spatial orientation of the inferior vena cava. J. Vasc. Surg. 50, 835 843, Figure 5.

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anti-shock trousers, respectively. This indicates that the assistance of gravity for venous return in the leg-raised position, and the compression of the pneumatic trousers, damp the effects of cardiac variation in IVC cross-sectional geometry. These data are supported by the fact that in situ measurements of IVC pressure, using pressure catheters, reveal higher venous pressure during systole (14.00 6 3.12 mmHg) as compared to diastole (6.95 6 1.85 mmHg) (Laborda et al., 2015).

Nutcracker Syndrome One peculiar condition, called nutcracker syndrome, when the left renal vein is compressed between the aorta and the superior mesenteric artery or between the aorta and the spine, has been relatively well described (Fig. 12.6). The situation arises when the superior mesenteric artery branches down from the aorta at an unusually acute angle, causing the space between the two to be especially small, or when the left renal vein courses posterior to the aorta. Since arterial pressure is so much higher than venous pressure, the circular cross-

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sections of the aorta and superior mesenteric artery flatten the left renal vein, potentially causing a higher pressure gradient, renal venous hypertension, thin-walled vein rupture, and/or blood in the urine. The amount of compression of the left renal vein can be highly variable, but most experts consider at least 50% diametric compression in the anterior posterior direction, as referenced to the hilar region of the left renal vein, to be clinically relevant and warrant monitoring (Poyraz et al., 2013). While the point of compression renders a smaller renal vein diameter locally, the rest of the left renal vein is actually larger than the right renal vein, a result of left renal vein hypertension caused by the narrowing. In an investigation on the impact of stenting for nutcracker syndrome, 10 mm diameter nitinol stents were placed endovascularly for left renal vein compression between the aorta and superior mesenteric artery (Li et al., 2013). In these patients, the hilar region of the left renal veins exhibited a diameter of 9.2 6 0.9 mm and the compressed aortomesenteric region had a diameter of 2.0 6 0.9 mm, representing a 78 6 9% compression. After stenting, the

FIGURE 12.6

Contrast-enhanced computed tomography scan showing anterior and posterior nutcracker syndrome, where the left renal is diametrically compressed between the aorta and the superior mesenteric artery (left), and between the aorta and the spine (right), respectively. Adapted from Poyraz, A.K., Firdolas, F., Onur, M.R., Kocakoc, E., 2013. Evaluation of left renal vein entrapment using multidetector computed tomography. Acta Radiol. 54, 144 148, Figures 1 and 2.

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FIGURE 12.7 Coronal (left) and sagittal (right) views of a computed tomography angiogram of the left renal vein after stenting. Note in the sagittal image that the stent is relatively expanded even though it is compressed between the aorta and superior mesenteric artery. Adapted from Li, H., Sun, X., Liu, G., Zhang, Y., Chu, J., Deng, C., et al., 2013. Endovascular stent placement for nutcracker phenomenon. J. X-Ray Sci. Technol. 21 (1), 95 102, Figure 3.

aortomesenteric region of the left renal artery expanded to 6.0 6 0.6 mm, representing a 44 6 9% decrease in the amount of diametric compression (Fig. 12.7). In these cases, left renal venous pressure decreased, left flank pain resolved, and hematuria disappeared within a few months of treatment. After two more years, symptoms did not return and there was no evidence of restenosis or thrombosis. Upon review of the literature, nutcracker syndrome stenting has been performed with a variety of stent designs made from nitinol, stainless steel, and Elgiloy, and the overall results have been favorable (Wang et al., 2012; Wu et al., 2016; Chen et al., 2011). However, in rare cases, the stent may migrate into the right atrium, necessitating endovascular or surgical retrieval, or experience stent re-compression. Stent migration indicates that the left renal vein expands enough post-implantation that the stent dislodges and flows into the IVC. Stent re-compression means that the “nutcracking” force between the aorta and superior mesenteric artery exceeds that of the stent’s radial resistive force. Theoretically, the superelastic properties of an oversized nitinol stent may decrease the chance of migration due to its ability to re-expand with the vessel. Meanwhile, stainless steel and Elgiloy may better combat acute recompression due to higher radial stiffness.

ILIOFEMORAL VEINS Anatomy and Pathology The right and left common iliac veins join to form the IVC. Each common iliac vein is formed by the convergence of the internal and external iliac veins approximately in front of the sacroiliac joints (Fig. 12.8). The right common iliac vein is typically shorter (5 6 cm long) and more vertical as compared to the left common iliac vein (7 8 cm long). The internal iliac vein is formed by the convergence of a variable set of veins that drain the pelvic region. The external iliac vein is the proximal extension of the common femoral vein, transitioning from one to the other as it crosses the inguinal ligament. The iliofemoral vein passes through the femoral triangle alongside the iliofemoral artery and femoral nerve (Fig. 12.9). The femoral triangle is generally in the coronal plane and is formed by the sartorius muscle laterally, the adductor longus muscle medially, and the inguinal ligament superiorly. The inguinal ligament runs from the anterior superior iliac spine to the pubic tubercle and serves to contain soft tissues as they course from the trunk to the lower extremity. The hip joint is rather unique in the human body, and in fact rare in the entire animal kingdom, in that it exhibits incomplete articular

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ILIOFEMORAL VEINS

Aorta

Inferior vena cava

Common iliac artery Common iliac vein Internal iliac artery External iliac artery Inguinal ligament Internal iliac vein External iliac vein

Common femoral artery

Common femoral vein Profunda femoris artery

Great saphenous vein Profunda femoris vein

Superficial femoral artery

Femoral vein

FIGURE 12.8 Iliofemoral vein anatomy in relation to the hip and leg bones (left) and iliofemoral arteries (right). The green circles represent areas where the iliofemoral arteries may compress the iliofemoral veins. Adapted from https://opentextbc.ca/anatomyandphysiology/chapter/20-5-circulatory-pathways, Figure 20 (left), and self-drawn (right). External iliac artery and vein Inguinal ligament

Femoral nerve

Lal. fem. culan. nerve Ing

uin

al

Femoral shealth: Lateral compartment Intermediate compartment Medial compartment Deep external pudendal vessels

Sartorius muscle

lig

am

ent

Femoral nerve Lumbo-inguinal nerve Femoral artery Femoral sheath Femoral vein Femoral ring Lacunar ligament

Adductor longus m. Femoral artery and vein

FIGURE 12.9 Anatomy of the femoral triangle from coronal (left) and axial (right) views. The common femoral vein, along with the common femoral artery and femoral nerve, are bounded between the inguinal ligament anteriorly and the pubic bone posteriorly. Adapted from web.duke.edu/anatomy/Lab14/Lab14.html (left), Gray’s Anatomy, Plate 546 (right).

congruency in the closed-packed position during hip extension, that is, the femoral head and hip socket do not fit perfectly in the standing position. This is a direct result of human evolution transitioning our ancestors from primarily

quadrupedal to primarily bipedal in such a short period of time (Hogervorst and Vereecke, 2014). In quadrupeds, since the neutral standing position involves hip flexion, articular congruency evolved in that position. The

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evolution of bipedalism happened so quickly that the osseous framework of the hip did not have enough time to catch up and reestablish articular congruency during the “new” neutral position of standing on two legs. In other joints, for example, the knee, the articular surfaces of the two bones (e.g., femur and tibia) exhibit complete congruency and the ligaments are drawn tight during extension. Since the iliofemoral veins are posterior and mostly medial to the iliofemoral arteries, there are certain locations where the arteries cross over the veins and may cause compression (Fig. 12.8). Over half of the general population has some level of non-thrombotic iliac vein compression, most of which is not clinically relevant (Raju and Neglen, 2006). However, May Thurner syndrome is a clinicallyrelevant variant of this condition where the left common iliac vein is compressed between the spine and the pulsating right common iliac artery, potentially impairing venous drainage and causing leg pain, swelling, deep vein thrombosis, varicose veins, and other complications. Over time, the pulsatile chronic compression causes the development of fibrous tissue in the left common iliac vein, exacerbating the thrombotic potential by further impeding flow and increasing turbulence and flow stasis. In rarer cases, venous compression can be clinically significant where the arteries compress the right common iliac vein, or even distally in the external iliac veins (Fig. 12.8). The other main category of lower extremity venous disease relevant for the vascular stent industry is post-thrombotic syndrome, a condition that follows deep vein thrombosis and causes leg pain, persistent leg swelling, discoloration, venous ulcers, etc. While the exact mechanisms of post-thrombotic syndrome are not fully understood, it is known that deep vein thrombosis causes inflammation, damage to vein valves, and may lead to retrograde venous flow, venous hypertension, and insufficient venous drainage.

Iliac Vein Deformation with Respiration and Valsalva As seen earlier in this chapter, there are published data on IVC cross-sectional deformations related to respiration, Valsalva, and body position. Later in this chapter, there is also a summary of how the femoropopliteal vein deforms with body position, respiration, and Valsalva. However, no specific work has been published on iliac vein deformations related to these physiologic stimuli. Fortunately, since there are data on the IVC and femoral veins, pressure-induced collapsibility can be estimated for the iliac veins in between. Conveniently, the published literature suggests that the cross-sectional deformations of the IVC and common femoral vein are relatively similar for respiration (Murphy et al., 2008; Miller et al., 2005) and Valsalva maneuver (Murphy et al., 2008; Jager et al., 1989) when body posture and venous fluid load are considered. Note, however, that the phasicity of deformation between the IVC and femoral veins may be different. For example, during expiration, the lower extremity veins may collapse as they send venous return into the expanding IVC with decreased intraabdominal pressure. Thus, it is unclear exactly when iliac vein collapse and expansion occur.

Iliac Vein Compression from External Structures Non-thrombotic iliac vein lesions are caused by adjacent arteries compressing the iliac vein, most notably with May Thurner syndrome when the right common iliac artery compresses the left common iliac vein (Fig. 12.10). Note that May Thurner syndrome is more than three times more prevalent in women than men. In a study conducted only on women (to eliminate gender difference and reduce vessel size differences), computed tomography was

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FIGURE 12.10 Example of a patient with May Thurner syndrome where the right common iliac artery (black and white arrows) compresses the left common iliac vein (black and white arrowheads) as viewed from axial (left) and sagittal (right) views. Adapted from Kibbe, M.R., Ujiki, M., Goodwin, A.L., Eskandari, M., Yao, J., Matsumura, J., 2004. Iliac vein compression in an asymptomatic patient population. J. Vasc. Surg. 39 (5), 937 943, Figures 3 and 5.

utilized to quantify left iliac vein diameter and compression in patients with deep vein thrombosis and in healthy controls (Carr et al., 2012). All patients had only left deep vein thrombosis, so the right common iliac vein was used as a baseline for computing left common iliac vein compression such that % Compression 5 100% 2 (left common iliac vein diameter/right common iliac vein diameter). The left common iliac vein was measured at the minimum diameter at the point of maximum compression by the right common iliac artery, and the right common iliac vein was measured 1 cm distal to the IVC bifurcation. The average left common iliac vein diameter was 4.0 and 6.5 mm for the deep vein thrombosis and control patients, respectively. The left common iliac vein compression was 68% and 52% for the deep vein thrombosis and control patients, respectively. These data demonstrate that patients with left deep vein thrombosis had significantly greater compression of the left common iliac vein compared to the healthy subjects. In a similar study with a much larger set of patients, unilateral deep vein thrombosis patients were scanned with contrast-enhanced computed tomography to measure common iliac vein compression (Narayan et al., 2012). Approximately 55% of the patients had left

deep vein thrombosis while 45% had right deep vein thrombosis. The distal right common iliac vein was used as the baseline for calculating common iliac vein compression such that % Compression 5 100% 2 (common iliac vein diameter on the side with deep vein thrombosis/distal right common iliac vein diameter). The common iliac vein was measured at the point of maximum compression, and the right common iliac vein at the distal portion where there was no apparent compression. The average compression for all common iliac veins on the side of deep vein thrombosis was 36.6%. Approximately 75% of the patients had .25% diametric compression, 33% had .50% compression, and 7% had .70% compression. The left common iliac vein was noted to have a 2.5-fold greater chance of having .70% compression as compared to the right common iliac vein (10% vs 4%). These results are similar to those found in another study, where approximately two-thirds of the patients showed .25% compression and one-fourth of the patients showed .50% compression (Kibbe et al., 2004). This study also showed that women had significantly greater common iliac vein compression compared to men (41.2 6 3.1% vs 27.0 6 3.0%).

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Iliofemoral Vein Deformation with Hip Joint Movement The stimulus most implicated in fractures occurring in stents implanted in the iliofemoral veins is hip joint motion. Considering that most iliofemoral stent fractures occur near the hip joint, the hip joint moves with every walking and stair-climbing step taken, and the fact that the hip joint is adjacent to the rigid inguinal ligament and pubis bone structures, smoking guns abound. Since the axial location of the inguinal ligament approximately coincides with the superior ramus of the pubis, the iliofemoral vein is sandwiched between these two structures just as it transitions from the external iliac vein to the femoral vein. The spatial coincidence of the inguinal ligament and superior ramus can cause iliofemoral vein compression or a mechanical pivot point (Fig. 12.11).

FIGURE 12.11 Depiction of the spatial coincidence of the inguinal ligament with the superior ramus of the pubis (red circle). Adapted from https://es.m.wikipedia.org/wiki/ Archivo:Gray319.png.

This phenomenon is a result of human bipedal evolution, where the human hip joint is unique in the animal kingdom by being in the fully extended position during normal stance and much of the gait cycle (Hogervorst and Vereecke, 2014). Relatedly, since the femoral head and pelvis acetabulum are not in congruency during extension in the close-packed position, the hip ligaments need to be very tight in order to establish joint stability (Levangie and Norkin, 2005). Conversely, when the hip is flexed and is in the openpacked position, the hip ligaments are uncoiled and slack. Furthermore, the fact that full hip extension is beyond the point of full articular congruency means that other structures, such as the iliofemoral veins, also need to be stretched along longer path lengths. The result is that hip extension may be the position that causes the tightest geometric constraint for the iliofemoral vessels, especially at the location of the inguinal ligament and superior ramus of the pubis. The inguinal ligament is unlikely to be the main source of stress, except in cases of extreme hip flexion, since it is held stably and independent of the hip angle at the static bony structures of the anterior superior iliac spine and pubic tubercle. In a cadaver study where stents of various designs were implanted into the iliofemoral veins, the distance between the stents and the inguinal ligament was quantified under different levels of hip flexion (Veniti Inc., 2014). Since the inguinal ligament could not be directly visualized via CT imaging, the inguinal ligament path was defined as the straight path between the anterior superior iliac spine of the ilium to the pubic tubercle on the pubic bone. The inguinal ligament paths appear to be separated from the stents in the anteroposterior direction by 1 3 cm in all hip flexion positions, making stent compression from direct inguinal ligament contact unlikely (Fig. 12.12). In addition, the inguinal ligament and iliofemoral vein are separated and

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FIGURE 12.12

Representative images of a cadaver study where stents were implanted into the iliofemoral veins and the cadaver was positioned with increasing hip flexion angles and imaged with computed tomography. Sagittal maximum intensity projection images show hip flexion angles of 0, 43, 75, 105, and 135 degrees (top row). Three-dimensional stent models overlaid with the L5 vertebral body and inguinal ligament paths (bottom row) are shown from front (bottom left), left oblique (bottom middle), and right oblique (bottom right) views. The stent models and inguinal ligament paths corresponding to 0 (gray), 43 (red), 75 (green), 105 (blue), and 135 degrees (purple) hip flexion are overlaid together. The stents and inguinal ligaments in all hip flexion positions were co-registered to the rigid L5 vertebral body and appear spatially separated from each other in all positions.

cushioned by connective tissue composed of abdominal fascia, the anterior wall of the femoral sheath, and the medial compartment (Moazzam et al., 2012; Lytle, 1974, 1979). However, it appears that the distal ends of the iliofemoral stents are in close vicinity to the pubis bone (Fig. 12.12, top row). In fact, the inferior ends of the iliofemoral stents were subject to the greatest cross-sectional minor diameter change with hip flexion (up to 20%), with the higher angles of hip flexion associated with greater minor diameters (i.e., less compression). This demonstration of less diametric compression at higher angles of hip flexion is consistent with the phenomenon of iliofemoral vein slackening and lifting off of the superior ramus of the pubis during hip flexion. Furthermore, as

opposed to the substantial padding between the iliofemoral vein and inguinal ligament, the superior ramus of the pubis is a hard, bony structure that is only padded with iliac fascia in some locations. These cadaver observations make sense because the iliofemoral vessels move with hip flexion and thigh position with respect to the abdomen, and the position of the pubis is independent of hip flexion angle. Thus, the superior ramus of the pubis acts as a fulcrum during hip extension. In other words, since the pubis does not move with hip extension, and the paths of the iliofemoral vessels shift posteriorly and lengthen, the vessels get pulled against the pubis during hip extension. Conversely, the iliofemoral vessels should slacken with hip

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FIGURE 12.13 Three-dimensional reconstruction of the pelvis and centerline of the iliofemoral veins from a representative patient computed tomography image from front (left), left side (middle), and close-up (right) views. In the right image, distance (short black line) was measured between the centerline of the iliofemoral vein (gray line) and the superior ramus of the pubis (green line on the surface of the pubis bone).

flexion because they are anterior to the hip joint and their paths shorten (Cheng et al., 2006, 2010). This means that hip extension and hyperextension could cause local diametric compression, bending, and axial tension at the superior ramus, while hip flexion may reverse these mechanical provocations. Walking motion is normally accompanied by a hip angle range from 25 degrees flexion to 15 degrees hyperextension, so normal activity exceeds full extension and could certainly instigate these vascular deformations (Winter, 1991). The conclusions about cross-sectional compression of the iliofemoral veins during hip extension are also supported by in vivo patient imaging analysis. In a study performed on 21 iliofemoral venous disease patients (36 limbs), the distance between the iliofemoral vein and the pubic bone was quantified in the supine body position from computed tomography images (Veniti Inc., 2017) (Fig. 12.13). The average distance between the centerline of the iliofemoral vein and the surface of the superior ramus of the pubis was 6.7 6 2.7 mm, with a range of 2.8 13.9 mm for all 36 limbs. From these same patients, the average common femoral vein diameter was approximately 12 mm (i.e., 6 mm radius). This quantitatively demonstrates the close vicinity of the femoral vein to the bony pubis, with 47% (17 of 36) of the

femoral veins being compressed by the pubis (femoral vein centerline # 6 mm away from the superior ramus) and 78% (28 of 36) within 3 mm of the pubis (femoral vein centerline # 9 mm of the superior ramus). In a patient implanted with multiple iliofemoral venous stents, there is striking fluoroscopic proof of iliofemoral vein compression at the superior ramus of the pubis in the straight hip position (Fig. 12.14). With contrast injection, there is a decrease in contrast in the flow lumen at the level of the superior ramus. Upon viewing the subtraction image, it is obvious that the flow lumen narrowing is in the anterior posterior direction exactly where the superior ramus contacts the common femoral vein. In fact, there is a visible white line delineating the superior border of the superior ramus bone on the subtraction contrast image. In studies that included both iliofemoral venous disease patients and cadavers, centerlines of implanted stents were constructed from 2D lateral fluoroscopy data (Veniti Inc., 2014, 2017). With hip flexion more aggressive than typical walking (B40 vs B30 degrees) and typical stair climbing (B100 vs B90 degrees), the stent length changed by an average of 2.1% and 2.7%, respectively. Using these same stent centerlines, curvature changes were also computed. The stent centerlines exhibited

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FIGURE 12.14 Anterior posterior fluoroscopy images of an example patient with implanted iliofemoral venous stents. Overlapped stents are seen in a non-contrast image (left image). With the injection of iodinated contrast, there is an apparent decrease in contrast at the superior ramus indicating flow lumen compression (middle image, green bracket). With subtraction imaging, the outline of the superior ramus bone causes an impression on the common femoral vein (right image, between the yellow arrows), with a distinct white line delineating the superior border of the superior ramus bone (right image, top yellow arrow).

curvatures of 0.115 6 0.012, 0.138 6 0.025, and 0.213 6 0.041 cm21 at the location of maximum bending for hip flexion angles of 0, B40, and B100 degrees, respectively. This translated to curvature changes of 0.032 6 0.019 and 0.116 6 0.023 cm21 for walking and stair climbing, respectively. Note that these absolute curvature values can be considered high since they were quantified from 2D lateral views only. In reality, the curvatures could potentially be lower due to increased path length in three-dimensional (3D) space. In summary, bipedal and upright walking means that the human hip extends past the point of full articular surface congruency, stretching the iliofemoral blood vessels to follow a longer path length and against the pubis. Hip extension and hyperextension during normal walking could cause tensioning of the iliofemoral vein against the superior ramus of the pubis and could theoretically cause local diametric compression, bending, and axial

tension. As shown with cadaver and patient imaging, the inguinal ligament path appears to be separated from the iliofemoral veins in the anteroposterior direction by 1 3 cm in a large range of hip flexion positions, making stent compression from direct inguinal ligament contact unlikely. In contrast, it appears that the common femoral vein often contacts or is in close proximity to the superior ramus of the pubis and can be compressed on it during hip extension. During hip flexion, the iliofemoral vein tends to curve upward, shorten, and increase in curvature, with increasing magnitude with greater hip flexion.

FEMOROPOPLITEAL VEINS Anatomy and Pathology The common femoral vein is the distal continuation of the external iliac vein after it

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passes the inguinal ligament (Fig. 12.8). The common femoral vein is formed as the confluence of the femoral vein (also known as the superficial femoral vein), deep femoral vein (also known as the profunda femoris vein), and the great saphenous vein. Since the femoral vein tracks parallel to the femoral artery, it also resides in the femoral sheath within the adductor canal in the thigh and exits at the adductor hiatus above the knee. Distal to the adductor hiatus, the femoral vein continues downward as the popliteal vein and passes posterior-medially to the distal portion of the femur, situating itself behind the femur in the popliteal fossa. The femoropopliteal vein can be subject to occlusion by thrombosis, especially in conjunction with popliteal vein entrapment syndrome.

Common Femoral Vein Deformations with Posture, Respiration, and Calf Contraction The femoropopliteal veins are subject to deformations from a variety of sources, including body position, respiration, Valsalva, knee joint motion, muscle contraction, and popliteal entrapment syndrome. Table 12.3 summarizes cross-sectional deformation data of the common femoral vein from studies investigating the effects of body position, respiration, calf contraction, and Valsalva maneuver (Table 12.3). In one study, healthy subjects were placed on a non-weight-bearing tilt table and their common femoral veins were scanned with ultrasound (Moneta et al., 1988). In order to compensate for differences in body size and

TABLE 12.3 Common Femoral Vein Deformations in Healthy Subjects Study (Measurement)

Physiologic State

Moneta et al. (1988) (normalized diametera) 210 degrees (head down)

Jager et al. (1989) (diameter)

Miller et al. (2005) (cross-sectional area)

Measurement 0.47 6 0.11 cm/m2

0 degrees (supine)

0.59 6 0.12 cm/m2

110 degrees (head up)

0.72 6 0.15 cm/m2

120 degrees (head up)

0.84 6 0.14 cm/m2

130 degrees (head up)

0.90 6 0.16 cm/m2

Supine—resting

1.05 6 0.18 cm

Supine—valsalva

1.52 6 0.25 cm

Standing—resting

1.50 6 0.20 cm

Standing—valsalva

1.63 6 0.17 cm

All 145 degrees (head up) Resting

Mild CC

Moderate CC

Ribcage—inspiration

1.25 6 0.16 cm2 1.28 6 0.16 cm2 1.24 6 0.20 cm2

Ribcage—expiration

1.32 6 0.17 cm2 1.37 6 0.19 cm2 1.35 6 0.24 cm2

Diaphragm—inspiration

1.50 6 0.16 cm2 1.52 6 0.16 cm2 1.60 6 0.18 cm2

Diaphragm—expiration

1.34 6 0.17 cm2 1.34 6 0.15 cm2 1.38 6 0.15 cm2

a

Data represented as common femoral vein diameter normalized to body surface area. Mild CC, Mild calf contraction of (B7 kg); Moderate CC, moderate calf contraction (B11 kg).

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diametric variation related to the respiratory cycle, diametric measurements were scaled to body surface area and recorded at maximal dilatation, respectively. The normalized common femoral vein diameters were 0.48 6 0.12, 0.59 6 0.12, 0.72 6 0.15, 0.84 6 0.14, and 0.90 6 0.16 cm/m2 for the 210 (head down), 0 (supine), 110 (head up), 120 (head up), and 130 degrees (head up) body positions, respectively. The common femoral vein diameter was linearly correlated to body position tilt, with a 92% increase in normalized diameter from 210 (head down) to 130 degrees (head up) position. This supports the fact that when the body is upright, the venous return must fight the force of gravity, and thus the blood pools in the lower extremities and the veins are more expanded. This finding is corroborated by another study that measured the common femoral vein diameter of healthy subjects in the supine and standing positions using B-mode ultrasound (Jager et al., 1989). During the resting state, the common femoral vein diameter increased from 1.05 6 0.18 to 1.50 6 0.20 cm when transitioning from supine to standing position, which constitutes a 43% change. In both body positions, the Valsalva maneuver was also performed, causing common femoral vein diametric increases of 44.5 6 15.0% and 8.6 6 10.0% in the supine and standing positions, respectively. These data show that the increased femoral venous volume load during the standing position causes the dilatation impact of Valsalva maneuver to be diminished compared to the supine position. In addition, this suggests that in reference to the supine resting condition, standing up and Valsalva maneuver cause very similar increases in common femoral vein diameter. In a more complex study, healthy subjects were imaged with ultrasound to investigate the impact of different types of breathing and different levels of calf contraction on common femoral vein cross-sectional area (Miller et al.,

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2005). Subjects were positioned in the 45 degrees head up posture and the feet were placed on a fixture for cyclic plantar flexion, with zero, mild (7 kg), and moderate (11 kg) plantar flexion force. Plantar flexion cycles were performed separately during inspiration and expiration phases of the respiratory cycle, with both ribcage and diaphragm breathing. With no calf contraction, inspiration and expiration produced common femoral vein cross-sectional areas of 1.25 6 0.16 and 1.32 6 0.17 cm2, respectively, during ribcage breathing, and 1.50 6 0.16 and 1.34 6 0.17 cm2, respectively, during diaphragm breathing. With mild calf contraction, inspiration and expiration produced cross-sectional areas of 1.28 6 0.16 and 1.37 6 0.19 cm2 for ribcage breathing, and 1.52 6 0.16 and 1.34 6 0.15 cm2 for diaphragm breathing, respectively. With moderate calf contraction, inspiration and expiration produced cross-sectional areas of 1.24 6 0.20 and 1.35 6 0.24 cm2 for ribcage breathing, and 1.60 6 0.18 and 1.38 6 0.15 cm2 for diaphragm breathing, respectively. These data show that the cross-sectional area of the femoral vein tends to be larger and exhibits greater respiratory change with diaphragmatic breathing compared to ribcage breathing (Miller et al., 2005). Furthermore, while the greater common femoral crosssectional area occurs with expiration during ribcage breathing, it occurs with inspiration during diaphragm breathing. This makes sense because intraabdominal pressures change much more with diaphragm than ribcage breathing, and increased intraabdominal pressure during diaphragmatic inspiration dams the venous return from entering the abdominal IVC and causes the femoral veins to expand. Calf muscle contraction tends to substantially increase femoral vein flow; however, it only slightly increases the femoral vein crosssectional area and changes in cross-sectional area in conjunction with respiration. Note that the respiratory-induced changes to femoral

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vein cross-sectional area in this study are relatively muted because of high femoral venous volume load due to the 45 degrees head up posture.

Femoropopliteal Vein Deformations from Musculoskeletal Influences Compression of the femoropopliteal vein also occurs due to forces from external

structures such as adjacent muscles and bone. Brown et al. (2009) utilized 3D magnetic resonance imaging to measure the compression of femoropopliteal vessels with maximal isometric thigh contraction in healthy adults. The femoropopliteal vein undergoes nearly complete compression from the vastus medialis muscle at the distal portion of the adductor canal, just superior to the adductor hiatus (Fig. 12.15).

FIGURE 12.15 Representative cross-sectional magnetic resonance images of the thigh in the relaxed state (left column) and during maximal isometric contraction (right column) inferior to the adductor canal (top row, “Inferior to AC”), in the distal portion of the adductor canal (middle row, “Distal AC”), and in the proximal portion of the adductor canal (bottom row, “Proximal AC”). Solid arrowheads indicate the femoropopliteal artery and open arrowheads indicate the femoropopliteal vein. d, Normalized location from femoral condyle to femoral head; AC, adductor canal; AM, adductor magnus muscle; BFL, long head of biceps femoris muscle; BFS, short head of biceps femoris muscle; F, femur; G, gracilis muscle; RF, rectus femoris muscle; S, sartorius muscle; SM, semimembranosus muscle; ST, semitendinosus muscle; VI, vastus intermedius muscle; VL, vastus lateralis muscle; VM, vastus medialis muscle. Adapted from Brown, R., Nguyen, T.D., Spincemaille, P., Prince, M.R., Wang, Y., 2009. In vivo quantification of femoral-popliteal compression during isometric thigh contraction: assessment using MR angiography. J. Magn. Reson. Imaging 29 (5), 1116 1124, Figure 3.

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In the distal portion of the adductor canal, the femoropopliteal vein cross-sectional area reduced by 82% during maximal isometric thigh contraction, while the proximal portion of the adductor canal and inferior to the adductor canal experienced 34% and 37% cross-sectional area reduction, respectively. To state this another way, while the femoropopliteal vein’s cross-sectional area significantly compressed along nearly its entire length, the most significant compression occurred in the 5 cm span just proximal to the adductor hiatus (Fig. 12.16). Meanwhile, although the femoropopliteal artery flattened in terms of cross-sectional aspect ratio, its cross-sectional area (relaxed 5 37.8 6 9.5 mm2, contracted 5 38.8 6 10.5 mm2) was not significantly affected. Thus, during high contraction, the low pressure femoropopliteal vein experiences cross-sectional area reduction while the high pressure femoropopliteal artery does not.

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The dramatic compression of the femoropopliteal vein at the adductor hiatus was painstakingly confirmed in an extensive study on a large number of cadavers (Uhl, 2015). The study revealed that the adductor hiatus compression occurred due to the contraction of the adductor longus muscle. A rare form of popliteal entrapment syndrome, called popliteal vein entrapment syndrome, involves compressing the popliteal vein by abnormal medial migration of the medial head of the gastrocnemius muscle or popliteus muscle (Czihal et al., 2015). This deformation is repetitive, particularly from plantar flexion of the ankle during walking or running. Symptoms of calf pain, swelling, and muscle cramps can occur in conjunction with resultant deep vein thrombosis or chronic venous insufficiency. While there have not been many studies specifically quantifying the centerline

FIGURE 12.16 Average femoropopliteal artery and vein cross-sectional lumen areas in relaxed and isometricallycontracted thighs plotted against normalized location from d 5 0.09 (B4 cm superior to femoral condyle) to d 5 0.41 (B18 cm superior to femoral condyle) (top graph). By plotting p-values vs. normalized location, it is apparent that the change in crosssectional area (i.e., cross-sectional compression) was statistically significant (p , 0.05) for nearly the entire length of the femoropopliteal vein, while it was not significant (p . 0.05) for the femoropopliteal artery (bottom graph). Adapted from Brown, R., Nguyen, T.D., Spincemaille, P., Prince, M.R., Wang, Y., 2009. In vivo quantification of femoral-popliteal compression during isometric thigh contraction: assessment using MR angiography. J. Magn. Reson. Imaging 29 (5), 1116 1124, Figure 5.

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deformations of the iliac, femoral, and popliteal veins during joint flexion and extension, the centerline deformations defined in Chapter 10, Lower Extremity Arteries, can be used as a starting point. Note, however, that the veins probably do not possess as much axial elasticity as do the arteries, and thus the veins should experience lower axial arclength deformations and higher bending deformations due to joint motion compared to the corresponding arteries. It is perhaps reasonable to consider the centerline deformations of diseased lower extremity arteries as firstorder approximations for centerline deformations of femoropopliteal veins.

CONCLUSION Because the venous system is under much less blood pressure and lower pulse pressure compared to the arterial system, vein walls are thinner, weaker, and less elastic than arteries. Due to the lower venous pressure, pressure changes due to respiration, Valsalva, body position, and changing blood volume status can produce dramatic cross-sectional shape changes in the IVC and lower extremity veins. Similarly, compression from adjacent pressurized arteries, contracting muscles, and bony structures can occur, causing venous narrowing, thrombosis, and occlusion, sometimes leading to serious venous disease. Joint motions may drive similar axial and bending deformations to the lower extremity veins compared to the corresponding arteries; however, this requires further direct investigation.

References Abu-Yousef, M.M., Mufid, M., Woods, K.T., Brown, B.P., Barloon, T.J., 1997. Normal lower limb venous Doppler flow phasicity: is it cardiac or respiratory? Am. J. Roentgenol. 169 (6), 1721 1725.

Blehar, D.J., Resop, D., Chin, B., Dayno, M., Gaspari, R., 2012. Inferior vena cava displacement during respirophasic ultrasound imaging. Crit. Ultrasound J. 4 (1), 18. Brown, R., Nguyen, T.D., Spincemaille, P., Prince, M.R., Wang, Y., 2009. In vivo quantification of femoralpopliteal compression during isometric thigh contraction: Assessment using MR angiography. J. Magn. Reson. Imaging 29 (5), 1116 1124. Byeon, K., Choi, J.O., Yang, J.H., Sung, J., Park, S.W., Oh, J.K., et al., 2012. The response of the vena cava to abdominal breathing. J. Altern. Complement. Med. 18 (2), 153 157. Carr, S., Chan, K., Rosenberg, J., Kuo, W.T., Kothary, N., Hovsepian, D.M., et al., 2012. Correlation of the diameter of the left common iliac vein with the risk of lowerextremity deep venous thrombosis. J. Vasc. Intervent. Radiol. 23 (11), 1467 1472. Chen, S., Zhang, H., Shi, H., Tian, L., Jin, W., Li, M., 2011. Endovascular stenting for treatment of nutcracker syndrome: report of 61 cases with long-term follow-up. J. Urol. 186, 570 575. Cheng, C.P., Herfkens, R.J., Taylor, C.A., 2003. Inferior vena caval hemodynamics quantified in vivo at rest and during cycling exercise using magnetic resonance imaging. Am. J. Physiol.: Heart Circ. Physiol. 284, H1161 H1167. Cheng, C.P., Wilson, N.M., Hallett, R.L., Herfkens, R.J., Taylor, C.A., 2006. In vivo MR angiographic quantification of axial and twisting deformations of the superficial femoral artery resulting from maximum hip and knee flexion. J. Vasc. Intervent. Radiol. 17, 979 987. Cheng, C.P., Choi, G., Herfkens, R.J., Taylor, C.A., 2010. The effect of aging on deformations of the superficial femoral artery resulting from hip and knee flexion: potential clinical implications. J. Vasc. Intervent. Radiol. 21, 195 202. Czihal, M., Banafsche, R., Hoffmann, U., Koeppel, T., 2015. Vascular compression syndromes. Vasa 44, 419 434. Greenway, C.V., Lautt, W.W., 1986. Blood volume, the venous system, preload, and cardiac output”. Can. J. Physiol. Pharmacol. 64 (4), 383 387. Guiotto, G., Masarone, M., Paladino, F., Ruggiero, E., Scott, S., Verde, S., et al., 2010. Inferior vena cava collapsibility to guide fluid removal in slow continuous ultrafiltration: a pilot study. Intensive Care Med. 36, 692 696. Hogervorst, T., Vereecke, E.E., 2014. Evolution of the human hip. Part 1: the osseous framework. J. Hip Preserv. Surg. 1 (2), 39 45. Jager, K., Seifert, H., Bollinger, A., 1989. M-mode echovenography: a new technique for the evaluation of venous wall and valve motion. Cardiovasc. Res. 23, 25 30. Jardin, F., Vieillard-Baron, A., 2006. Ultrasonographic examination of the venae cavae. Intensive Care Med. 32, 203 206.

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Kibbe, M.R., Ujiki, M., Goodwin, A.L., Eskandari, M., Yao, J., Matsumura, J., 2004. Iliac vein compression in an asymptomatic patient population. J. Vasc. Surg. 39 (5), 937 943. Kircher, B.J., Himelman, R.B., Schiller, N.B., 1990. Noninvasive estimation of right atrial pressure from the inspiratory collapse of the inferior vena cava. Am. J. Cardiol. 66, 493 496. Krause, I., Birk, E., Davidovits, M., Cleper, R., Blieden, L., Pinhas, L., et al., 2001. Inferior vena cava diameter: a useful method for estimation of fluid status in children on haemodialysis. Nephrol. Dial. Transplant. 16 (6), 1203 1206. Kuo, W.T., Robertson, S.W., Odegaard, J.I., Hofmann, V.L., 2013. Complex retrieval of fractured, embedded, and penetrating inferior vena cava filters: a prospective study with histologic and electron microscopic analysis. J. Vasc. Interv. Radiol. 24, 622 630. Kutty, S., Li, L., Hasan, R., Peng, Q., Rangamani, S., Danford, D.A., 2014. Systemic venous diameters, collapsibility indices, and right atrial measurements in normal pediatric subjects. J. Am. Soc. Echocardiogr. 27 (2), 155 162. Laborda, A., Sierre, S., Malve, M., De Blas, I., Ioakeim, I., Kuo, W.T., et al., 2014. Influence of breathing movements and Valsalva maneuver on vena caval dynamics. World J. Radiol. 6 (10), 833 839. Laborda, A., Kuo, W.T., Ioakeim, I., De Blas, I., Malve, M., Lahuerta, C., et al., 2015. Respiratory-induced haemodynamic changes: a contributing factor to IVC filter penetration. Cardiovasc. Interv. Radiol. 38 (5), 1192 1197. Levangie, P., Norkin, C., 2005. Joint Structure and Function: A Comprehensive Analysis, fourth ed. The F. A. Davis Company, Philadelphia, PA. Li, H., Sun, X., Liu, G., Zhang, Y., Chu, J., Deng, C., et al., 2013. Endovascular stent placement for nutcracker phenomenon. J. X-Ray Sci. Technol. 21 (1), 95 102. Lytle, W.J., 1979. Inguinal anatomy. J. Anat. 128 (3), 581 594. Lytle, W.J., 1974. The inguinal and lacunar ligaments. J. Anat. 118 (2), 241 251. Miller, J.D., Pegelow, D.F., Jacques, A.J., Dempsey, J.A., 2005. Skeletal muscle pump versus respiratory muscle pump: modulation of venous return from the locomotor limb in humans. J. Physiol. 563 (3), 925 943. Moazzam, C., Heddings, A.A., Moodie, P., Cole, P.A., 2012. Anterior pelvic subcutaneous internal fixator application: an anatomic study. J. Orthop. Trauma 26 (5), 263 268. Moneta, G.L., Bedford, G., Beach, K., Strandness, D.E., 1988. Duplex ultrasound assessment of venous diameters, peak velocities, and flow patterns. J. Vasc. Surg. 8, 286 291.

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Murphy, E., et al., 2009. Volume associated dynamic geometry and spatial orientation of the inferior vena cava. J. Vasc. Surg. 50, 835 843. Murphy, E.H., Johnson, E.D., Arko, F.R., 2008. Evaluation of wall motion and dynamic geometry of the inferior vena cava using intravascular ultrasound: implications for future device design. J. Endovasc. Ther. 15, 349 355. Nakamura, K., Tomida, M., Ando, T., Sen, K., Inokuchi, R., Kobayashi, E., et al., 2013. Cardiac variation of inferior vena cava: new concept in the evaluation of intravascular blood volume. J. Med. Ultrason. 40 (3), 205 209. Narayan, A., Eng, J., Carmi, L., McGrane, S., Ahmed, M., Sharrett, A.R., et al., 2012. Iliac vein compression as risk factor for left- versus right-sided deep venous thrombosis: case-control study. Radiology 265 (3), 949 957. Poyraz, A.K., Firdolas, F., Onur, M.R., Kocakoc, E., 2013. Evaluation of left renal vein entrapment using multidetector computed tomography. Acta Radiol. 54, 144 148. Raju, S., Neglen, P., 2006. High prevalence of nonthrombotic iliac vein lesions in chronic venous disease: a permissive role in pathogenicity. J. Vasc. Surg. 44, 136 144. Reeves, J.T., Grover, R.F., Blount, S.G., Filley, G.F., 1961. Cardiac output response to standing and treadmill walking. J. Appl. Physiol. 16, 283 288. Uhl, 2015. Anatomy of the Hunter’s canal and its role in the venous outlet syndrome of the lower limb. Phlebology 30 (9), 604 611. Veniti Inc., 2014. Cadaver Study Report, Document #STERSD-005-B (Unpublished Data). Veniti Inc., 2017. Veniti VICI Venous Stent Fractures Root Cause and Clinical Implications (Unpublished Data). Wade, O.L., Bishop, J.M., 1962. Cardiac Output and Regional Blood Flow. Blackwell Scientific Publications, Oxford, pp. 26 50. Wallace, D.J., Allison, M., Stone, M.B., 2010. Inferior vena cava percentage collapse during respiration is affected by the sampling location: an ultrasound study in healthy volunteers. Acad. Emergency Med. 17 (1), 96 99. Wang, X., Zhang, Y., Li, C., Zhang, H., 2012. Results of endovascular treatment for patients with nutcracker syndrome. J. Vasc. Surg. 56, 142 148. Winter, D.A., 1991. The Biomechanics and Motor Control of Human Gait: Normal, Elderly and Pathological, second ed. University of Waterloo Press, Waterloo. Wu, Z., Zheng, X., He, Y., Fang, X., Li, D., Tian, L., et al., 2016. Stent migration after endovascular stenting in patients with nutcracker syndrome. J. Vasc. Surg. Venous Lymphat. Disord. 4, 193 199.

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C H A P T E R

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Developing Boundary Conditions for Device Design and Durability Evaluation Christopher P. Cheng Division of Vascular Surgery, Stanford University, Stanford, CA, United States

Having a bunch of good data is one thing, but applying it is another. This chapter leverages the vascular deformation data derived from medical imaging, geometric modeling, and various quantification techniques and converts them into usable boundary conditions for device design and durability evaluation. In other words, the following discussion is about data science. Wikipedia calls data science “an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms.” But this is not the type of data science that incorporates machine learning and data mining of humongous data sets; it is more about how to squeeze every ounce of usefulness out of small, focused collections of data.

CHOOSING DEFORMATION METRICS After quantifying deformations via medical imaging, image processing, geometric modeling, and quantification, it is time to translate

Handbook of Vascular Motion DOI: https://doi.org/10.1016/B978-0-12-815713-8.00013-9

those deformations into actual mechanical boundary conditions. This usually requires picking the correct set and severity of metrics, distilling available data with statistics, and defining the duty cycle and number of repetitions of that cycle. Regardless of what the vascular implant is, a good starting point is reviewing the mechanical durability guidance documents set by the US Food and Drug Administration (FDA), ASTM International (previously American Society for Testing and Materials), and International Organization for Standardization (ISO). These include the following: 1. FDA Guidance Document 1545 (2010) “Non-Clinical Engineering Tests and Recommended Labeling for Intravascular Stents and Associated Delivery Systems” (REF) Section IV.B.9,10,11: Non-clinical engineering tests—Stent dimensional and functional attributes—Stress/strain analysis, Fatigue analysis, Accelerated durability testing

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2. ASTM F2477-07 (2013) “Standard Test Methods for in vitro Pulsatile Durability Testing of Vascular Stents” (REF) 3. ASTM F2942-13 (2013) “Standard Guide for in vitro Axial, Bending, and Torsional Durability Testing of Vascular Stents” (REF) 4. ASTM F2514-08 (2014) “Standard Guide for Finite Element Analysis (FEA) of Metallic Vascular Stents Subjected to Uniform Radial Loading” (REF) 5. ISO 25539-1:2017 (2017) “Cardiovascular implants—Endovascular devices—Part 1: Endovascular prostheses” (REF) Section 8.5.2.2,3: Design evaluation— Bench and analytical tests—Endovascular prosthesis—Fatigue and Durability— Computational analyses, in vitro testing 6. ISO 25539-2:2017 (2017) “Cardiovascular Implants—Endovascular Devices—Part 2: Vascular Stents” (REF) Section 8.6.3.5.2,3,4: Design evaluation—Stent—Stent Integrity— Durability—Stress/strain analyses, Fatigue safety factor determination, Fatigue durability testing 7. ISO 25539-3:2017 (2017) “Cardiovascular Implants—Endovascular Devices—Part 3: Vena Cava Filters” (REF) Section 8.5: Design evaluation—Bench and analytical tests 8. ISO 7198:2016 (2016) “Cardiovascular Implants and Extracorporeal Systems— Vascular Prostheses—Tubular Vascular Grafts and Vascular Patches” (REF) Section 8.7: Design evaluation—Bench and analytical tests 9. ISO 1099:2017 (2017) “Metallic materials— Fatigue testing—Axial Force-Controlled Method” (REF) Upon reviewing these guidance documents, you will notice that they include several qualifying statements about how these documents

are to be used only as guidance; they do not include many quantitative details about deformation conditions. The documents encourage companies to perform their own literature reviews, and animal, cadaver, and clinical testing to determine their own defendable boundary conditions for durability evaluation. Furthermore, while the guidance related to pulsatile radial testing is more detailed, the information related to other deformation modes (e.g., bending, axial, twist, cross-sectional) and other sources of deformation (e.g., respiration, musculoskeletal, and external influences) is much more sparse. That is why this book exists: to help provide some guidance in these lessdefined areas. Perhaps one way to think about durability evaluation is that the published standards and guidance documents provide rules on how to format durability testing, but you still need to generate the content to reflect the reality of your specific device and clinical indication. The deformation conditions are not only based on need but on the availability of information via literature and internal testing, which in turn is bounded by medical imaging and quantitative methods. Moreover, the boundary conditions often need to be adapted to the available benchtop and computational evaluation methods. For example, while it is tempting to define the deformation of a bending artery or stent with a change in angulation, angulation is often ill-defined (Fig. 13.1). Without specific segment lengths with which to define angulation, these measurements are worthless. In fact, even when “properly” defined, unless a specific curvature is specified at the bending vertex, there is a risk of discontinuity and excessive kinking deformation at that vertex. For these reasons, curvature and curvature change, along well-defined lengths, are often superior to angulation and bend angle measurements.

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FIGURE 13.1 Example of ill-defined stent bend angle measurements. The images are of neurovascular stents imaged in vitro using C-arm computed tomography imaging in three different bend configurations. The measurements from the original publication (top row) deemed the stent bend angles to be 120 degrees (left), 90 degrees (middle), and 30 degrees (right). However, the methods did not define the segment lengths, the vertex of the bend, and whether the measurements were performed on the centerline/inner curve/outer curve. With explicit methods (bottom row) defining 5 mm segment lengths, vertex locations that result in the greatest bend angles, and using the stent centerlines, the bend angles were reassessed to be 150 degrees (left), 140 degrees (middle), and 105 degrees (right). Adapted from Ebrahimi, N., Claus, B., Lee, C.Y., Biondi, A., Benndorf, G., 2007. Stent conformity in curved vascular models with simulated aneurysm necks using flat-panel CT: an in vitro study. Am. J. Neuroradiol. 28 (5), 823 829, Figure 4.

SAMPLE STATISTICS The drawback of the scarcity of knowledge about vascular deformations is that sparse, disparate pieces of data need to be pooled together to construct boundary conditions. The benefit is the inherent ease of working with small samples of data. The first place to start is in the peer-reviewed literature, where the study methods and results have been vetted by experts, and the rigor is largely trusted by regulatory agencies and notified bodies. In

addition, published studies on vascular deformation tend to contain data on 5 10 patients or more, and the methods are consistent at least within that sample population. It is recognized by the regulatory bodies that these types of studies are often expensive, difficult to justify ethically, and require additional effort from physicians and patients; thus, small sample sizes are often allowed. Data from literature are most often presented in the form of mean and standard deviation, median and interquartile range, or

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FIGURE 13.2 If a population has a Gaussian distribution, then 68%, 95%, and 99.7% of the population is contained within one, two, and three standard deviations of the mean, respectively. From https://en.wikipedia.org/wiki/File: Empirical_Rule.PNG.

simply the range. Mean and standard deviation measurements are most useful when the data has a Gaussian distribution (i.e., normally distributed) because then simple relationships between standard deviations and population percentiles can be drawn. For example, approximately 68% of the population will be encompassed within one standard deviation of the mean, 95% within two standard deviations, and 99.7% within three standard deviations (Fig. 13.2). In order to test if a sample of data is drawn from a normally distributed population, a Lilliefors test can be used. The Lilliefors test is based on the Kolmogorov Smirnov test and informs whether a sample is significantly different from a Gaussian distribution (Lilliefors, 1967). If it is not significantly different, then parametric methods can be used; otherwise, non-parametric methods are more appropriate. Presentation of data with interquartile ranges can be more useful in the case of nonGaussian-distributed data. With no assumption about how data is distributed, a population can be described in this manner with five numbers: minimum, first quartile, median, third

quartile, and maximum values. For example, even with high skewness (measure of distribution asymmetry) and kurtosis (measure of likelihood of outliers), these descriptors are valid. Even better, when the data has been selfgenerated, or in publications where all data points are presented, arbitrary percentile limits can be calculated with simple functions within any statistical software package. Another important pair of concepts to consider when collecting and using sample data is sample selection and sample size. Sample size is the number of data points collected from a general population, and sample selection is how those samples are chosen. For example, if the goal is to understand how carotid stents deform after being implanted into the carotid artery, patients with carotid stents must be selected from the population of all patients with carotid stents. To best represent the current carotid stent indication, sample data should be composed mainly of symptomatic patients with risk factors to surgical endarterectomy, which include older age, location inferior to the clavicle, cardiac and coronary

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comorbidities, pulmonary disease, and renal disease. However, if the goal is to understand the biomechanics of patients who fall into a proposed set of expanded indications for carotid stenting, perhaps asymptomatic patients with lower risk to surgery should be considered. Note that the careful selection of patient age, height, weight, gender, ethnicity, etc., can help improve the utility of the data. To define an appropriate sample size, both confidence interval and confidence level need to be considered. Confidence interval, also known as margin of error, refers to the plus or minus variation that a particular value, calculated from the sample data, compares to the actual value for the entire population. For example, if the average axial deformation of a carotid stent within a sample population is 4% with a confidence interval of 2%, then the entire population would be expected to have an average axial deformation between 2% and 6%. Confidence level is the percentage certainty that the sample population and confidence interval represent the entire population. Continuing from the previous example, a confidence level of 90% means that there is 90% certainty that the average carotid stent axial deformation is within 2% 6% for the entire population. Relating back to sample size, tighter confidence intervals and greater confidence levels can be achieved with increasing sample size. In other words, a sufficient sample size must be collected in order to achieve a certain confidence level that the sample will represent the total population within a certain confidence interval. While smaller samples of data are easier, faster, and cheaper to collect, it is less likely that a smaller sample size will accurately characterize the general population. This lower confidence and accuracy could misrepresent the population as a whole in either direction; the sample could either overestimate or underestimate the mean and variance of severity of vascular deformation. Because underestimating deformation severity could potentially

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result in underestimated fracture occurrence, small sample data sets may warrant using greater safety factors by utilizing multiples of the confidence interval on the high end.

DEFINING THE DUTY CYCLE The duty cycle is the complete deformation cycle that is the recurring unit in a repetitive test. The following examples show the construction of example duty cycles for diametric distension, axial length change, and bending boundary conditions.

Diametric Deformation Example To perform benchtop durability testing of the diametric distension of the common femoral artery, the duty cycle is comprised of the progression of diametric change, from expansion back to retraction. Time-resolved medical imaging can be used to define the exact temporal progression of diametric change, that is, the systolic expansion and retraction period taking up less of the cardiac cycle compared to the diastolic resting period; however, for the purposes of this discussion, we will discuss only the maximum deformation values with no attention to temporal progression. The following is a summary of published studies that are the most relevant for determining the boundary conditions for intravascular device durability evaluation in the common femoral artery due to cardiac pulsatility (Table 13.1). These studies include healthy volunteers and patients who have risk factors related to cardiovascular disease and use similar methods to quantify vessel diameter, that is, ultrasound tracking of the arterial walls. From these references, the boundary conditions of varying severity can be constructed. For example, it is well known that hypertension causes less diametric distension due to

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TABLE 13.1 Summary of Population, Pulse Pressure, and Diametric Distension of the Femoral Artery in Healthy Volunteers and Patients With Cardiovascular Disease Risk Factors Study

Population

Pulse P (mmHg)

Diametric Distension (%)

Henry et al. (2003)

Impaired glucose metabolism, 70.3 6 6.3 years

70 6 16

1.72 6 0.57

Henry et al. (2003)

Type 2 diabetic, 67.3 6 8.1 years

74 6 18

1.87 6 0.67

Benetos et al. (1993)

Healthy/hypertensive, 47 6 6 years

62.5 6 2.5

3.47 6 0.18

Willekes et al. (1998)

Healthy women, 18 35 years

47 6 6

3.43 6 2.00

Data shown as mean 6 standard deviation. Pulse P, Pulse pressure.

the fact that the vessels are under higher pressure, the collagen fibers are tauter, and the wall stiffness increases. Thus, more severe diametric distension conditions would be derived from healthy patients without hypertension. See the following “moderate” and “aggressive” scenarios: Moderate case—Maximum distension of 2% could be considered moderate for common femoral artery diametric pulsatility since it is just greater than the mean distension experienced by the common femoral arteries of patients with impaired glucose metabolism (1.72%) and type 2 diabetes (1.87%) (Henry et al., 2003). In fact, the patients in need of common femoral artery implants for occlusive disease would likely exhibit these same risk factors, with the addition of stiffened, atherosclerotic femoral arteries. Aggressive case—Maximum distension of 3.5% could be considered aggressive for common femoral artery diametric pulsatility since it is greater than the average 3.47% common femoral artery diametric distension reported by Benetos et al. (1993), in both healthy and hypertensive subjects. It is also greater than the average 3.42% diametric distension reported by Willekes et al. (1998), in a population of young, healthy women.

For arterial pulse pressure, defined as the difference between diastolic and systolic blood pressure, the greatest magnitude was reported by Henry et al. (2003) at 80 6 9 mmHg diastolic to 149 6 20 mmHg systolic (74 6 18 mmHg pulse pressure). The ASTM standard for pulsatile fatigue testing suggests 80 mmHg diastolic to 160 mmHg systolic pulsatile pressure, which is more aggressive than the magnitudes reported in the femoral artery literature (ASTM F2477-07, 2013). As such, it makes sense to follow the ASTM standard, satisfying the standard as well as being more aggressive than the literature. With tubing material that experiences 5% distension with 100 mmHg of pulse pressure, and a pulse pressure of 80 mmHg (80 mmHg diastolic and 160 mmHg systolic as suggested by ASTM), this would result in 4% tube diametric distension. This 4% exceeds the 3.5% distension compared to the “aggressive” case above and the associated literature (Benetos et al., 1993; Willekes et al., 1998). A boundary condition of 4% diametric distension driven by an 80 160 mmHg diastolic to systolic pulse pressure in a 5% compliant tube (5% distension over 100 mmHg of pulse pressure) can be considered conservative because: 1. A diametric distension of 4% is greater than the data derived from young and healthy adults, which should exhibit greater arterial distension compared to the patients who need stenting for peripheral vascular occlusive disease (Willekes et al., 1998).

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2. A diametric distension of 4% is approximately three standard deviations above the mean for a population mixed with healthy and hypertensive adults aged 47 6 6 years (3.47 1 3 3 0.18 5 4.0) (Benetos et al., 1993). This means that not only is the sample population likely to have more compliant arteries compared to patients in need of stenting for peripheral vascular occlusive disease, but also 4% is approximately 99.85th percentile of the diametric distension of that population. 3. The pulse pressure of 80 mmHg (80 160 mmHg) recommended by ASTM F2477 is greater than the average 74 mmHg pulse pressure observed in diabetic, hypertensive adults aged 67.3 6 8.1 years (Henry et al., 2003). 4. The combination of aggressive diametric distension comparable to more compliant vessels in healthy adults AND aggressive pulse pressure, as exhibited in diabetic, hypertensive patients, yields a conservative

pulsatile diametric distension boundary condition.

Axial Length Deformation Example The next example focuses on developing a leg flexion-induced axial length deformation duty cycle for the superficial femoral artery (SFA) based on published data. The most relevant data come from two publications from the same investigators, both reporting how implanted nitinol stents deform with hip and knee flexion commensurate with walking and stair-climbing (Nikanorov et al., 2008, 2013). The measurements were taken from lateral plain film X-ray images. Table 13.2 shows the published axial length deformations based on location, that is, middle SFA, distal SFA 1 proximal popliteal artery (PA), and PA. Since it is known that axial length deformations of the femoropopliteal artery increase closer to the knee, the middle SFA data will tend not to represent the worst case

TABLE 13.2 Axial Length Deformations of Implanted Femoropopliteal Artery Stents with Hip and Knee Flexion Study

Population and Condition

Flexion Angles

Anatomic Location

Axial Shortening (%)

Nikanorov et al. (2008)

Cadaver, single stents

20 degrees hip 70 degrees knee

mSFA dSFA/pPA PA

362 461 664

Nikanorov et al. (2008)

Cadaver, single stents

90 degrees hip 90 degrees knee

mSFA dSFA/pPA PA

363 663 11 6 5

Nikanorov et al. (2008)

PAD patients, single and overlap

20 degrees hip 70 degrees knee

mSFA dSFA/pPA PA

1.7 6 1.7 2.4 6 0.4 3.5 6 2.7

Nikanorov et al. (2008)

PAD patients, single and overlap

90 degrees hip 90 degrees knee

mSFA dSFA/pPA PA

3.1 6 1.8 5.3 6 0.5 8.5 6 3.2

Data shown as mean or mean 6 standard deviation. SFA, Superficial femoral artery; PA, popliteal artery; p, proximal; m, middle; d, distal; PAD, peripheral artery disease.

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deformations. Thus the focus should be on the data from the distal SFA and PA. From these data the following “moderate” and “aggressive” scenarios can be justified: Moderate case—For walking flexion, Nikanorov et al. (2008) reported an average axial stent shortening of 4% in the distal SFA 1 proximal PA in cadavers with flexion angles commensurate with walking. For stair-climbing flexion, the same publication reported an average axial stent shortening of 6% in the distal SFA 1 proximal PA in cadavers with flexion angles commensurate with stair-climbing. Aggressive case—For walking flexion, Nikanorov et al. (2008) reported a mean 1 1 standard deviation axial stent shortening of 5% in the distal SFA 1 proximal PA for flexion angles commensurate with walking. For stair-climbing flexion, the same publication reported a mean 1 1 standard deviation axial stent shortening of 9% in the distal SFA 1 proximal PA for flexion angles commensurate with stair-climbing. The “aggressive case” can be considered conservative because: 1. The data was derived from 90 degrees hip flexion and 90 degrees knee flexion, which are on the upper end of joint angles for stair-climbing. This yields more aggressive deformations because higher flexion angles result in greater vessel axial length deformations. 2. For both walking and stair-climbing deformations, the axial length deformation proposed is the sample population mean 1 1 standard deviation, which would cover approximately 84% of the population. 3. The data was derived from cadaver specimens, which tend to exhibit greater axial length deformations compared to diseased living patients (Nikanorov et al., 2008). This may be because these particular

cadavers did not have peripheral vascular disease, which means the arteries would exhibit greater elasticity and axial length deformation. However, since these cadaver measurements were taken from 2D lateral plain film X-rays, it is not clear whether these quantified axial deformations are representative of the axial deformation in three dimensions. If the stents remained in the sagittal plane, these measurements would be accurate; however, deviation from the sagittal plane could render the measurements under- or overestimated.

Bending Deformation Example The following is a fictitious example of defining the stent bending duty cycle for an iliac blood vessel stent under development. A set of 20 patients implanted with commercially available iliac vessel stents were imaged using 3D computed tomography in the supine and two flexed-hip positions. The patients’ legs were positioned with foam pillows to produce hip flexion angles of 30 and 90 degrees, meant to be commensurate with walking and stairclimbing, respectively. Note that the maximum hip flexion is 20 30 degrees for walking and the approximately 70 90 degrees for stairclimbing (Barr and Backus, 2001). From these images, 3D geometric models of the stents were constructed with perpendicular lumen segmentation and centerline extraction methods. The centerlines of each stent, for each of the three hip positions, were then used to calculate pointwise curvature by fitting circles to three equidistant centerline points spanning a window length equal to approximately the diameter (10 mm) of the blood vessel. By using branch vessels as fiducial markers and normalizing for arclength changes, material points between pairs of anatomic states were matched in order to calculate the curvature changes

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TABLE 13.3 Sample Statistics of Centerline Curvatures and Curvature Changes of Iliac Vessel Stents in Hip Positions Corresponding to Supine, Walking, and Stair-Climbing at the Location of Maximum Bending Centerline Curvature (cm21)

Curvature Change (cm21)

Hip 5 0 degrees

Hip 5 30 degrees

Hip 5 90 degrees

Walking

Stair-Climbing

Average

0.107

0.132

0.193

0.025

0.086

Stdev

0.015

0.020

0.042

0.026

0.041

Min

0.073

0.090

0.133

2 0.009

0.033

Max

0.137

0.182

0.278

0.084

0.168

50%ile

0.106

0.131

0.182

0.020

0.082

75%ile

0.115

0.140

0.223

0.038

0.119

90%ile

0.123

0.154

0.246

0.060

0.128

Stdev, Standard deviation; Min, minimum; Max, maximum; 50%ile, 50th percentile; 75%ile, 75th percentile; 90%ile, 90th percentile.

along the entire length of the stent. Table 13.3 shows the population-derived centerline curvatures of the implanted stents at the location of maximum bending under varying degrees of hip flexion. Since the deformation magnitude, or cyclic change in curvature, is what predominantly drives alternating strain and mechanical fatigue, the curvature change value is the most important. First, we take the “Average” curvature in the 0 degree hip flexion position, which is the population-averaged baseline curvature at the location of maximum stent bending. Then, we add various amounts of curvature change to that average baseline curvature in order to represent walking or stair-climbing deformation, with varying levels of percentage population coverage. These curvatures translate into radius of curvature conditions of: Walking Supine curvature 5 0.107 cm21-supine radius 5 9.36 cm Walking curvature (50th percentile) 5 supine curvature 1 walking change (50th percentile)

5 0.107 1 0.020 cm21 5 0.127 cm21 -walking radius (50th percentile) 5 7.90 cm Walking curvature (75th percentile) 5 supine curvature 1 walking change (75th percentile) 5 0.107 1 0.038 cm21 5 0.145 cm21 -walking radius (75th percentile) 5 6.92 cm Walking curvature (90th percentile) 5 supine curvature 1 walking change (90th percentile) 5 0.107 1 0.060 cm21 5 0.167 cm21-walking radius (90th percentile) 5 5.98 cm Stair-Climbing Supine curvature 5 0.107 cm21-supine radius 5 9.36 cm Stair-climbing curvature (50th percentile) 5 supine curvature 1 stair change (50th percentile) 5 0.107 1 0.082 cm21 5 0.189 cm21-stairclimbing radius (50th percentile) 5 5.30 cm

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Stair-climbing curvature (75th percentile) 5 supine curvature 1 stair change (75th percentile) 5 0.107 1 0.119 cm21 5 0.226 cm21-stairclimbing radius (75th percentile) 5 4.43 cm Stair-climbing curvature (90th percentile) 5 supine curvature 1 walking change (90th percentile) 5 0.107 1 0.128 cm21 5 0.235 cm21-stairclimbing radius (90th percentile) 5 4.26 cm The following bending boundary conditions can be considered to be aggressive because: Walking: Radius of curvature from 9.4 cm to 6.0 cm Stair-climbing: Radius of curvature from 9.4 cm to 4.3 cm 1. Hip flexion angles used for walking and stair-climbing were 30 and 90 degrees, respectively, which are on the upper end of hip flexion angles for those body motions. This yields aggressive deformations because the data shows that higher hip flexion angles result in greater vessel bending. 2. Maximum pointwise curvature changes along the entire length of the stent, between paired anatomic hip positions, were used to calculate the amount of incremental curvature to add to the baseline straight-hip position. This represents the location on the stent with the highest bending deformation. If this bending condition is applied to a finite length of stent, then more of the stent will undergo this deformation compared to the single point as observed in the study patients. 3. For both walking and stair-climbing conditions, 90th percentile values of the maximum curvature changes were used. This covers 90% of the maximum bending condition in the sample population.

4. For walking, this 90th percentile curvature change is more than one standard deviation above the mean (0.060 cm21 . 0.025 1 0.026 cm21), as is also the case for stair-climbing (0.128 cm21 . 0.086 1 0.041 cm21). So if the population data for bending was Gaussian distributed, then this provides evidence that these aggressive conditions would cover more than 84% of the population. In this fictitious example, the iliac vessel stents studied in the patient population were of a commercially-available stent; however, the bending boundary conditions were to be used for designing and testing a preclinical stent under development. It is important to understand the bending stiffness of the new stent in relation to the commercially-available stent. For example, if the new stent exhibits lower bending stiffness compared to the existing stent, then it may experience greater bending deformations under the same conditions. If, however, the new stent is stiffer, the bending deformations may be less. But if the musculoskeletal-induced bending of the blood vessel is predominantly displacement-controlled, meaning the anatomic forces causing the bending far exceed the stiffness of the stent, then the bending may be relatively independent of the stent properties.

Other Deformations and Considerations Similar methods to those described above can also be used to develop other deformation boundary conditions from raw data. In reality, many of these deformations may be superimposed, creating multimodal deformations. For example, axial length, axial twist, and bending deformations may occur simultaneously in a leg artery during hip and knee flexion. While theoretically all of these deformations can be combined in computational simulations and

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benchtop testing, in practice the methods to impose simultaneous multimodal deformations may be very challenging. There are certain combinations of deformations that can be reproduced with specialized methods or equipment. For example, axial length and axial twist of a tubular structure can be combined by changing the distance of one end fixture with respect to another end fixture while rotating one of the end fixtures on its own axis. In addition, if the end fixtures can prescribe pulsatile pressure into a compliant tube, then diametric distension can be added to the mix of deformations. Note that in order to enforce precise diametric change, the device must be oversized in the compliant tube, meaning the device will always be in contact with the wall of the tube, even during the expanded state. Furthermore, an external structure can be used to deform the crosssectional shape of the tubular device to arrive at four simultaneous modes of deformation (Fig. 13.3).

FIGURE 13.3 Depiction of multimodal deformation with superimposed symmetric diametric (green), asymmetric cross-sectional crush (blue), axial twist (red), and axial length (black) deformations.

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There are several rules of thumb when combining different deformation modes: 1. Axial length and axial twist deformations can be combined as long as the sample is always under axial tension. If the sample shortens past the point of slack, the result would be helical torsion, also described as out-of-plane curvature or mathematical torsion. 2. Axial length and bending deformations can be combined into one duty cycle to occur serially (not simultaneously). To do this, first place the sample under axial tension and then shorten the sample until it is just at the point of slack. At this point, the sample has only experienced axial length change thus far. However, if the ends of the sample are brought even closer together, then the sample can be made to curve off-axis, causing bending deformation. 3. To combine axial length and bending deformations simultaneously, the sample needs to be under constant axial tension, and a cylinder with a particular diameter can be positioned perpendicular to the length of the sample and pushed toward it. Note that this may also cause simultaneous cross-sectional deformation unless the sample has sufficient internal pressure to keep the cross-section circular. 4. Cross-sectional deformations can be combined with any other deformation mode by external structures pressing inward. However, for deformations that move off axis (e.g., bending, torsion), the position and orientation of the simultaneous crosssectional deformation may not be very precise. While deformation modes are imposed by a specific amount of perturbation (e.g., 1 cm axial length change, 45 degrees axial twist, 0.5 cm21 increase curvature, 0.3 cm cross-sectional crush), all deformations actually need to be prescribed over a certain length of sample. In

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the case of axial length and axial twist deformations, the longer the length, the more the deformation is spread out and the milder the strains. In the case of bending, diametric, and cross-sectional deformations, longer lengths translate to more material being deformed simultaneously. For example, a particular increase of curvature imposed on a 10 cm length of sample will result in double the amount of sample strained as compared to a 5 cm length of sample. This can come in handy when trying to manipulate statistical powering for data collection. Another consideration for determining vascular deformation boundary conditions is the variety of drivers of motion. For example, while in most Western cultures, squatting and kneeling are not large portions of daily activity, in many parts of Asia and the Middle East, much of the population spends hours a day dining and praying in these body positions. These extreme levels of hip and knee flexion will amplify deformations of the lower extremity blood vessels. In other words, it is critical to

understand the patient population and realize that environmental and cultural differences may dramatically affect body motions and thus blood vessel deformations.

NUMBER AND FREQUENCY OF CYCLES Once the duty cycle has been developed, the number of cycles needs to be defined. In the case of benchtop durability testing, the number of cycles and frequency of repetition are used as equipment parameters, while for computational analysis, the number of cycles in combination with computed stresses and strains are used for fatigue analysis. See Table 13.4 for estimates of cycle counts for some common anatomic and physiologic drivers of vascular deformation. It is important to note the patient populations from which these numbers are derived in order to check their relevance with a particular treatment indication. For example, the cardiac and respiratory count estimates

TABLE 13.4 Approximate Annual Number of Cycles for Common Sources of Vascular Deformation Deformation Source

Number of Cycles Rationale

Cardiac pulse

B40M/year

The average adult heart rate is 72 beat/min-72 beat/min 3 60 min/ h 3 24 h/day 3 365 days/year 5 37.8 M beat/year

Respiration (Hooker et al., 1989)

B10M/year

The average adult respiration rate is 20 breaths/min-20 breaths/ min 3 60 min/h 3 24 h/day 3 365 days/year 5 10.5 M breaths/year

Valsalva maneuver (Hsu et al., 1994)

B6000/year

Valsalva occurs during weight lifting, defecation, coughing, etc. Coughing is the most common of these activities, and occurs 0 16 times/day-16 coughs/day 3 365 days/year 5 5840 cycles/year

Walking

B1M/year

The average healthy adult walks 2.5 miles/day and it takes an average of 2000 steps to walk a mile-(5000 steps/day 3 365 days/year)/2 legs 5 0.9125 M steps/year

Stair-Climbing and sitting (Morlock et al., 2001)

B75K/year

In healthy adults, the average number of sitting cycles is 63 sits/day and stair-climbing cycles is 278 stairs/day-{63 sits/day 1 [(278 stairs/ day)/2 legs]} 3 365 days/year 5 73,730 cycles/year

Kneeling (Mulholland and Wyss, 2001)

B10K/year

Up to 25 extreme kneeling cycles/day-25 kneels/day 3 365 days/ year 5 9125 cycles/year

K, Thousand; M, million.

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GOLDILOCKS ZONE

were derived from healthy adults (Hooker et al., 1989; Hsu et al., 1994), while the stairclimbing and sitting cycles were derived from patients with total hip replacements (Morlock et al., 2001). Estimates of cycle count for other drivers of motion can be calculated in similar ways. The annual cycle counts shown in the preceding table can be used to determine the total number of cycles to be used for benchtop durability testing and for computational fatigue analysis. For example, while regulatory guidance for most vascular devices suggest testing to 10 years of operation, heart valve devices may require up to 15 years of operation. It is also sometimes possible to get an idea of longer term performance by extrapolating from shorter term data. For example, if an estimate of benchtop durability results is required in 1 month in a development program, and the full 10-year equivalent of cycling requires 5 months of testing, 2-year equivalent results (which can be completed in 1 month) can be used to extrapolate up to the 10-year results using statistical fatigue analysis techniques. Note that testing frequency can also be varied to affect the speed of benchtop durability testing, however, beware limitations with respect to testing equipment and inertial effects.

GOLDILOCKS ZONE It may be tempting to use boundary conditions that represent the average case since they are more easily passable regarding fatigue acceptance criteria. However, it is nearly impossible to truly know what the “average” case is, considering the errors involved with medical imaging, image processing, deformation quantification, small sample sizes, and dissimilarities between the sample population and the actual patient population. Moreover, the average case would cover only about half

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of the eligible population, which would preclude the general use of a product. In addition, how would physicians choose which half of the population is eligible for safe use of the product? Severity of vascular motion is unknowable using standard diagnostic techniques. On the other hand, it may be tempting to use extremely conservative boundary conditions, that is, overly aggressive conditions that will cover the most extreme use cases. While these conditions would challenge the fatigue performance of the product to a high degree, they may go too far by indicating fatigue failures that would actually not happen in patients, or at least not happen in a meaningful percentage of patients. This can be especially damning when “corners” testing is implemented, when the minimum and maximum material limits (due to manufacturing tolerances) are compounded onto benchtop fatigue and computational simulation testing. The danger of this strategy is the prevention of continued development and approval of a product that could otherwise help thousands of patients, not to mention wasting resources. Hence, we must seek the Goldilocks zone, where boundary conditions are chosen to be reasonably conservative, covering a large majority of the population without being overly aggressive (Fig. 13.4). The tools at the tester’s disposal include the addition of standard deviations, percentile calculations, safety factors, and defendable rationale related to how the sample population may exhibit more aggressive vascular deformations compared to the target patient population. Since regulatory agencies and notified bodies rely on the manufacturers to decide on the conditions to which their products should be evaluated, this is an exemplary area to exercise reason, logic, and a little creativity when the available data does not perfectly fit the application.

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there is data available on a known device in another part of the anatomy. If a biomechanical correlation can be made between the two anatomies regarding physiologic drivers of motion (e.g., cardiac pulsatility, respiration, joint flexion) and magnitude of motion, then the data can be converted to the new anatomy or indication.

CONCLUSION

FIGURE 13.4 Vascular deformations in famous contortionist Hussein Yoga would pose a challenge for most peripheral vascular implants. From https://commons.wikimedia.org/wiki/File:Hussein_backbend.jpg.

Here are some common scenarios and strategies for finding the Goldilocks zone: 1. Vascular deformation data is only available in a population where the deformation magnitudes are known to be larger than in the patient population. In these cases, even if there is only a rough approximation of how much the two populations differ, then some reasonable assumptions and allowances can be made to adapt the available data to the device and indication in question. 2. Vascular deformation data is only available in a population treated with a commerciallyavailable predicate device. This is an ideal scenario to perform mechanical comparison testing between the predicate device and the device under development, to create a link between the two devices. With an established scaling factor, the vascular deformation boundary conditions can be translated for the new device. 3. There is no reliable data for the anatomic area and/or indication of interest; however,

Raw vascular deformation data from literature, animal studies, and clinical studies need to be converted into usable durability boundary conditions for benchtop testing and computational analysis. This process includes choosing the appropriate metrics, using statistical methods to sufficiently represent the target patient population, and establishing the duty cycle and number of cycles. While single-mode deformations are easiest to prescribe, some multimodal deformations are relatively easy to enforce in benchtop and computational environments, and add weight to the durability analysis for regulatory submission. Perhaps most importantly, a strategy must be developed to seek the Goldilocks zone, where the derived boundary conditions are aggressive enough to cover the vast majority of the target patient population, but not so conservative as to lead to false negatives that wrongly derail a product development program.

References ASTM F2477-07(2013), 2477. Standard Test Methods for In Vitro Pulsatile Durability Testing of Vascular Stents. ASTM International, West Conshohocken, PA. Available from: www.astm.org. ASTM F2514-08(2014), 2514. Standard Guide for Finite Element Analysis (FEA) of Metallic Vascular Stents Subjected to Uniform Radial Loading. ASTM International, West Conshohocken, PA. Available from: www.astm.org.

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ASTM F2942-13, 2942. Standard Guide for In Vitro Axial, Bending, and Torsional Durability Testing of Vascular Stents. ASTM International, West Conshohocken, PA. Available from: www.astm.org. Barr, A.E., Backus, S.I., 2001. Biomechanics of gait, Chapter 18. In: Nordin, M., Frankel, V.H. (Eds.), Basic Biomechanics of the Musculoskeletal System. Lippincott Williams & Wilkins, Philadelphia, PA, pp. 438 443. Benetos, A., Laurent, S., Hoeks, A., Boutouyrie, P., Safar, M., 1993. Arterial alterations with aging and high blood pressure. Arterioscler. Thromb. Vasc. Biol. 13, 90 97. Ebrahimi, N., Claus, B., Lee, C.Y., Biondi, A., Benndorf, G., 2007. Stent conformity in curved vascular models with simulated aneurysm necks using flat-panel CT: An in vitro study. Am. J. Neuroradiol. 28 (5), 823 829. FDA Guidance Document 1545, 2010. Non-clinical engineering tests and recommended labeling for intravascular stents and associated delivery systems. ,http://www.fda.gov/ cdrh/ode/guidance/1545.pdf. (accessed 18.04.10). Henry, R.M.A., Kostense, P.J., Spijkerman, A.M.W., Dekker, J.M., Nijpels, G., Heine, R.J., et al., 2003. Arterial stiffness increases with deteriorating glucose tolerance status. Circulation 107, 2089 2095. Hooker, E.A., O’Brien, D.J., Danzl, D.F., Barefoot, J.A.C., Brown, J.R., 1989. Respiratory rates in emergency department patients. J. Emerg. Med. 7, 129 132. Hsu, J.Y., Stone, R.A., Logan-Sinclair, R.B., Worsdell, M., Busst, C.M., Chung, K.F., 1994. Coughing frequency in patients with persistent cough: assessment using a 24 hour ambulatory recorder. Eur. Respir. J. 7, 1246 1253. ISO 1099:2017, 2017. Metallic Materials—Fatigue Testing— Axial Force-Controlled Method. International Organization for Standardization, Geneva. Available from: www.iso.org. ISO 25539-1:2017, 2017. Cardiovascular Implants— Endovascular Devices—Part 1: Endovascular Prostheses. International Organization for Standardization, Geneva. Available from: www.iso.org.

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ISO 25539-2:2017, 2017. Cardiovascular Implants— Endovascular Devices—Part 2: Vascular Stents. International Organization for Standardization, Geneva. Available from: www.iso.org. ISO 25539-3:2017, 2017. Cardiovascular Implants— Endovascular Devices—Part 3: Vena Cava Filters. International Organization for Standardization, Geneva. Available from: www.iso.org. ISO 7198:2016, 2016. Cardiovascular Implants and Extracorporeal Systems—Vascular Prostheses—Tubular Vascular Grafts and Vascular Patches. International Organization for Standardization, Geneva. Available from: www.iso.org. Lilliefors, H., 1967. On the Kolmogorov Smirnov test for normality with mean and variance unknown. J. Am. Stat. Assoc. 62, 399 402. Morlock, M., Schneider, E., Bluhm, A., Vollmer, M., Bergmann, G., Muller, V., et al., 2001. Duration and frequency of every day activities in total hip patients. J. Biomech. 34 (7), 873 881. Mulholland, S.J., Wyss, U.P., 2001. Activities of daily living in non-Western cultures: range of motion requirements for hip and knee joint implants. Int. J. Rehabil. Res. 24, 191 198. Nikanorov, A., Smouse, H.B., Osman, K., Bialas, M., Shrivastava, S., Schwartz, L.B., 2008. Fracture of selfexpanding nitinol stents stressed in vitro under simulated intravascular conditions. J. Vasc. Surg. 48, 435 440. Nikanorov, A., Schillinger, M., Zhao, H., Minar, E., Schwartz, L.B., 2013. Assessment of self-expanding nitinol stent deformation after chronic implantation into the femoropoliteal arteries. EuroIntervention 9, 730 737. Willekes, C., Hoogland, H.J., Hoeks, A.P.G., Reneman, R.S., 1998. Bladder filling reduces femoral artery wall distension and strain: beware of a full bladder. Ultrasound Med. Biol. 6, 803 807.

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Device Design and Computational Simulation C. Bonsignore Confluent Medical Technologies, Fremont, CA, United States

Humans have been making tools for more than two million years, and the evolution and development of our tools have defined the evolution of our species. Yet modern medicine is a comparatively new development, and catheterdirected intervention is even more so. The entire discipline of interventional medicine is hardly more than a few decades old, and I write to you as a first-generation native of this nascent discipline. Having spent the first 25 years of my professional career in this field, I am increasingly aware of how little we all know, and how much will soon be obsolete. Please consider this chapter a curiosity handed from one generation to the next, a collection of lessons learned that would have been helpful to know at the beginning of my career.

SINCE THE DAWN OF STENT ENGINEERING My viewpoint, as expressed here, is informed by more than two decades of experience as a consultant, partner, spectator, and critic to

Handbook of Vascular Motion DOI: https://doi.org/10.1016/B978-0-12-815713-8.00014-0

hundreds of projects at medical device firms large and small. In 1994 during the summer prior to my final undergraduate year of Mechanical Engineering, I was hired as an intern at Johnson & Johnson (J&J) Interventional Systems (JJIS). By the end of the summer, I was one of the leading experts on stent design and engineering, primarily because the discipline did not really exist at the time. Of the three stent engineers at J&J, two of us were interns. A year later, JJIS launched one of the most commercially successful and clinically influential medical devices of all time. A small spinout of Ethicon, JJIS was formed as an internal incubator to explore the new field of interventional medicine. JJIS pursued at least a dozen ideas that were ahead of their time including left ventricular assist pumps and laser ablation catheters. Each failed, until one unlikely contender was left: something called a balloon-expandable stent. J&J licensed this technology from a group called Expandable Grafts Partnership. The principals of this endeavor were Julio Palmaz, an

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interventional radiologist who fashioned his first stent from materials purchased at Radio Shack; Richard Schatz, an interventional cardiologist; and Phil Romano, an entrepreneur known for wearing interesting socks and founding restaurant chains such as Fuddruckers and Macaroni Grill. Their invention was found to be an essential complement to “plain old balloon angioplasty” and unlocked a door to explosive growth in interventional cardiology. JJIS was the first to achieve significant commercial success with interventional stents and in the process created many of the engineering and process conventions and expectations that guide development of cardiovascular implants today. My journey with J&J included two billion-dollar products, the Palmaz Schatz Intracoronary stent, and Cypher drug-eluting stent. Both were remarkably successful firsts of their kind, holding monopoly positions for a short time; both saw their fortunes quickly erased when faced with competition in the marketplace.

an ecosystem of specialized contract development and manufacturing firms to fill their pipeline and fabricate their products. The last decade of my career has been serving this second constant. Most of it has followed the growth and increasing importance of a peculiar material called nitinol. Nitinol, an equiatomic compound of nickel and titanium, has the unique properties of shape memory and superelasticity. This flexibility allows it to transform from a large shape to a compact profile, returning to its original shape in vivo. Unlike a balloon-expandable stent, which could be crushed by external compression, bending, or kinking, a superelastic nitinol stent recovers to its original shape after such deformations. This was exactly the type of magic required to fuel development of ever-smaller devices and components.

RAPID CHANGE

It is said that the human body is 70% water by mass. Similarly, I suspect that medical device firms are at least 70% documentation. Look inside any medical device company and you will find it teeming with operating procedures, work instructions, forms, and reports. And lots of flowcharts, like that of Fig. 14.1. While these phases may have different names or boundaries, this general flow is common for all medical device projects. The investment of time, engineering, costs, and documentation escalates along this path. Discovery focuses on design exploration. This phase typically includes concept generation, prototype fabrication, testing, and simulation. At its essence the discovery stage is an iterative four-step process:

There are a few constants in this industry. The first is that the giants control the market, and they grow by acquiring the most promising new technologies, and by combining with each other. If you spend any time in the medical device industry, you are likely to experience mergers, acquisitions, spinouts, and start-ups. The landscape is ever changing. Upstarts chase emerging technologies, opportunists quickly follow those with the most promise (and reappropriate the scraps left by those who do not survive), and the giants assemble and grow diverse portfolios of proven technologies. By necessity the largest firms have deep expertise in sales, marketing, clinical, regulatory affairs, supply-chain and fulfillment logistics, and engineering. Note that manufacturing is not included in this list of necessities, which brings us to the second constant: The giants rely upon

THE PRODUCT DEVELOPMENT PROCESS

1. 2. 3. 4.

State a question. Engineer a solution. Evaluate feasibility. Refine the question, and repeat.

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THE DISCOVERY CYCLE

FIGURE 14.1

Typical phases of medical device product development.

The majority of this chapter expands upon these steps. In this phase, we explore a design space, seek limits of success and failure, and ruthlessly iterate to find the most promising design options. Usually, this phase is exempt from the rigors of design control. This is important because only a small fraction of the efforts occurring during discovery will carry forward to development. At this stage, we try to “fail fast,” learn from each experience, and move quickly to the next improvement. We also keep in mind “design for manufacturability” principles that may seem at odds with rapid iteration but will become more important later. This phase should conclude with a firm answer to the question of “what is the thing we should make?,” usually in the form of nominal design specification and performance requirements. Development typically focuses on process selection. How do we make the design that we have defined in the discovery phase? We have now exited the sandbox and entered the realm of design control: Methods and processes will now be formally documented, and revisions will be reviewed, approved, and recorded. Appropriate processes and manufacturing methods will be selected to meet design specifications, performance, and quality requirements. At the conclusion of this phase, nominal processes are identified and documented. Optimization focuses on process validation planning. What are the limits of the processes we will use to make the selected design? Methods are characterized; process limits are proposed and tested. Inspection methods are

selected and refined to measure critical specifications. Here, we confirm that design specifications can be reliably met under a range of expected material and process variations. At the conclusion of this phase the design and process specifications are locked, and validation protocols are finalized. Validation assures that the planned production process will reliably and reproducibly produce devices meeting all defined specifications. Typically, validation is performed at the site of production level manufacturing, by personnel trained according to process documentation. This phase may include tests of process limits and usually will also include high volume builds at nominal conditions. If the preceding phases were well engineered, the outcomes of validation should be well known in advance. This is not a good time for surprises! At the conclusion of this phase, development is complete. Production is the promised land. Manufacturing proceeds per established design specifications, process specifications, and release requirements, according to a defined forecast and demand plan. Processes are monitored, quality metrics are recorded, and improvements are identified, reviewed, and implemented to assure that quality and efficiency targets are achieved.

THE DISCOVERY CYCLE Most medical device designs never make it to clinical use (and some that do should not).

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The best and most successful projects require a mix of perspectives: • deep clinical insight into an unmet need, with an intuition for engineering problem solving and • strong applied engineering skills, with an intuition for clinical insights. These complementary characteristics are unusual to find in isolation, even less so in combination, and the reason why this book is so important. The best solutions to the most important problems are found near the boundaries of engineering and medicine, each discipline reaching across into the domain of the other. From an engineering vantage point, I have come to appreciate the value of clinical insight and a well-posed question. A good example was in the development of a neurovascular clot retriever. A customer had extensive clinical experience with a first-generation clot retriever, and consequently a deep understanding of the engineering limits of success and failure. Too soft a structure would fail to adequately engage the clot, while too strong a structure would slice through the clot and risk vascular damage. This sounds fine in words, but their understanding was deeper: They could measure values of stiffness and detect levels too high or low, which informed precise allowable limits of in-process radial force tests. Their understanding was deeper still, as they developed bench models and simulated clot materials that could be used to replicate clinical experience and verify performance of a proposed design. In the case of this project the customer lacked engineering experience with laser-cut nitinol components, so our engineering team formed the perfect complement. We quickly proposed and iterated designs, prototyped and tested components, and narrowed design options based on simulated clot testing. Ultimately, less than a year after papering a conference

room with rough sketches of design ideas, our device saved the first of many lives. Dozens of design improvements and variations followed, and the product line continues to be the market leader. The above project was an ideal example of the discovery cycle in practice. With clinical and engineering experience working together in the same room, inspiration was abundant. The essential design concepts were captured in embryonic form and quickly evolved to become a foundation of patents protecting the design. Tangible prototypes were quickly manufactured, tested, and refined. And the iterative discovery cycle that we began continues a decade later, with continuous incremental improvements implemented every year. It is not always this easy. We will address some common challenges in the next sections.

INSPIRATION Invention is surrounded by an abundance of mythology: brilliant minds, mad scientists, and wizards, isolated in a laboratory in a trancelike state until inspiration strikes like a bolt of lightning. Reality is rather more mundane. Invention just happens, often without noticing it. It is a natural by-product of curious humans in the setting of interesting problems. Like molecules colliding under the right conditions, inventions condense from the ether-like chemical compounds. They often evaporate or decay before detection, they may seem to be unwanted secondary products, or they may be catalysts that enable or accelerate subsequent reactions. Rarely are inventions the product of divine revelation or linear thinking, and rarely are they the product of a single mind. Even so, all ideas have to start somewhere, and compelling creative visions are rarely formed by committee. If you are a solo artist seeking inspiration, I direct your attention to the 2011 Kirby Ferguson video series

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GOALS AND CONSTRAINTS

“Everything Is a Remix,” easily located by search and also cited elsewhere (Ferguson, 2011; Markham, 2013). His pop-culture viewpoint on human creativity resonates with my experience in medical device innovation: Creativity is an incremental process, and new ideas are really just old ideas copied, transformed, and combined in new contexts. His short follow-up piece describes four steps to getting an idea: (1) create boundaries, (2) consume everything inside those boundaries, (3) digest the research, and (4) forget about it. A mind properly prepared by the hard work of the first three steps will work in the background and alert its owner when inspiration emerges. There are not many solo artists performing in the medical device industry. If you think you have conceived a fantastic new invention, that is great. Perhaps you are a wizard. But medical device development is a team sport, so you are going to need to find someone to challenge your thinking. As an engineer, find a medical expert in the field, or vice versa. Be prepared to be uncomfortable, and be open to the unpredictable chemistry that may change your mind or lead you in a new direction. Expect that someone else had your idea a long time ago, and perhaps they published or patented it. Do not be surprised to hear that your idea has been tried and failed, with a long list of reasons why it did not work. These experiences are essential landmarks along the unglamorous path through the process of inventing. A word on intellectual property (IP): Find a lawyer you can trust. While you are in solo inventor mode, write down everything you can, in as much detail as possible. Strongly consider filing a provisional patent application before disclosing your ideas to potential collaborators. It does not need to be fancy or expensive, but it buys you a year to formalize your idea into a formal patent application. It also creates an objective record documenting your ideas, which can enable free exchange with collaborators, and provides a way to later isolate

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their ideas from your own, and (more likely) shared ideas from individual ideas. Another caution: In the right setting, invention will happen naturally, whether or not it is intended. IP law is complicated. Employees are usually required to assign any IP to their employers, so it is easy to quickly entangle yourself in a complicated web of IP ownership, especially if collaborators contribute to your idea as part of their day jobs (or even on their own time). Nobody likes nondisclosure agreements and contracts, but the up-front friction they add to the process will save you untold pain later.

GOALS AND CONSTRAINTS As Ferguson’s “boundaries” are the first essential step in a creative project, “goals and constraints” are the first priority of the medical device design process. No solution accomplishes everything possible without restrictions, so this first step sets a vision and establishes the assumptions upon which the foundation of the design process is built. Setting goals and constraints should be among the first order of business in any collaborative project and should be a key outcome of a project kickoff meeting. As a prerequisite, everyone in the team will need to understand the essential details of the disease state, clinical setting, therapeutic alternatives, and commercial landscape. This often requires that the medical expert invest the necessary time to educate the engineering team, walking them through the current reality, including strengths, weaknesses, challenges, and opportunities. The team should be mindful to partition “conventional wisdom” separately from “novel insights” upon which this unique project will be built. If you are not hearing any novel insights, keep asking questions. Engineers and medical experts perceive and explain the world differently, so many questions should be asked

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and discussed at this stage. Assume nothing, and confirm everything. Make generous use of sketches, and take pictures of all of your scribbles. It is essential that everyone understands the setting at an atomic level. At the conclusion of this prerequisite exercise, whether they realize it or not, the team has already established the fundamental assumptions of the project. The first level of goals and constraints are easy to define. Goals simply define what the design must accomplish, and constraints define the limits within which the design must exist, including the anatomical boundary conditions discussed in detail throughout this book. Just call them out, write them on a whiteboard or sticky notes, keep going until everyone is bored, take a short break, then continue. Be specific. Translate everything into units everyone understands: 3 French 5 1 mm 5 0.0394 in. Be clear about outer diameter, inner diameter, and wall thickness measurements. The preceding two sentences may seem unnecessarily obvious but may be the most useful in the chapter. The next step is to prioritize the goals and constraints. This is difficult, but essential. First rank the goals. Which one single goal is the most important, i.e., the banner headline for this effort, the essential differentiating factor that makes the proposed solution superior to the alternatives? This is the goal that will be most averse to compromise, so choose it carefully. And be mindful that everything else on the list will be increasingly open to compromise. This is the nature of design: Everything is a trade-off, and prioritizing the factors to trade against each other is a high art. When you are done ranking the goals, repeat this troublesome process with the list of constraints. The team will resist, because the true priorities are likely unknown or debatable at this stage; forge ahead anyway. Like everything in the design process, setting goals and constraints is an iterative process. Especially in the early stages, you should be willing to limit your proof-of-concept

exercises to the most essential of goals, and you should be willing to violate many of the constraints. This is okay! You are making a first prototype, not a finished product. For example, the design project may require a percutaneous catheter delivered solution, but in the early stages, proving that an idea works can be separated from demonstrating that it can be small. Do not hesitate to substitute a garden hose for a guide catheter if that makes it easier for everyone to focus on the fundamental objective of the design. Be aware that throughout the experience, previously unconsidered objectives and constraints will be discovered and priorities questioned. Team members will have different perceptions, and everyone should keep account of their observations. The goals and constraints should be a living document. It should not be revised on a whim, in response to any one observation, or by any one team member. Rather, it should be revisited with a regular, agreed cadence, as a team, usually at the end of an iteration or the beginning of a new one. The revision history of this document should tell the story of the original hypothesis of the project, and of its evolution as the design progresses toward reality.

ENGINEERING Within the fences delineated by the first draft goals, constraints, and boundary conditions, it is time to become an architect. We now propose potential solutions that will fit our purpose and consider the palette of materials and techniques available to serve our needs. Imagination is confronted by reality, as we begin the process of reducing ideas to practice. We have entered the realm of engineering. At this stage, there is likely to be some healthy creative tension among the medical and engineering experts. The medical viewpoint is typically expansive, seeking to meet or

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exceed all of the goals, as the driving force of the profession is to cure and to heal. The engineering viewpoint is typically narrowing, seeking realistic solutions that can be practiced with confidence using known techniques, as the driving force of the profession is to transform goals into reality. The balance between these complementary impulses determines the degree of technical risk inherent in the project, as well as the potential magnitude of reward. A design that does not stray far from known forms, materials, and methods may have low technical risk but is also limited in its potential impact (an incremental “me-too” product). Conversely, a design with disruptive potential often faces potentially insurmountable odds of making it out of the laboratory. Projects exist at all points in this risk reward continuum, but their true position on this scale is not always understood by all parties. It is the engineer’s responsibility to keep the team well informed about the technical risks implicit in every design choice— what might be called, “knowing the center of the road.” Every project will venture “offroad” occasionally, but it is essential that such excursions are calculated and deliberate. Material selection is one of the most important first decisions the team will face. There are two major categories to consider for medical devices: polymers and metals. Polymers are essential to catheter-based intervention and are used to fabricate shafts, hubs, balloons, coatings, and all manner of tools and instruments. You should expect to become familiar with polyesters (“nylon,” “PEs”), polyurethanes, polytetrafluoroethylene (PTFE, commonly known as Teflon), polyimides, and silicones. Techniques such as extrusion, injection molding, thermal forming, lamination, dip coating, and solvent bonding are all common for medical products. Many catheter components are the composites of different polymers, or similar polymers with different mechanical properties (“durometer” is a

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common term describing the hardness of a polymer). Composites may include concentric layers of material through the thickness of a catheter-like component (e.g., a PTFE liner at the inner surface of a PE catheter), or a series of materials with varying properties along that length (e.g., a catheter with a soft tip and stiff proximal shaft). Polymer components also commonly include hydrophilic coatings to enhance lubricity in a wet environment, or silicone lubricant (commonly described as “MDX”) to reduce adverse frictional effects. Polymers may also be compounded with additives such as barium sulfate to improve radiopacity or enhance frictional characteristics. All of these things are centered in the “middle of the road” for medical component instruments and disposables, and should be well within the capabilities of experienced manufacturers. As the constituents of textile fibers or membranes, polymers are commonly used in graft materials of implantable vascular devices. Outside of this, polymers are somewhat less common as structural implantable materials, because they typically degrade over time. In some cases, such as biodegradable sutures or stents, this is precisely the intent. So, while polymer implants are not unheard of, this use case may require close scrutiny, with particular consideration for long-term effects of the byproducts of degradation. Metals are also used alone or in combination with polymers in medical tools and instruments. Catheter shafts are commonly reinforced with metallic braid or coil, and metallic needles, cannulas, and trocars have long been essential to modern surgery. Metals have especially important roles as implantable materials because of their unique combinations of strength and durability. Stainless steel, cobalt chromium alloys, and titanium are “conventional” metals used for medical implants. Early cardiovascular stents, such as the Palmaz Schatz intracoronary stent, were fabricated from 316L stainless steel.

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This is a low-carbon alloy composition, known for its favorable corrosion performance, and commonly used for suture needles. This alloy includes iron with 16% 18% chromium, 10% 14% nickel, 2% 3% molybdenum, 2% manganese, and traces of other elements. For balloon-expandable stent applications the stent is plastically deformed by the expanding balloon, such that local areas of metal experience permanent set, thus allowing the stent to hold its expanded shape after the balloon is deflated (less a small degree of recoil in diameter related to elastic recovery of the metal) (Fig. 14.2). Cobalt chromium alloys, such as L605, MP35N, or Elgiloy, are known for high strength, corrosion resistance, ductility, and fatigue performance. These materials include 35% 40% cobalt, 20% chromium, 10% 15% nickel, and may also include tungsten, molybdenum, or iron. These materials are common choices for modern balloon-expandable stents and similar cardiovascular implants, as they can be engineered to have superior strength, durability, and radiopacity characteristics relative to stainless steel-based designs of a comparable form. Titanium is commonly used for orthopedic implants for its high strength, low mass, and ideal surface characteristics. Nitinol is an “unconventional” material with unusual properties. An equiatomic intermetallic compound of nickel and titanium, nitinol can

exhibit the unique properties of shape memory and superelasticity. Shape memory refers to the ability of the material to deform at a low temperature, then recover its original shape when exposed to a high temperature. Superelasticity refers to the ability of the material to deform to an unusual degree (6% 8% strain or more) and recover to its original shape, all while at a high temperature (the transition temperature is typically set less than body temperature for medical components). Both manifestations of the same underlying physics, these phenomena arise from a phase transition in the material. Much like ordinary water, nitinol can exist in three phases, controlled by temperature and stress (which is mathematically equivalent to pressure). Martensite is the low-temperature (low entropy) phase, akin to ice. Austenite is the high-temperature (high entropy) phase, akin to steam. R-phase is an inconvenient intermediate phase, like liquid water, which we will ignore for now (Duerig et al., 2017; Shamimi et al., 2018). Fig. 14.3 depicts the stress strain response of loading and unloading nitinol. In the shape memory effect the material starts at a low temperature in the martensite phase. The crystal structure of martensitic nitinol is unique because the layers of atoms called “twins” can unfold in response to applied stresses, causing shape changes without

FIGURE 14.2 Balloon-expanded stent expansion. The balloon unfolds and expands as it is pressurized, causing plastic deformation in the stent as it increases in diameter. Conventional stents often foreshorten in length as their diameter expands. When the balloon is deflated, the diameter of the stent will recoil slightly as the elastic component of deformation is recovered, and the recoiling artery applies pressure on the stent as well.

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FIGURE 14.3 Stress strain response of superelastic nitinol. Starting at 1, the austenite phase responds with the linear elastic response of a conventional material. At 2 the austenite begins to transform to martensite. The shape of the material changes under a constant stress, the loading plateau stress or UPS from 2 to 3, as the transformation proceeds through the volume of material. At point 3 the material is substantially transformed to the martensite phase, and the material again responds in a linear elastic manner from 3 to 4. At point 4, which may be approximately 8% strain, as the stress is released, the material recovers to point 5. From point 5 to 6 the martensite reverts to austenite, and the material returns to its original shape as the stress is completely released at point 1. The path from 5 to 6 is known as the unloading plateau, or LPS. If stress continues to increase from point 4, nonrecoverable plastic damage begins to accumulate in the material at point 7, as atomic bonds break. At point 8 the UTS is reached as the material ruptures. LPS, Lower plateau stress; UPS, upper plateau stress; UTS, ultimate tensile strength.

breaking atomic bonds. When the temperature is elevated above the transition temperature, the crystal structure reverts to the austenite phase, and the twins disappear, causing the component to recover its original shape. The superelastic effect is much the same, but rather than cooling to produce martensite, one relies on the applied stress itself to transform the austenite (much like one can pressurize steam to form water). Of course, once martensite is formed, twins can again be folded, and the shape can again be changed without breaking bonds. When the applied stress is removed, austenite is again the stable phase (just as water reverts to steam when pressure is removed), and the original shape is restored. From a macroscopic perspective, the metal appears almost rubber like, able to spring back

to its original shape after deformations as great as 10%. Its ability to fully recover from significant shape changes has enabled many modern minimally invasive and transcatheter interventions, allowing large devices to be delivered through small access points. A properly treated nitinol component develops a thin but durable layer of titanium dioxide at its surface, similar to that of a pure titanium implant. Given the strong intermetallic bond between nickel and titanium atoms, despite containing 50% nickel, a properly processed nitinol implant can release less nickel to the bloodstream than a stainless steel or cobalt chromium alloy containing a much lower percentage of nickel. Nitinol also has an unmatched ability to withstand static and cyclic deformation, so it is

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commonly used in anatomical settings that may be subject to external compression, bending, torsion, pulsing, or myriad of other loads as discussed in other chapters of this book. The durability of nitinol is not without limits; however, these limits will be explored in some detail in the next section.

FABRICATION Manufacturing is the practice of transforming materials from one form to another. The array of medical manufacturing technologies is similar to those of other industries. Plastic components are molded, extruded, and bonded using thermal methods or a variety of adhesives. Metals are forged, stamped, photochemically etched, machined, laser cut, etc. Every process has its own range of suitability, advantages, and limitations. This section provides an overview of fabrication methods that are “in the middle of the road” for manufacturing medical components. Many cardiovascular implants have a cylindrical shape to match that of the lumen in which they are placed. Therefore stents and valve frames are usually fabricated from tubing, from which they are intricately cut using laser micromachining techniques. Within this domain, there are a variety of laser types, with a variety of optical systems, energy levels, and frequencies. The selection of laser system will influence the tolerance and precision available in the final component, as well as the production speed and ultimately the manufacturing cost. It is likely that multiple options are possible, so it is essential that the designer and manufacturer have a common understanding of tolerance requirements, cost targets, and technical capabilities offered by each system. While laser micromachining is common for medical devices, it is not the only option. For metal components that are flat, electrodischarge machining is often suitable. In this

method an electrically charged wire carves paths through a component, and often several components can be stacked together to cut multiples at a time. For complex threedimensional (3D) shapes, computer numerically controlled machining may be necessary. Tooling and setup can be quite costly for such techniques, which can make it impractical for short runs of prototypes. An increasingly common alternative uses additive manufacturing to fuse powdered metal into complex shapes using an automated laser scanner. Also known as 3D printing, these techniques can offer shapes and surface topologies that cannot be easily achieved using conventional machining. Additive manufactured components also have tradeoffs, as the properties of fused metal powder may be unfavorably different from those of conventional machined metal.

DESIGN CONTROL AND ENGINEERING SPECIFICATIONS Fig. 14.4 is an illustration of the design control process that is required for regulated medical device development, as expected by FDA and similar agencies worldwide (Food and Drug Administration Center for Devices and Radiological Health, 1997). Here we consider an example medical component, a vascular stent, and how each design control element relates to each other. • User needs define the intended clinical indication for the component. In this example an arterial vascular stent intended to treat de novo peripheral arterial disease of the iliac artery. We specify an expected range of vessel diameters and lengths, and a catheter profile through which the stent must be delivered. We also define the anatomical boundary conditions that the stent will experience, as discussed in detail elsewhere in this book. For example, a range

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FIGURE 14.4 The medical device design control waterfall diagram. This diagram is recreated from the 1997 FDA Design Control Guidance for Medical Device Manufacturers and was originally created by Medical Devices Bureau, Health Canada.

of pulsatile pressures, the expected stiffness of healthy and diseased vessel segments, susceptibility of external compression, a range of static bends the stent may need to accommodate, and any dynamic changes to the vessel and surrounding anatomy that may be related to motion of the hip or leg. We also consider the acute performance requirements, such as flexibility to reach the site of implantation, and outward strength to expand a constricted lumen, tolerate balloon inflation, and resist recoil. Finally, we consider long-term performance requirements, such as biocompatibility and structural durability for an appropriate duration (commonly 10 years for vascular stents). • Design inputs translate user needs into objective and measurable engineering terms. For example, we may define an acceptable range of radial resistive force and/ or chronic outward force, which define the force versus diameter response of a superelastic stent as it is compressed and

expanded. Similar ranges may be set for pinching or crushing loads, axial stiffness, or bending stiffness. Here we may also define the crimped diameter of the stent, considering allowances related to the design of the catheter through which it must be delivered, as well as the expanded diameter of the stent, considering the degree of oversizing we wish to allow or require relative to the expected vessel diameters. Design inputs such as these must be defined to address every aspect of the user needs described above. • In the design process, we create tangible (or virtual) artifacts that attempt to meet all of the design inputs as described above. This usually involves iteration, prototyping, simulation, and testing. It also often requires some negotiation, as testing may reveal gaps in design inputs, or raise questions about user needs. Tests are developed, revised, and repeated, and results are scored to identify the most promising design candidates.

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• Design outputs are objectively measurable characteristics of the final design itself, such as raw material requirements, feature dimensions, tolerances, and surface finish requirements. These characteristics are commonly measured and certified by the manufacturer of the component, for every batch fabricated. • Design verification refers to testing that objectively proves components fabricated according to the defined design outputs (i.e., components meeting the specification) meet all of the design input requirements defined above. In short, does the component meet its functional requirements? In our example, this might include radial force testing to demonstrate that stents with high, low, and nominal feature tolerances successfully meet radial resistive force and chronic outward force requirements. Design verification may also include physical fatigue testing, corrosion testing, and other forms of biocompatibility testing. Design verification is usually the responsibility of the designer (not necessarily the manufacturer). Definitive design verification testing is typically done once for a given set of user needs. • Design validation in this context refers to clinical testing of finished medical devices, previously verified to be within spec, and having previously passed design verification. If there were any critical omissions or flaws in our assumptions about user needs or design inputs, we will discover them here. This is a bad time for surprises. It is said that design verification assures that we made the component correctly, while design validation tests if we made the correct component.

The essential design output document, the Engineering Specification, is the product of everything that has led the designer to the final design. It is the master recipe from which all future articles will be fabricated, the engineering equivalent of DNA. Usually this is a drawing depicting the final form of the component, often including several views illustrating all of the important aspects of the component, and dimensions specifying targets and ranges for specific features such as length, width, or thickness. The drawing usually includes annotations to clarify certain features, or designate some features with elevated or reduced criticality. In addition, there may be annotations and a list of notes to state other important details, such as the material from which the component is fabricated, surface finishing requirements, etc. The drawing may also reference other documents, such as applicable standards, inspection plans, or handling requirements. From a component manufacturer’s perspective, every aspect of user needs and design inputs, including every consideration of clinical boundary conditions discussed throughout this book, is represented by the dimensions and notations on the engineering specification. A manufacturer will make exactly what is specified and inspect exactly what is required, and certify accordingly. As the owner of the engineering specification, it is the designer’s responsibility to assure that there is a meaningful relationship between every dimension, tolerance, and notation on the drawing and a corresponding design input. Not all dimensions have equal importance; some may be included for reference only, while others may be critical to the function of the device. For example, the radial outward force of a neurovascular clot retriever may be an essential design input, required to

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be within a narrow band for proper function. Through simulation and testing, the designer finds that the radial force is most strongly influenced by a specific strut width feature and finds the acceptable limits of this feature width to ensure that radial force requirements are met. The tolerance of this feature is defined accordingly, designated a critical dimension, and designated for a rigorous level of inspection. Every dimension and notation on the engineering drawing has an influence on its cost and quality, and should therefore be thoroughly considered. In the previous clot retriever example, if every dimension were to be held to a tight tolerance and inspected at the highest level, the component would not be economically viable. If, however, the critical strut width and related radial force were not controlled within strict limits, the component would not be clinically viable. A balance must be struck. While an engineering specification may begin as a napkin sketch, it should end as a work of art and science. It will likely go through many revisions, the product of design and manufacturing collaboration, and the distillation of everything we know about translating clinical disease states and boundary conditions into engineered therapies. A word of caution: It is not uncommon for a manufacturer to have a batch of components returned because they “don’t function like the last batch did,” despite meeting all requirements of the specification. This usually means that there is something important about the performance of the device that is not captured by the specification, is simply not understood. In such cases, more work is required to isolate and control the source of variability, or make the design less sensitive to variables that cannot be eliminated. The specification often evolves during the life of a component to incorporate new

information gathered during the manufacturing and commercial life cycle of the product.

SIMULATION Computational simulation translates the physics of the subject component and its environment from the filthy world of atoms and cells to the orderly world of bits. With computational power constantly increasing in availability and decreasing in cost, “in silico” experimentation seems to hold infinite promise to accelerate development and reduce the need for burdensome physical testing, animal testing, and human clinical trials. But here is a secret: Simulation (like physical testing) can also be messy and imprecise. In its simplest form, a computational simulation is simply a function that transforms factors into responses. The response may be a prediction of structural integrity or durability, corresponding to factors such as design selections and loading conditions. In the cases of bridges, automobiles, and aircraft, loading conditions are known with a reasonable degree of confidence. For medical devices, this is not so, and unraveling the complexity of such boundary conditions is the primary motivation for this book. Anatomical conditions vary significantly within and among individuals, and are strongly influenced by age, size, and disease state progression. And dynamics related to the cardiac, gait, respiratory, or other movement cycles can be vexingly difficult to reproduce outside of actual human subjects. Here are two broad categories of computer models that may be useful for simulation of in vivo loading conditions: • Screening models are intended to isolate the influence of specific design choices in the context of selected loading conditions. This

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type of modeling is commonly used to guide design iteration and is especially useful for understanding the sensitivity of outcomes to design inputs. As such, the absolute numerical outcomes are less important than relative difference between models. Screening studies can help a designer narrow a field of options to the most promising candidates. Screening is not a substitute for physical testing but can accelerate development by focusing testing resources on designs that are most likely to succeed. • Replicant models are intended to incorporate, to the extent possible, all of the known variables in the design and environment, and predict performance within a known range of loading conditions. This is a much higher bar, as it requires the analyst to know, understand, and consider all potential sources of variability in the component and the environment, judge which factors to incorporate and how, and build a model that can represent these in isolation, as well as in combination. FDA offers guidance on their expectations for such simulations (Morrison, 2016). No computational model can (or should) incorporate every possible variable; therefore every model is an abstraction of reality. The appropriate degree and implementation of this abstraction requires considerable judgment. Abstraction is the essence of translating messy atoms into orderly bits, and it is also a likely point of failure in computational modeling. While the math is complicated, and programming is intricate, these are not the usual sources of false or misleading predictions. Rather, errors are more likely in the category of omission: An anatomical boundary condition that was unknown or believed insignificant proves in reality to be dominant, or a material assumed to be consistent in composition and properties proves to be nonhomogeneous.

Screening models are useful for design iteration precisely because they intentionally dismiss all variables except those that can be readily controlled and measured. Such models rely upon a high degree of abstraction, trading simplicity for accuracy, seeking to find a viable solution quickly. When considering screening models, it is helpful to first distill the engineering system to its essence. If at all possible, try to find a closed-form mathematical model to represent the system; while it may be far from complete or accurate, such models can provide important intuition about the behavior of the system. For example, a laser-cut cardiovascular stent may seem at first glance to be an impossibly intricate and complex structure, unsuitable for any closed-form modeling. However, on closer inspection, a stent can be represented as an array of interconnected beams. The behavior of beams can be represented by relatively simple beam equations. And these equations can be rearranged into terms familiar to stent design (Fig. 14.5), both in terms of strain and force versus deflection, or stiffness. Considering stent radial stiffness, we can now easily appreciate the single-order power of material elastic modulus and wall thickness, the third-order power of strut width, and the inverse third-order power of strut length. If we are interested in strain, we can see that strut width has a first-order influence, and strut length an inverse second power influence. For axial buckling performance, we can consider the Euler equation for critical load. A simple spreadsheet or computer program can be used to quickly map a vast design space and understand the interplay between design inputs and outputs. Open Stent Design is an example of such a tool set (Bonsignore, 2012).

FINITE ELEMENT ANALYSIS Having filled the back-of-your-proverbialenvelope with beam equations or similar

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FIGURE 14.5

Linear approximation of reaction force F and strain ε in a stent with elastic modulus E, wall thickness t, strut width w, and length L, deflected by an amount δ.

closed-form solutions, you will soon find yourself seeking more sophisticated methods. We now introduce finite element analysis (FEA), a computational technique that discretizes a large domain into many tiny elements, each bounded by nodes defining locations in space, and containing one or more integration points at which field equations are calculated. In a structural model, forces and displacements are calculated at the location of each integration point, balancing internal forces with those resulting from interactions with its neighbors, and any external boundary conditions, such as applied forces or displacements. There are many academic and open source options for FEA, but medical device applications usually rely on commercially developed and supported packages such as ABAQUS (Dassault Systemes SIMULIA, Providence, Rhode Island) or ANSYS (ANSYS Inc., Canonsburg, Pennsylvania). FEA is a specialty of its own, and there are some common terms related to this technique.

• Constitutive model: At the core of a computational simulation the constitutive model is a mathematical representation of how a material responds to applied loading. In the simplest terms, this is the relationship between stress (load) and strain (deformation) in each dimension of interest. The constitutive model may also consider the effects of temperature, damage (plasticity), phase change, hydrostatic pressure, or coupling to electrical or magnetic fields, depending on the physics that are relevant to the simulation. • Dimensionality: While actual medical components exist in 3D space like the rest of us, the analyst may simplify the model to a 2D representation if the primary influences are limited to a rectangular or cylindrical plane (stents, balloons, grafts, or vessels can qualify), or a 1D representation if the structure can be represented by points and lines (wires, for example). Lower

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dimensionality models can leverage specialized elements that can simplify the simulation, making it easier to iterate quickly. Symmetry: Many medical components are symmetrical about one or more planes. If this is true, the structural response of the structure in its loading environment may be repeated within each symmetrical segment, and the analyst may elect to model this subset instead of the full geometry. Mesh: The geometry of the system is usually created using some computer-aided design software to describe its size, shape, and position. The analyst will partition the geometry into regularly shaped segments, and mesh the partitioned geometry into an array of elements. Elements: A discrete mathematical unit, or element, represents a specific volume of material, and the physics of interest within. Elements are designed for 1D, 2D, or 3D dimensionality and can have a variety of shapes optimized for different topologies. For example, 2D elements may be triangle shaped “tris” or rectangular “quads,” and 3D elements may be tetrahedral shaped “tets” or hexahedral shaped “bricks.” Tris and tets can fill an arbitrary planar topology, and quads and bricks can fill an arbitrary volumetric topology. Integration points: Field equations are solved at specific locations in space within each element, called integration points. Elements have at least one integration point (often described as “reduced integration”) and may have multiple integration points. Nodes: Locations in space defining the bounds of each element. Nodes are located at each corner of first-order elements and may also be located along the edges of higher order elements. Boundary conditions: The effects of the outside world on the model are described as boundary conditions. In a structural simulation, boundary conditions are usually

defined in terms of specified displacements, loads, or interactions at relevant nodes in the model. While the universe exists in a reality that spans many orders of magnitude, computational models are typically optimized to operate at a particular length scale. A macro-scale model considers physics on the order of centimeters to meters and is primarily interested in bulk physical properties of material and structures. Mesoscale models are optimal at the scale of millimeters, a common size of engineered features, notches, or cracks in industrial engineering. A microscale model considers a scale of microns, the typical length of voids, inclusions, and grain boundaries in polycrystalline material. Nanoscale models consider phenomena at the scale of individual atoms. Multiscale models attempt to combine these, by coupling the outputs of lower levels to higher levels (Panchal et al., 2013). By this description, cardiovascular medical implants typically operate at a microscale. However, the tools and methods that we use for medical device simulation were developed to operate at the meso- to macroscales of industrial machinery, automobiles, and aircraft. In devices like stents and heart valves, nominal feature sizes are often as small as hundreds of microns. This can be similar in scale to the grain size of the material, and close to the single digit to tens of microns scale of crack initiation features, or material inhomogeneities such as voids or inclusions. Multiscale modeling is an active area of research (Kelly et al., 2016; Moore et al., 2016), but these techniques are not yet in common practice. In practice, our current material characterization methods and computational techniques operate at the meso level, so we must ignore the microscale characteristics of our micron-sized devices. A computational simulation is prepared to answer one or more questions of interest for a specific context of use. These terms are of

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particular note in the field of model verification, validation, and uncertainty quantification (VVUQ). This is an area of increasing importance to medical device simulation, as rigorous validation is essential to unlock the full potential of simulation to augment and possibly replace bench testing, or even perhaps clinical testing. VVUQ proposes a framework for credibility assessment of a computational model, by carefully describing and characterizing modeling assumptions and sources of variability or uncertainty (Pathmanathan et al., 2017).

FEASIBILITY SCREENING A screening FEA model may focus on a very simple question of interest, such as “is this a feasible design?,” or more specific questions such as “can this design expand to 10 mm in diameter, and be constrained to 2 mm in diameter, within the limits of superelasticity?” In a screening model the context of use is limited to finding feasible solutions in a design space, and predicting relative performance of one solution compared with others, in measures such as stress or strain, and stiffness. In this context, verification and validation efforts are usually quite limited, as the design and methods are far from finalized. Reference models will be leveraged, generic material properties may be used, and validation by comparison with physical testing may be neglected entirely. This is the least ambitious category of simulation, wherein rigor is traded for speed and simplicity. The modest level of credibility offered by such a simulation relies substantially on the judgment of the analyst. That said, an experienced analyst can bring extraordinary value to a project in this stage, rapidly assessing design options, and focusing efforts on the most promising solutions. Once feasibility is understood, related questions of interest may be posed to understand the sensitivity of design outputs to design

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inputs. For example, we might want to understand the relationship between axial drag force on a stent graft and the strain amplitude for one or more anchor barb designs. In this example the context of use may be focused on finding the most robust design given the range of expected loading conditions. Such a model might include steps such as: 1. Search literature for expected ranges of axial drag force on stent grafts of a similar design (Alberto Figueroa et al., 2009; Liffman et al., 2001). 2. Adapt the force ranges for the specific design of interest. For example, if the design has a total of 10 barbs, we might assume that the total axial drag force is carried by all barbs equally. A more conservative assumption may be that some of the barbs fail to engage, and the entire load must be carried by the remaining barbs. The specific assumptions will require clinical and engineering judgment. (In this example, we neglect any loadcarrying contribution from frictional effects of the stent graft engaging the vessel wall.) 3. Construct a model of the barb design of interest. This model may include one influence of preceding loading steps, such as constraining to the diameter of the delivery system, and deploying to the diameter of the vessel of interest. The model may include only the barb feature, or may include the barb and adjacent structures. More engineering judgment is deployed here, as we apply levels of abstraction to isolate the feature of interest. Fig. 14.6A illustrates parametric variation of barb length. 4. Select rigid body constraints. The structure must be held in space in some way, because without such constraints limiting rigid body motion, the model will respond to external loads by simply flying away. The simplest approach may be to

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FIGURE 14.6 (A) Parametric variation of barb length for a sample component, in its constrained configuration. (B) Systolic (blue) and diastolic (green) configuration of the expanded component exposed to different combinations of boundary conditions.

completely fix the barb at its root, and similarly fix the adjacent features, isolating the barb itself as the only deformable structure in the model. While easy, this may be an oversimplification of the true system. The critical strains are likely at or near the root of the barb, so the adjacent features may play an important role. Furthermore, the stent graft may be pulsing in diameter in some way that is synchronized with the rise and fall of axial drag force. Therefore it may be impossible to isolate the influence of cyclic axial drag force from that of cyclic pulsatility. As a consequence, we may need to return to step 3 and consider the extent of the selected model. In this example, it may be important to include features adjacent to the barb, and perhaps the entire component instead of only the barb itself. Rigid body constraints should be applied far away from the region of interest, to the extent possible.

5. Select loading boundary conditions. Here, we simply apply the loads selected in step 2. But where shall these loads be applied? This depends on how the barb engages with the surrounding tissue, and to some degree, it also depends on the characteristics of the tissue itself. We shall consider tissue modeling out of scope for this exercise, so another abstraction is required. We may choose to uniformly distribute the load across the surface area of the barb that we expect to be in contact with tissue. This requires us to define precisely what surfaces are involved, which requires assumptions on barb penetration and position, as well as the effective thickness of the tissue. Applying some engineering judgment, we can simplify the effective position to a single point along the length of the barb. At the extremes the effective load is concentrated at the base or the tip; in reality, it is somewhere in between. For simplicity, we

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may elect to apply the concentrated load at the midpoint of the barb length; in doing so, we have introduced another significant dose of engineering judgment into our model. 6. Apply loads and measure responses. In our example the simulation includes a minimum of two steps: one representing the minimum magnitude of axial drag force, and the other the maximum magnitude. For the response, we compare the strain fields between these two steps. But what exactly shall we compare? It might be tempting to simply subtract the maximum value of maximum principle strain observed in one step from the other, and divide the difference by two to calculate the amplitude. However, the location of peak strain may be different between these steps. Furthermore, strain is a 3D field, and the direction of the maximum principle strain may be different between steps. Yet again, more judgment is necessary to appropriately measure the response variable of interest. 7. Repeat for a set of related designs. For example, we might repeat this simulation for barbs with a range of feature dimensions, such as length, width, thickness, and root radius, while holding the axial drag force assumptions constant throughout. This provides an assessment of sensitivity of these design features to the response variable, in this case strain amplitude. Alternatively, we might vary the magnitude, direction vector, and position of the axial drag force, and thereby understand how strain amplitude relates to variation in this applied load. Fig. 14.6B represents two similar models, each with different factor values, illustrating the difference in structural response to systolic and diastolic loading. 8. Automate simulations to explore a design space of interest and fit a model to the

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results. Once the most relevant inputs and outputs are understood, the simulation may be repeated many times using a parameterized template. Using computational probabilistic methods, as described by Gupta, Kulkarni, and others (Dey et al., 2015; Gupta et al., 2012; Kulkarni et al., 2013), simulations can be repeated with inputs (factors) defined as parameters. These factors can be selected within specified limits for each repetition, thus establishing the relationship to the outputs (responses) of interest within a defined design space. Depending on the number of factors under consideration, dozens or hundreds of simulations may be necessary to adequately cover the entire design space and capture the influence of potential interactions between factors. This approach is described as a virtual designof-experiment and may implement methods such as Latin hypercube sampling to efficiently randomize values for each factor, while also ensuring that factors are not correlated with each other. 9. With a sufficient number of simulations completed, statistical methods can be used to assess the correlations between factors and responses, and their relative importance alone and in combination. This is described as a sensitivity analysis and provides important insights about the relative influence of each design and loading factor, allowing the design team to more precisely quantify the tradeoffs associated with each design decision. It also can give insights into the safe clinical limits for a given design. 10. Furthermore, the simulation results data set can be used to fit a multivariate model relating responses to factors. Such a mathematical model can be queried to predict the response for any selection of factors with the bounds of the original data set. Using methods such as Monte Carlo

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simulation, design factors can be varied according to expected manufacturing tolerances, and loading factors can be varied according to expected clinical conditions. In mere seconds, this process can be repeated hundreds or thousands of times, representing the expected variations occurring during the clinical use or the worldwide commercial lifetime of a product. With this method the design team can estimate the ranges of the responses corresponding to a meaningful population size (Giunta et al., 2003).

PROTOTYPE AND TEST Computational simulations are increasingly powerful, and when executed properly can provide important insights into performance characteristics of potential designs. It can be tempting to invest in many iterations of simulations, exploring and optimizing design options. While this may be a valid approach for mature products and applications, for new designs, there is no substitute for creating tangible prototypes. There is no universal definition for what defines a “prototype,” but I find it helpful to think of prototypes as tangible artifacts that are used to discover what the ultimate design needs to be. In this sense, prototypes may not look like the final design and may not act like the final design in all respects. Rather, prototypes may focus on one or more performance features of interest and help the designer to test specific assumptions. For example, a stent prototype may be used to test radial stiffness and scaffolding performance, but intentionally ignore crimped profile and flexibility requirements, as these can be isolated and optimized separately in later iterations. What specifications are required for prototypes? As few as possible. I often recommend “shiny and not broken” and am often willing

to negotiate on both. Simply handling a first article prototype, in its most raw form, provides a wealth of qualitative information that can be impossible to anticipate prior to fabrication. Especially in the hands of an experienced engineer or physician, a first article prototype can reveal intuitions about such qualities as stiffness, shape, form, or sharpness. Prototypes are usually produced on a “best effort” basis, meaning that the manufacturer will target desired characteristics and feature dimensions but will not guarantee that all will be met. In any case, it is a good practice to measure the features and characteristics that are expected to be important, so there is a record of exactly what was prototyped. This also provides some insights into process capabilities, and information about how to specify requirements in future prototypes. After a prototype has been successfully fabricated, the engineer and manufacturer may agree on some “a la carte” inspection or testing requirements. For the sake of speed, cost, and expediency, it is good to avoid overburdening the prototype process with unnecessary inspections. Early prototypes may be used once and quickly dismissed after qualitative evaluations, so extensive inspection would be a waste. It is advisable to keep an organized archive of prototypes, so they will be available for more detailed interrogation later, if necessary. As prototypes mature, so too should inspection and testing expectations. For many categories of medical devices, there are well-established expectations and conventions for performance testing. These typically take the form of ASTM or ISO standards and are often listed in relevant guidance documents (FDA, 2010). You should be aware of such conventions and identify a shorter list of tests that are especially relevant to your specific design. For novel devices, it is quite likely that the most important tests will be those for which there is no standard, or the standard is

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ambiguous. Especially in the case of cardiovascular implants, the most significant design and performance challenges can be related to the experience of delivery and deployment. These are subtle and qualitative characteristics, and it can be quite difficult to accurately recreate the experience of real human anatomy in a laboratory benchtop setting. In my experience the design and development of novel test methods is inseparable from the design and development of novel medical devices. The device can only be as good as the test by which it is evaluated, and this becomes a strong motivation to deploy sophisticated test methods as early as possible. Acute animal studies are very insightful in this regard. The team should also consider befriending a local butcher. Ex vivo hearts, blood vessels, and other tissues are readily available, and while messy and imperfect, they can provide insights that could not be revealed in the setting of glass and plastic models common in the lab. Every preclinical experience, whether in vivo or ex vivo, is likely to reveal some limitation or flawed assumption of prior bench tests or simulations. Try to recognize these setbacks as gifts that should inform improvements in the next iteration of tests and models. When the process is working as intended, device and test will iterate and evolve in tandem, hopefully leading to a first human clinical experience with few surprises.

CONCLUSION Medical device development does not follow a linear path, despite the best efforts of project managers to plan otherwise. Every iteration offers some insights to incorporate into the next, and some iterations move progress in the wrong direction. Sometimes it seems that the only way to reach the end is to go in circles, so it is essential to keep a sharp focus on certain points along the path. These points

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coincide with step functions on the effort versus knowledge chart that a design progress traces throughout its evolution. • Eureka: The idea emerges. A napkin sketch is created, and visions of possibilities fill the mind of its creator. This is followed by documentation, research, and quite possibly a crushing blow of reality that kills the idea before more calories are expended. • Simulation: A first draft computational simulation can often be created quite easily, and while the inputs may be best guesses, the output can be stunning and insightful. It also may kill the idea, but if so, better now than later. • Prototype: Depending on the design, simulation may not be necessary, or simply making a prototype may be easier and cheaper. It cannot be emphasized enough how powerful it is to hold a tangible object in one’s hand. Just handling a first-of-a-kind prototype often offers the intuition to know if an idea is feasible. Or if it should be killed. • In vivo animal study: Many calories will be burned before reaching this milestone. Several design iterations, assemblies, and bench tests, and many days and dollars. None of this will be as real as the first in vivo animal study. It will probably go badly, but much will be learned. • First-in-human: Before reaching this point, reams of documentation will have been prepared, reviewed, and revised. The design will have likely evolved through several preclinical generations. This is about as high stakes a moment as a medical device designer can experience. There have been many more first-in-human studies in the world than commercial devices, so guess what: The first-in-human experience may also be the last. While there are many subsequent landmarks and some important steps in between, these are the big ones from a designer’s point of

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view. And fortunately, the first three can happen quickly and with relatively little investment. The important lesson here, as elsewhere: The key to success is to fail fast, and fail often. Cycle through the first three steps, and be merciless about killing the dubious ideas at these early stages. It gets much more painful later, and there will always be more ideas.

References Bonsignore, C., 2012. Open Stent Design, Figshare. doi:10.6084/m9.figshare.95614.v3. Dey, A., Kulkarni, S., Mahadevan, S., Tryon, R.G., Krishnan, G., 2015. Uncertainty management in computational simulations of medical devices. J. Med. Device 9, 30954. Duerig, T.W., Pelton, A.R., Bhattacharya, K., 2017. The measurement and interpretation of transformation temperatures in nitinol. Shape Mem. Superelasticity 3, 485 498. Available from: https://doi.org/10.1007/s40830-0170133-0. FDA, 2010. Guidance for Industry and FDA Staff NonClinical Engineering Tests and Recommended Labeling for Intravascular Stents and Associated Delivery Systems. U.S. Food and Drug Administration, Center for Devices and Radiological Health, Silver Spring, MD. Ferguson, K., 2011 Everything Is a Remix. Figueroa, C.A., Taylor, C.A., Yeh, V., Chiou, A.J., Zarins, C. K., 2009. Effect of curvature on displacement forces acting on aortic endografts: a 3-dimensional computational analysis. J. Endovasc. Ther. 16, 284 294. Available from: https://doi.org/10.1583/08-2667.1. Food and Drug Administration Center for Devices and Radiological Health, 1997. Design control guidance for medical device manufacturers. In: FDA 21 CFR 82030 Sub-Clause 44 ISO 9001, p. 53. Giunta, A., Wojtkiewicz, S., Eldred, M., 2003. Overview of modern design of experiments methods for computational simulations (invited). In: 41st Aerospace Sciences Meeting and Exhibit. doi:10.2514/6.2003-649. Gupta, A., Koch, P., Liu (Cheryl), X., 2012. Evaluate medical device design robustness by combining statistical and probabilistic tools with finite element analysis. J. Med. Device 6, 017590. Available from: https://doi. org/10.1115/1.4026768.

Kelly, A., Stebner, A.P., Bhattacharya, K., 2016. A micromechanics-inspired constitutive model for shapememory alloys that accounts for initiation and saturation of phase transformation. J. Mech. Phys. Solids. 1 28. Available from: https://doi.org/10.1016/j. jmps.2016.02.007. Kulkarni, S., Krishnan, G., Clerc, C., Merdan, K., Tryon, R., 2013. Using probabilistic computational durability modeling and simulation to create a virtual design of experiments based on limited laboratory tests. J. Med. Device 7, 40911 40918. Liffman, K., Lawrence-Brown, M.M.D., Semmens, J.B., Bui, A., Rudman, M., Hartley, D.E., 2001. Analytical modeling and numerical simulation of forces in an endoluminal graft. J. Endovasc. Ther. 8, 358 371. Available from: https://doi.org/10.1177/152660280100800405. Markham, A., 2013. Remix cultures, remix methods: reframing qualitative inquiry for social media contexts. In: Denzin, N.K., Giardina, M.D. (Eds.), Global Dimensions of Qualitative Inquiry, 1st ed., Routledge, pp. 63 81. Moore, J.A., Frankel, D., Prasannavenkatesan, R., Domel, A.G., Olson, G.B., Kam, W., 2016. A crystal plasticitybased study of the relationship between microstructure and ultra-high-cycle fatigue life in nickel titanium alloys. Int. J. Fatigue 91, 183 194. Available from: https://doi.org/10.1016/j.ijfatigue.2016.06.006. Morrison, T.M., 2016. Reporting of Computational Modeling Studies in Medical Device Submissions— Guidance for Industry and Food and Drug Administration Staff. US Food and Drug Administration, Center for Devices and Radiological Health, pp. 1 48. Available from: https://www.fda. gov/downloads/MedicalDevices/DeviceRegulationand Guidance/GuidanceDocuments/UCM381813.pdf. Panchal, J.H., Kalidindi, S.R., McDowell, D.L., 2013. Key computational modeling issues in integrated computational materials engineering. Comput. Des. 45, 4 25. Available from: https://doi.org/10.1016/j.cad.2012.06.006. Pathmanathan, P., Gray, R.A., Romero, V.J., Morrison, T.M., 2017. Applicability analysis of validation evidence for biomedical computational models. J. Verif. Valid. Uncertain. Quantif. 2, 021005. Available from: https:// doi.org/10.1115/1.4037671. Shamimi, A., Amin-Ahmadi, B., Stebner, A., Duerig, T., 2018. The effect of low temperature aging and the evolution of R-phase in Ni-rich NiTi. Shape Mem. Superelasticity. Available from: https://doi.org/ 10.1007/s40830-018-0193-9.

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Evaluation of Mechanical Fatigue and Durability A.R. Pelton G.RAU Inc., Santa Clara, CA, United States

Cardiovascular implants, such as stents, stent grafts, heart valve frames, and permanent vena cava filters, are designed to function for the lifetime of the patient. The FDA requires durability assessment of cardiovascular implant durability for a minimum of 10 years that results in 380 million cycles of deformation from cardiac pulsatility (based on a heart rate of 1.2 Hz), 10 million cycles musculoskeletal motions for each leg from walking (Silva, 2002), and 100 million respiratory cycles (Hooker et al., 1989). Given the dynamic conditions of the human anatomy in a corrosive environment with deformations from cardiovascular, pulmonary, and musculoskeletal physiology, this places a burden on the requirements for in vivo durability. Cardiovascular implant device fractures may result in thrombosis, perforation, restenosis, and migration resulting in morbidity and mortality (Adlakha et al., 2010). The mechanics of repeated motions of engineering materials involves the field of mechanical fatigue. Who has not flexed a paperclip throughout a boring conference call that resulted in fracture of the paperclip? Whereas each flex is of low magnitude, fatigue is a Handbook of Vascular Motion DOI: https://doi.org/10.1016/B978-0-12-815713-8.00015-2

damage accumulation process that could eventually result in failure. Consequently, fatigue is responsible for a large percentage of engineering failures in the transportation field, including automotive, aerospace, and railway applications (Manson and Halford, 2006). In an extensive survey by National Institute of Standards and Technology, the majority of the engineering fatigue failures were due to fabrication defects, design flaws, abnormal service, and defective material (Manson and Halford, 2006). It is, therefore, imperative that fatigue durability investigations of cardiovascular implant devices be conducted to include the effects of fabrication, design, service, and material selection, as well as duration. This is especially important since once a device is implanted it is not possible to do “preventive maintenance,” unlike other fatigue-sensitive applications. The FDA has long been concerned with the fatigue durability of cardiovascular devices. Historically, the FDA (1995, 2005) has recommended benchtop radial fatigue testing of stents deployed into mock arteries under physiological systolic/diastolic pressure cycles at

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accelerated frequency relative to cardiac rhythm. According to these guidelines, the fatigue durability requirement would be achieved if no fatigue fractures were observed in 380 million cycles, or an equivalent of 10 years at physiologically relevant conditions of pulsatile pressure and mock vessel compliance. This approach is termed “test-to-success” because devices are deemed to have “passed” if they survive 380 million cycles without a single fracture. Whereas radial pulsatile fatigue tests serve as useful indicators of device performance, these test regimens do not always predict device durability in the clinical setting with perfect accuracy (Cavanaugh et al., 2006). Therefore more contemporary approaches to benchtop testing have emerged to be more predictive of fatigue lifetimes. Other safety-critical industries, such as aerospace and automotive, have long used a “test-to-fracture” approach, whereby devices are tested under a range of conditions, including those exceeding expected service conditions. These fracture and survival data are summarized into a “fatigue-failure” map to predict fatigue life of the engineering components under combinations of cyclic conditions (i.e., duty cycles) and material conditions (Mitchell, 1996). Accordingly, the 2010 FDA Guidance Document for Intravascular Stents recommends that extensive fatigue-life analyses be conducted on the device material in order to determine relevant parameters, such as a fatigue limit, as well as constructing a strain-life diagram (FDA, 2010a). Consequently, this more recent Guidance Document sets a necessary direction for the medical device industry to characterize stents and other cardiovascular devices with a “testto-fracture” methodology under a variety of deformation conditions. The purpose of this chapter is to review the methods used to characterize the in vivo durability of a cardiovascular implant with benchtop testing and computational analysis. Testing methods are summarized with respect to

relevant FDA Guidance Documents and international standards. The principles of fatigue analysis will be discussed, followed by three case studies: (1) balloon-expandable cobalt
chromium (Co
Cr) alloy coronary stents, (2) self-expanding Nitinol stents with the indication for superficial femoral arteries, and (3) structural heart Nitinol implants.

PRINCIPLES OF FATIGUE AND DURABILITY ASSESSMENT Fatigue is defined as the progressive localized permanent structural damage that occurs as a result of cyclic stresses and strains. This damage accumulation may lead to the initiation of microcracks, crack propagation and potentially to fracture (Manson and Halford, 2006). Predictions of the initiation and propagation of events, through proper testing and analysis, are critical for the design and optimization of all implant devices. In the late 19th century Wo¨hler (1870) conducted the earliest systematic investigations of fatigue behavior for the German railroad industry during the Industrial Revolution. His methods defined the engineering and scientific methods that are still being used today. The general approach to generate a stress-life or strain-life (Wo¨hler) diagram is to test specimens at a range of applied cyclic stresses/strains and record the number of cycles until fracture. The stress/strain values where the specimens reach a specified number of cycles, whether 107 or 6 3 108 cycles, define the stress/strain fatigue limit. For test conditions above this limit, there is a finite probability of fracture, whereas testing below this limit, there is high probability of survival. Fig. 15.1 is a reproduction of the early Wo¨hler data for smooth and notched steel specimens that were cycled to a maximum of 106 cycles. These curves both show that an increase in stress amplitude leads to a decrease in fatigue life (i.e., fewer cycles to fracture) and

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so-called damage-tolerant analysis (Suresh, 1998). This method implicitly assumes that flaws exist in any material structure, and such flaws (envision the “tear tabs” for easy opening of packaged foods) propagate with cyclic deformation. For this method, fatigue-crack growth from a flaw that is intentionally introduced is measured as a function of cyclically applied stress. This approach, therefore, measures only the propagation stage of the fatigue life. Two important metrics are obtained in damage-tolerant analyses: FIGURE 15.1 Stress amplitude versus cycles to failure of steel with both smooth and notched surfaces. From Wo¨hler, A., 1870. U¨ber die Festigkeitsversuche mit Eisen and Stahl. Zeitschrift fu¨r Bauwesen 20, 73
106; Manson, S.S., Halford, G.R., 2006. Fatigue and Durability of Structural Materials. ASM International.

can be divided into low-cycle (#105 cycles) and high-cycle ($105 cycles) regions. The fatigue data with arrows indicate conditions of survival to 106 cycles; these are the respective 106-cycle fatigue stress limits for these test and material conditions. Stress/Strain amplitudes that are less than those on the curves define regions of high probability of survival. Furthermore, these curves demonstrate that notched specimens (with deliberate surface defects) have substantially lower fatigue stress limits than those with smooth surfaces (nearly 40% lower survival conditions for these Wo¨hler data). These curves highlight the principles that are required for implant device testing in order to derive reliable in vivo fatigue-safe operating conditions. The key finding from these tests is the quantification of the boundary (limit) between fatigue fracture and fatigue survival. Armed with this information, a fatigue safety factor (FSF) can be calculated based on biomechanical forces/deformations and computational analysis. An alternative, and complementary, method to assess fatigue in engineering materials is the

1. Stress-intensity threshold (ΔKth)—The stress-intensity range value below which fatigue-crack propagation occurs at vanishingly low growth rates. The greater the magnitude of ΔKth, the greater the tolerance of stress amplitude and greater probability of survival. 2. Critical crack length (acrit)—The dimensional length of a flaw below which the material will not preferentially propagate a fatigue crack from that flaw. Flaws longer than acrit serve as stress concentrators in a material and act as preferential nucleation sites for fatigue-crack propagation. Both of these general approaches to fatigue are used to characterize and predict fatigue life in cardiovascular devices. The next section presents fatigue testing and analysis methods for cardiovascular implants and is followed by durability case studies of three cardiovascular devices.

CARDIOVASCULAR IMPLANT ANALYSIS AND TESTING METHODS Risk-based approaches (e.g., from a comprehensive product failure mode effects analysis, FMEA) are recommended for durability testing and analysis; that is, the greater the risk to patient or product, the greater the burden of

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durability assessment. Implant device durability is evaluated with computational stress/strain analysis, combined with fatigue analysis, as well as benchtop accelerated fatigue testing. To supplement the broad recommendations from the FDA Guidance Documents, international standards, such as those from ASTM International and International Organization for Standardization (ISO) organizations, provide more detailed methods for analyses and tests, and will be discussed next. To be considered a thorough durability assessment, it is essential to include each manufacturing step, crimping and delivery, device recoil, as well as all physiologic loading conditions specific to the implant device. Physiologic loading may include combinations of the following deformations (Cavanaugh et al., 2006; FDA, 2010a; ISO, 2008, 2010): Radial dilation/compression Torsion Bending Axial tension/compression and Focal or nonfocal cross-sectional crush The previous chapter on device design and computational simulation reviews the powerful tools of computational stress/strain analysis with finite element analysis (FEA) and will not be repeated in detail here, except to emphasize a few salient points. ASTM F2514, “Standard Guide for Finite Element Analysis (FEA) of Metallic Vascular Stents Subjected to Uniform Radial Loading” (ASTM, 2008), summarizes the requirements for the development of finite element models used in the evaluation of the performance of a metallic vascular stent design under uniform radial loading. Although focused on only the radial mode of deformation for stents, the general approach in the standard applies to FEA of other physiologic deformation modes and other cardiovascular implants. The late Dr. Roy Greenberg often stated, “Don’t tell me where the stent works, tell me

where it doesn’t work.” As such, in order to determine the durability of a stent or other implant device, it is essential to conduct “teststo-fracture” (Gong et al., 2009) in addition to “tests-to-success.” A recent industry standard addresses the methods for conducting tests to fracture, in ASTM F3211, “Standard Guide for Fatigue-to-Fracture (FtF) Methodology for Cardiovascular Medical Devices” (ASTM, 2017). This guide provides experimental methodologies to assess and determine the structural fatigue life of implantable cardiovascular medical devices. In addition, and absolutely essential for acceptance by regulatory agencies, the guide outlines several approaches to determine statistical bounds on fatigue life at in vivo use conditions. Fig. 15.2 schematically illustrates the approach that incorporates the principles of Wo¨hler testing along with statistical distributions along the experimentally determined curve. In this figure, S can represent either stress or strain and N represents number of cycles, or life. The key determinations from this fatigue graph are as follows: 1. The mean S
N curve that summarizes the experimental fatigue-life data. 2. The derived design curve that illustrates the fatigue-life data for the implant device; the exact position of the design curve depends on the in vivo conditions as well as expected fatigue safety limits. 3. The fatigue strength (strain) limit at 107 cycles. These methods use measured fatigue life derived in whole or in part from hyperphysiological testing to fracture. This guide is general in nature and applies to the use of a complete cardiovascular medical implant or a subcomponent (extracted cell) of a cardiovascular medical device or coupons as test specimens. It is expected that these test articles fully represent the entire manufacturing process (including crimping and simulated use) and contain any surface defects that could affect

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CASE STUDY 1: BALLOON-EXPANDABLE STENT

FIGURE 15.2 Fatigue-life model depicting terminology where S is stress (or strain) and N is fatigue life (number of cycles to fracture). The difference between the mean S
N curve and the design curve provides the fatigue safety factor. From ASTM, 2017. F3211-17 Standard Guide for Fatigue-to-Fracture (FtF) Methodology for Cardiovascular Medical Devices. ASTM International.

fatigue durability. Furthermore, the guide recommends that the sample size be chosen to establish conformance to a predetermined specification with appropriate statistical confidence levels, in accord with the product FMEA. One efficient method to estimate the median load to fracture at a given number of cycles is an “up
down” or “staircase” method (Little, 1975). This basic up
down technique is to choose the initial testing at an estimate of the force (or deformation) associated with median fatigue strength for the desired number of cycles. This deformation condition can be determined from prior experience and/or through FEA predictions. If the specimens do not fracture by run-out to a specific number of cycles at that condition, then the next test condition is run at one load increment (mean, amplitude, or both) greater in load. Otherwise, the test is run at one load increment lower. This process is repeated until sufficient confidence is obtained from the testing. The fatigue strain limit line at a certain number of cycles can thus be determined in relatively few iterations. The following sections summarize three methods that have been successfully used for:

(1) balloon-expandable Co
Cr stents; (2) selfexpanding Nitinol stents; and (3) Nitinol structural heart devices.

CASE STUDY 1: BALLOONEXPANDABLE STENT Balloon-expanded stents have historically been composed of stainless steel (e.g., AISI 316L), and more recently the medical device industry has incorporated Co
Cr alloys (e.g., L605). Stents are inserted into the diseased site over an inflatable balloon generally from peripheral access. Once the stent is in position the balloon is pressurized to expand the stent to the shape of the target site. During this radial expansion the stent is plastically (permanently) deformed so that it remains in its open shape to overcome vessel recoil in order to maintain blood flow in the vessel. The stents tend to be rigid due to the inherent stiffness of the chosen engineering materials, which is ideal for maintaining luminal diameter. Consequently, relatively small stent diametric changes occur from the cardiac pulse pressures. The drawback of such stiff stents is that

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they are more prone to fracture when placed at branch points or in tortuous vessels that produce higher mechanical perturbations (Adlakha et al., 2010). The linear-elastic mechanical characteristics of stainless steel and Co
Cr alloys allow their fatigue behavior to be analyzed with stress-based methods. Furthermore, since there is a wealth of mechanical data on these alloys in the literature, it is often sufficient to conduct relatively few device benchtop tests and supplement with computational analysis and literature references. In vivo stent loading is provided by cyclic systolic/diastolic pressurization from cardiac heartbeats. Therefore radial fatigue testing, per ASTM F2477 (ASTM, 2013b), is the most common benchtop test method for coronary stents. Next is a summary of a fatigue analysis of a Co
Cr balloon-expandable coronary stent that employs a sophisticated testing and analytical approach. Marrey et al. (2006) presented a novel fatigue analysis of a Co
Cr coronary stent, where the design life was conservatively

evaluated with a fracture mechanics methodology. Their approach based the primary fatigue-life assessment on a traditional yet conservative version of a stress-life analysis; additionally, they used fracture mechanics to evaluate the role of preexisting flaws. Fracture mechanics provides a powerful methodology to quantify the severity of flaws (inherent in the material or from processing) in terms of their potential for reducing the safe life of the stent. The first step in their method was to analyze each step of the stent loading process and to determine the associated stress
strain states. Fig. 15.3 shows a schematic of the coronary stent expansion process considered in the fatigue analysis starting with the as-manufactured (laser-cut) stent, crimping onto the balloon, radial expansion from balloon dilation, and then incorporation in the coronary artery followed by pulsatile cycles from cardiac cycles. The second step in their investigation was to determine the experimental stress amplitude versus life (S
N) curve for the Co
Cr stent

FIGURE 15.3 Schematic diagram of the steps analyzed for the fatigue analysis of a balloon-expandable stent, including crimping onto the balloon, radial expansion to the nominal diameter of the vessel, and a balanced stress-state configuration. From Marrey, R.V., Burgermeister, R., Grishaber, R.B., Ritchie, R.O., 2006. Fatigue and life prediction for cobalt-chromium stents: a fracture mechanics analysis. Biomaterials. 27 (9), 1988
2000.

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CASE STUDY 1: BALLOON-EXPANDABLE STENT

FIGURE 15.4 Stress amplitude versus number of cycles (S
N) fatigue data for 125 μm diameter wire specimens of Co
Cr alloy, tested in rotary bending with zero mean stress (R 5 21) in 37 C 0.9% saline solution at 60 Hz. The runout stress amplitude of 207 MPa was determined for these conditions to 4 3 108 cycles. This value is used in the modified Goodman analysis in Fig. 15.5. From Marrey, R.V., Burgermeister, R., Grishaber, R.B., Ritchie, R.O., 2006. Fatigue and life prediction for cobalt-chromium stents: a fracture mechanics analysis. Biomaterials. 27 (9), 1988
2000.

700

Applied stress amplitude, Δσ/2 (MPa)

650

Endurance stress Applied Alt stress Best fit trendline

600

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550 500 450 400 350 300 250 200 150 104

105

106

107

108

109

Number of fully reversed applied cycles, N (cycles)

alloy. Fatigue limit testing was conducted in saline solution at 37 C under conditions of fully reversed cycling (zero mean stress) as shown in Fig. 15.4. The 4 3 108 cycle fatigue strength of the Co
Cr alloy was determined to be 207 MPa. This value, along with the experimentally determined tensile strength of the material, was plotted on a mean stress versus stress amplitude diagram and characterized with a modified Goodman fatigue analysis (Suresh, 1998), as shown in Fig. 15.5. This analysis demonstrates that the allowable stress amplitude linearly decreases with increasing mean stress. The stress values under the Goodman line are predicted to survive stress cycling, whereas those values above the line are predicted to fracture. The computed stress values from FEA at different locations of the stent during the imposed 100 mmHg pulse pressures are also plotted on Fig. 15.5. Under these fatigue conditions, it is clearly seen that the stent is predicted to survive the 4 3 108 cycles since all computed values are below the Goodman failure line.

The greatest in vivo stress values are located at a mean stress of 735 MPa and a stress amplitude of 52 MPa (circled value in Fig. 15.5). These values are used to determine the FSF which quantifies the proximity of the mean stress and stress amplitude to the fatiguefailure line. A FSF value of 1 indicates that the computed stress values fall on the line and predicts a finite probability of fatigue fracture. FSF values greater than 1 predict greater probability of survival. Under the conditions considered for this stent analysis the FSF was calculated to be 1.32 and, therefore, is predicted to survive these in vivo conditions with high probability. For many cardiovascular device investigations, the above benchtop tests, FEA, and FSF calculation would be sufficient to demonstrate fatigue durability safety. However, since FEA is a continuum mechanics method, these analyses do not consider the effects of inherent flaws in the stent, whether from the material or from the stent processing. Therefore the investigators conducted additional fracture mechanics

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FIGURE 15.5 Comparison of predicted mean stresses and stress amplitudes with the modified Goodman curve (red line). The calculated stress data were determined with FEA under a range of predicted in vivo conditions. With zero mean stress (R 5 21) the stress amplitude is 207 MPa (from Fig. 15.4). At zero stress amplitude the mean stress is equivalent to the UTS of 1449 MPa. The numerical integration point with coordinates (735, 52) MPa (circled in red) is closest to the Goodman curve and represents the worst case fatigue region. The fatigue safety factor under these conditions is calculated as the distance from that point to the Goodman line and is equal to 1.32. FEA, Finite element analysis; UTS, ultimate tensile stress. From Marrey, R.V., Burgermeister, R., Grishaber, R.B., Ritchie, R.O., 2006. Fatigue and life prediction for cobalt-chromium stents: a fracture mechanics analysis. Biomaterials. 27 (9), 1988
2000.

analyses to quantify the effects of cracks. For this part of the analysis the local stresses on the stent at each step were converted into “stress intensities” (local stresses in the presence of cracks) that were calculated as a function of crack size. Under fatigue loading conditions a preexisting crack grows according to (Suresh, 1998): da 5 CðΔKÞm dN where a is the crack length, N is the number of fatigue cycles, C and m are experimentally determined scaling constants, and ΔK is range with ΔK 5
the stress-intensity

Ksystolic 2 Kdiastolic
. Ksystolic and Kdiastolic represent the values of K at the end of the systolic and diastolic pressure cycles, respectively. From fracture pffiffiffiffiffi mechanics principles, Ksystolic 5 p πa and Kdiastolic 5 Qσ systolic ffiffiffiffiffi Qσdiastolic πa, where QB1 and σsystolic and σdiastoic are the respective applied stresses from the pulse pressures. Experimental data (Ritchie and Lubock, 1986) for fatigue crack
growth rates for the Co
Cr alloy were

then used to determine the remaining stent life based on the loading cycles required to propagate the flaw to a critical size, when stent fracture would be predicted to occur. At very low growth rates approaching B1028 mm/cycle, the stress-intensity range is referred to as the fatigue threshold, ΔKth. Below this value, preexisting cracks are expected to be dormant, and therefore the stent is considered fatigue safe. For the worst case conditions analyzed for this stent, ΔKth 5 2.58 MPaOm. The critical crack length that corresponds to this value of ΔKth was calculated to be 90 μm. The importance of this value is that cracks less than this value have a lower probability of growth into fracture. Quality control stent inspections are typically done at magnifications of 10
40 3 which will magnify a 90 μm crack to 0.9
3.6 mm, which are perceivable with careful inspection. Furthermore, FEA provides high stress “hot spots” of critical stresses or strains that guide the inspections to ensure that cracks do not exist in the highest risk locations. Therefore potential fracture

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CASE STUDY 2: NITINOL SELF-EXPANDING STENT

candidates can be screened with proper visual inspections, and premature failure due to balloon inflation or in vivo radial fatigue should not occur under the assumed boundary conditions (Marrey et al., 2006).

CASE STUDY 2: NITINOL SELFEXPANDING STENT Nitinol cardiovascular implants present an entirely different fatigue deformation profile than investigated by early researchers (see the references in Robertson et al., 2012) and, therefore, require different approaches to mimic in vivo conditions. Nitinol has a unique combination of properties, including shape memory and superelasticity that allows up to 10% strain recovery (Otsuka and Ren, 2005), compared with typical 0.2% elastic recovery from stainless steel and Co
Cr. Furthermore, in their pioneering studies, Berg et al. showed conclusively that superelastic Nitinol does not follow Goodmantype fatigue behavior, that is, the allowable fatigue strain does not necessarily decrease with increasing mean strains as with stainless steel and Co
Cr (Tabanli et al., 1999, 2001). Unlike balloon-expandable stents, Nitinol cardiovascular implant devices are thermomechanically processed to their fully open geometry. For example, 2 mm OD tubing is laser

321

machined with an as-cut pattern and then radially expanded to intermediate diameters with tapered steel mandrels, followed by thermal heat treatments (nominal 500 C for B5 min). This expansion/heat treatment process is repeated until the final dimensions are achieved. The shape memory and superelastic properties allow these Nitinol self-expanding stents to undergo a large single-strain excursion (B10%) during constraint into a delivery system (Duerig et al., 2000). Once the cardiovascular device is loaded into the delivery catheter, the system is sterilized. For example, EtO sterilization reaches B60 C, which may induce additional forces on the constrained stent that are required input in the FEA models. Upon implantation the stent begins its recovery to its preset geometry until it contacts the vessel walls and reaches an expansionconstraint force equilibrium. The stent is designed to be slightly oversized with respect to the vessel diameter, for example, an 8 mm stent in a 6 mm vessel. This “interference fit” produces a mean strain on the stent as illustrated in Fig. 15.6 for a 9 mm Cordis SMART stent deployed into 9, 6, and 3 mm ID silicone tubes at 37 C. The mean strains are calculated with FEA and depend on deformations such as the change in strut angle, θ (Pelton, et al., 2008). In addition to the mean strains the physiological movements from the

FIGURE 15.6 Cordis SMART stents (9 mm) deployed into silicone tubes with physiologic compliance of 5%
7%/ 100 mmHg at 37 C. The amount of oversizing increases with decreasing tube ID with a decrease in strut angle, θ, and a corresponding increase in mean strain. Here the mean strains were calculated from FEA as 0.1%, 5%, and 7.4%, respectively, for the 9 (A), 6 (B), and 3 mm (C) ID tubing. From Pelton, A.R., Schroeder, V., Mitchell, M.R., Gong, X.-Y., Barney, M., Robertson, S.W., 2008. Fatigue and durability of Nitinol stents. J. Mech. Behav. Biomed. Mater. 1, 153
164.

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cardiac systolic
diastolic cycle as well as musculoskeletal motions induce strain amplitudes. The effects of the combinations of strains on the Nitinol peripheral stent durability are discussed next. Although different in vivo biomechanical deformations work simultaneously (albeit at different frequencies and phase relationships), it is important to understand the individual contributions of each type of deformation so that all fatigue contributions are captured on the benchtop as well as with FEA. Recent literature has begun to clarify the anatomical and physiological environment of the superficial femoral and popliteal arteries, as discussed in earlier chapters. For the following example, we will consider two types of motions as input for durability testing and analysis: those from cardiac pulse pressures and those from bending and axial compression from musculoskeletal (leg) motions.

Cardiac Pulse Pressures Peripheral arteries are known to vary in diameter and compliance properties, such that when they are stented a range of balanced diameters and resultant strains will be imparted to the implanted stent. Upon implantation the stent is constrained by the arterial wall with a reduction of the stent diameter to less than the labeled or fully expanded size. Therefore the stent exerts a chronic outward force on the arterial wall that is designed to prevent migration (Duerig et al., 2000). The ASTM F2477 standard for pulsatile fatigue testing suggests 80 mmHg pulse pressure (160/80 mmHg) and 4% distension for the mock vessel (5% distension equivalent for 100 mmHg pulse pressure) (ASTM, 2013b). Superelastic Nitinol stents tend to “breathe” with the arterial pulse pressures from the cardiac cycle with resultant diastolic and systolic balanced forces and diameters (Duerig et al., 2000). The resultant diametric

FIGURE 15.7 Scanning electron microscopy image of a SMART “strut V” illustrating the strut length, L, width, w, and bridge. The stent wall thickness, t, is projected into the page. From Pelton, A.R., Schroeder, V., Mitchell, M.R., Gong, X.-Y., Barney, M., Robertson, S.W., 2008. Fatigue and durability of Nitinol stents. J. Mech. Behav. Biomed. Mater. 1, 153
164.

changes induce local cyclic bending stresses/strains on the stent structure (Auricchio et al., 2016; Berti et al., 2017; Pelton et al., 2008). For this discussion, we will consider the Cordis SMART Nitinol self-expanding stent, as shown in Fig. 15.6. The structural features of the stent are illustrated in Fig. 15.7 and include the “V”-strut geometry with strut length, L, strut width, w, strut thickness, t, and strut bridge. In order to determine the fatigue durability of this stent over a range of deformation, two complementary tests were conducted (Pelton, 2011; Pelton et al., 2008). In this extensive investigation, “diamond-like” coupons were manufactured from Nitinol tubing with the exact processing parameters as those used for the stents. The geometry of the diamond test articles was chosen to mimic the strut features of the stent; a total of 432 specimens were tested with various combinations of mean and strain amplitudes. Fig. 15.8 shows a Nitinol diamond test article mounted on a fatigue tester. FEA was used to convert target strains

III. UTILIZING VASCULAR MOTION DATA AND IMPLICATIONS

CASE STUDY 2: NITINOL SELF-EXPANDING STENT

323

FIGURE 15.8 Customized fixture used to fatigue test the Nitinol diamond specimens. Up to four specimens were tested simultaneously under identical conditions of mean strain and strain amplitude. Fracture is monitored for each specimen with an external detection system. From Pelton, A.R., Schroeder, V., Mitchell, M.R., Gong, X.-Y., Barney, M., Robertson, S.W., 2008. Fatigue and durability of Nitinol stents. J. Mech. Behav. Biomed. Mater. 1, 153
164.

(both mean and amplitude) into testing displacements. The fatigue tests were conducted to fracture or to a run-out condition of 107 cycles. Similar approaches to determine Nitinol implant durability have recently been published (Auricchio et al., 2016; Berti et al., 2017; Bonsignore, 2017; Carnelli et al., 2011; Dordoni et al., 2014, 2015). For validation of the pulsatile fatigue behavior of the Nitinol stent, 63 conditions of pulsatile-to-fracture proof tests with 10 mm Cordis SMART stents were conducted (Pelton et al., 2008) in accord with ASTM F2477 (ASTM, 2013b). The stents were deployed into 6
8 mm ID silicone mock arteries (2
4 mm oversizing) to generate the mean strains; silicone tube radial compliance was either 6% or 10% per 100 mmHg. Pulse pressures were adjusted in order to generate cyclic diametric distensions with resulting strain amplitudes on the stents. FEA was used to determine the

resultant mean strains and strain amplitudes for the 107-cycle fatigue tests as a function of oversizing and pulsatile pulse pressures. It should be noted that many of these experimental conditions exceed the physiologic conditions observed in vivo in order to induce fractures deliberately. These experimental stent pulsatile fatigue data are overlaid on the diamond fatigue-life data in Fig. 15.9. Stents fractured at less than 107 cycles only at high strain amplitude conditions as predicted by the conservative fatigue strain line (red dotted line). The stents survived to 107 cycles with strain amplitudes below 6 0.45%, which is consistent with the B0.4% fatigue strain-limit line from the diamond testing. From FEA the in vivo conditions for pulsatile fatigue results in a worst case mean strain of 1.22% and a corresponding strain amplitude of 0.24%. Based on these fatigue strains and with the use of the diamond fatigue data in

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15. EVALUATION OF MECHANICAL FATIGUE AND DURABILITY

FIGURE 15.9

Constant-life diagram from the diamond stent subcomponent fatigue testing where the various conditions of mean strain and strain amplitude are plotted. Conditions that survived the 107-cycle testing are shown as open squares, whereas cyclic conditions that led to fracture ,107 cycles are represented with closed squares. The 107-fatigue strain limit of 0.4% is illustrated with a dotted line. These data indicate that fatigue-fracture probability increases at strain values greater than 0.4% strain amplitude, whereas at strain amplitudes ,0.4% there is a greater probability of survival. The whole stent pulsatile fracture data are overlaid on the diamond fatigue data. The open circles represent test conditions for SMART stents that survived 107 pulsatile cycles. The closed circles are those conditions that led to fracture of the SMART stent at ,107 pulsatile fatigue cycles. Note that the stent fatigue testing is consistent with the diamond subcomponent data, whereby fracture tends to occur above the 0.4% strain amplitude (dotted line) for a range of mean strains. From Pelton, A.R., Schroeder, V., Mitchell, M.R., Gong, X.-Y., Barney, M., Robertson, S.W., 2008. Fatigue and durability of Nitinol stents. J. Mech. Behav. Biomed. Mater. 1, 153
164.

Fig. 15.9, the FSF 5 0.4%/0.24% 5 1.7 for the cardiac cycling. With such a large FSF, it is not expected that the cardiac cycles will lead to stent fractures.

Musculoskeletal and Respiratory Motions In addition to the cyclic deformations from the cardiac cycle, musculoskeletal and respiratory motions combine to result in a unique stress/strain state on implanted stents (Ansari et al., 2013; Cheng et al., 2006; Choi et al., 2009; Desyatova et al., 2017; Ganguly et al., 2011; Gokgol et al., 2017; Maleckis et al., 2017; Nikanorov et al., 2009; Poulson et al., 2018;

Simons et al., 2010; Suh et al., 2011, 2013). For the specific case of stenting the femoropopliteal arteries, it is assumed that there are approximately 107 steps/leg of walking motion (Silva, 2002) as well as nearly 750,000 cycles/leg of sitting/stair climbing motions (Morlock et al., 2001) for a 10-year duration. As an example of such an investigation, we present the results of FEA of a Nitinol open source stent (OSS) (Saffari, 2012) that is compared to results from benchtop testing of the Cordis SMART stent. The cyclic axial benchtop tests were conducted in accord with ASTM F2942 (ASTM, 2013a), whereby the SMART stents were deployed into silicone mock arteries

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CASE STUDY 2: NITINOL SELF-EXPANDING STENT

TABLE 15.1 Boundary Conditions and Resultant Maximum Fatigue Strains From Finite Element Analysis Simulation of the Nitinol Open Source Stent Boundary Condition

Mean Strain, %

Strain Amplitude, %

8.6% Axial compression

3.9

0.69

22.6 mm Bending radius

5.6

1.12

Data from Nikanorov, A., Schillinger, M., Zhao, H., Minar, E., Schwartz, L.B., 2009. Assessment of self-expanding Nitinol stent deformations implanted into the femoropopliteal artery. In: Paper Presented at the SVS Vascular Annual Meeting. Society for Vascular Surgery, Denver, CO.

with 5%
7% compliance per 100 mmHg with 2 mm oversizing (8 mm stents in 6 mm vessels). Testing was done at 37 C with a water flowloop adjusted to diastolic conditions (worst case conditions from FEA). In the computational simulations the OSS is subjected to femoropopliteal artery axial compression and bending boundary conditions of 90 /90 knee/hip flexion from sitting/standing motions (Nikanorov et al., 2009). The maximum resultant mean strains and strain amplitudes for these simulated conditions are shown in Table 15.1. Fig. 15.10 (top) shows the resultant “point cloud” analysis from FEA of the 8.6% axial compression simulation of the OSS superimposed on a published Nitinol fatigue diagram (Pelton, 2011; Pelton et al., 2008). The point cloud shows all combinations of mean strain and strain amplitudes from each of the 165,912 elements analyzed for the OSS. The color strain map of the OSS with the location of the maximum strain amplitude is also shown for these axial compression conditions. Much of the stent has fatigue strains less than the 107-cycle fatigue limit with a corresponding lower probability of stent fracture in these regions. However, there are also several sections of the stent that exceed the strain-limit line that predicts a greater probability of fracture. As such, the FSF for these sections are ,1. Fig. 15.10 (bottom) shows benchtop fatigue data from the

325

Cordis SMART stent with a similar geometry to the OSS that was tested with six different axial compression conditions to 107 cycles. These benchtop data demonstrate that the stent is able to survive 107 cycles (corresponding to 10 years of implant time) at # 8% axial compression (ΔL/L), which corresponds to a walking gait. At conditions of $ 10% axial compression, however, the stent shows fractures as early as 103
104 cycles (corresponding to 0.5
4 days of implant time). As such, the FEA of the OSS is in good agreement with the benchtop results. Cyclic bending benchtop tests were conducted in accord with ASTM F2942 (ASTM, 2013a), whereby the SMART stents were deployed into silicone mock arteries with 5%
7% compliance per 100 mmHg with 2 mm oversizing (8 mm stents in 6 mm vessels). Testing was done at 37 C with a water flowloop adjusted to diastolic conditions (worst case conditions from FEA). Fig. 15.11 (top) shows the point cloud fatigue strain data from the computational simulation of the OSS under conditions of cyclic 22.6 mm bend radius (Saffari, 2012). The FEA bend data from these severe sit/stand boundary conditions are also superimposed on a Nitinol fatigue strain-limit diagram (Pelton, 2011). These simulations result in a mean strain of 5.6% and strain amplitude of 1.12%; in this case, a much greater number of the stent elements exceed the fatigue strain limit. The greater probability of fracture with bend radii less than B45 mm is confirmed with the benchtop data shown in Fig. 15.11 (bottom). The red circles indicate stent fracture, whereas the green open circles represent stent survival to 107 cycles. The published fatigue strain-limit diagrams (Figs. 15.9
15.11) (Pelton, 2011; Pelton et al., 2008) used in these analyses can also be graphed to show the statistical evaluation of fracture probability. Robertson et al. (2015) demonstrated this approach with five Nitinol materials as shown in Fig. 15.12 (top). This

III. UTILIZING VASCULAR MOTION DATA AND IMPLICATIONS

1.4 1.2 1.0 Strain amplitude (%)

8.6% 0.8 0.6 0.4 0.2 0.0

0

1

2

3

4

5

6

7

8

9

10

Mean strain (%)

Equivalent patient life (years) 14

10

–3

10–2

10–1

100

101

106

107

Axial compression %

12 10 8 6 4 2 0 103

104

105 Cycles

FIGURE 15.10 (Top) FEA “point cloud” analysis of the mean strains and strain amplitudes from the 165,912 elements for the Nitinol OSS device under 8.6% axial compression conditions. The inset image shows the location of the maximum strain amplitude of 0.69%. (Bottom) Benchtop axial fatigue data from a Nitinol stent with similar geometry as the OSS. The red circles indicate stent fracture, whereas the green open circles represent stent survival to 10 M cycles. These data are consistent with the FEA simulations. FEA, Finite element analysis; OSS, open source stent. From Saffari, P., 2012. Best practices for FEA simulation of a stent. In: Paper Presented at the SIMULIA Regional User Meeting 2012. Linz, Austria.

CASE STUDY 2: NITINOL SELF-EXPANDING STENT

1.4

Strain amplitude (%)

1.2 1.0

ρ = 22.6 mm

0.8 0.6 0.4 0.2 0.0

0

1

2

3

6 4 5 Mean strain (%)

7

8

Equivalent patient life (years) 20

10–3

10–2

10–1

100

104

105 Cycles

106

9

327

FIGURE 15.11 (Top) FEA “point cloud” analysis of the mean strains and strain amplitudes from the 165,912 elements for the Nitinol OSS device under cyclic 22.6 mm bend radius conditions. The inset image shows the location of the maximum strain amplitude of 1.12% that corresponds to the greatest strain amplitude from the point cloud data (circled in red). (Bottom) Benchtop axial fatigue data from a Nitinol stent with similar geometry as the OSS that demonstrates that cyclic bend with bend radii less than B45 mm have a greater probability of fracture. The red circles indicate stent fracture, whereas the green open circles represent stent survival to 10 10 M cycles. The data are consistent with the FEA simulations. FEA, Finite element analysis; OSS, open source stent. From Saffari, P., 2012. Best practices for FEA simula101 tion of a stent. In: Paper Presented at the SIMULIA Regional User Meeting 2012. Linz, Austria.

30

Bend radius (mm)

40 50 60 70 80 90 100 103

figure illustrates the logistic regression analysis of fracture probability of Nitinol that increases as a function of strain amplitude for each of the materials. As an example of the utility of this data analysis, Scheinert et al. (2005) reported

107

fracture rates of 15%, 52%, and 31%, respectively for the Cordis SMART, Bard Luminexx, and Abbott SelfX stents. These 1-year fracture rates are marked with stars on the red curve for Standard VAR (vacuum arc remelted) Nitinol

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FIGURE 15.12 (Top) Logistic regression of fracture probability of Nitinol diamond fracture at 10 M cycles versus strain amplitude for five versions of Nitinol including standard VAR and H.P. VAR under conditions of 6% crimp strain and 3% mean strain. The statistical analysis indicates that decreases in inclusion length (101
40 μm) and inclusion volume fraction (1.5%
0.5%) result in greater fatigue strain limits. Star markers are added to correspond to fracture rates of three early Nitinol peripheral stents. (Bottom) Comparison of fracture probability of H.P. VAR and EBR Nitinol at 6% crimp strain and 5% mean strain. EBR Nitinol has inclusion size ,5 μm with an inclusion volume fraction of ,0.5% with a concomitant increase in strain limit. EBR, Electron beam refined; H.P, high purity; VAR, vacuum arm remelted. From Robertson, S.W., Launey, M., Shelley, O., Ong, I., Vien, L., Senthilnathan, K., et al., 2015. A statistical approach to understand the role of inclusions on the fatigue resistance of superelastic Nitinol wire and tubing. J. Mech. Behav. Biomed. Mater. 51, 119
131; Scheinert, D., Scheinert, S., Sax, J., Piorkowski, C., Bra¨unlich, S., Ulrich, M., et al., 2005. Prevalence and clinical impact of stent fractures after femoropopliteal stenting. J. Am. Coll. Cardiol. 45, 312
315; Pelton, A.R., Pelton, S.M., Ulmer, J., Niedermaier, D., Plaskonka, K., Mitchell, M.R., et al., 2017. The use of next generation Nitinol for medical implants. In: European Symposium on Vascular Biomaterials. Strasbourg, France, pp. 35
44; Pelton, A.R., Pelton, S.M., Jo¨rn, T., Ulmer, J., Niedermaier, D., Plaskonka, K., et al., 2018. The quest for fatigue-resistant Nitinol for medical implants. In: Mitchell, M. R., Berg, B., Woods, T. (Eds.), Fourth Symposium on Fatigue and Fracture of Metallic Medical Materials and Devices (STP1616), accepted for publication. ASTM.

CASE STUDY 3: STRUCTURAL HEART IMPLANT DEVICE

and correspond to fatigue strain amplitudes of approximately 0.65%, 0.75%, and 0.70%, respectively. Patency rates of 82%, 52%, and 44%, scaled with the fracture rates for the three Nitinol stents. The in vivo axial displacements for these patients were likely similar to each other, so that the differences in strain amplitude and, therefore, patency rates reflect the differences in stent design. This correlation to in vivo fracture rates thus provides verification for benchtop testing and FEA. Analysis of the test conditions and microstructural features of different Nitinol materials Fig. 15.12 (top) clearly shows that fatigue behavior depends on inclusion size and volume fraction (Robertson et al., 2015). For example, the materials with the lowest fatigue strain limit have inclusion lengths of B101 μm and inclusion volume fractions of 1.5%, whereas the two Nitinol materials with smaller inclusions (B40 μm) and lower volume fraction (0.5%) have greater strain limits. More recently, Nitinol with even greater microstructural purity became available for cardiovascular implant devices as shown in Fig. 15.12 (bottom) (Pelton et al., 2017, 2018). This electron beam refined (EBR) Nitinol has # 5 μm oxide inclusions and a resultant fatigue strain limit of B2%. The impact of these increases in fatigue strain limit can be seen for the cases of axial compression and bending considered above. The original diamond fatigue data (Figs. 15.9
15.11) were obtained with the Nitinol with the lowest fatigue limit and, therefore, demonstrate an FSF , 1 for both axial compression and bending conditions considered. The data in Fig. 15.12 (bottom) show that the Nitinol with a fatigue strain limit of 1% at higher mean strains would result in an FSF of 1.0%/0.69% 5 1.45 for the axial compression conditions. However, the FSF for this Nitinol would still be ,1 for the bending conditions. The EBR Nitinol with a fatigue strain limit of 2% would result in an FSF of 2.9 for axial compression and 1.78 for bending and, therefore,

329

will likely have a greater probability of survival under these boundary conditions. As such, the selection of which Nitinol material to use may depend on the in vivo fatigue strains.

CASE STUDY 3: STRUCTURAL HEART IMPLANT DEVICE During the past decade, there has been a wave of transcatheter replacement heart valves developed, including those for aortic, mitral, and tricuspid. The FDA has approved two transcatheter aortic valve replacement (TAVR) devices in the past few years. Edwards SAPIEN system (Edwards Lifesciences Corporation, Irvine, California) was the firstgeneration balloon-expandable TAVR device that consisted of a tri-leaflet, bovine pericardial tissue valve attached to a stainless-steel frame. Newer generations of balloon-expandable TAVR devices include SAPIEN XT and SAPIEN 3 valves, which can be deployed through transapical, transfemoral, transaxillary, and transaortic approaches, and consist of Co
Cr frames (Thourani et al., 2016). The first self-expandable TAVR device was introduced in the Medtronic CoreValve system (Medtronic Inc., Minneapolis, Minnesota), which consisted of tri-leaflet porcine pericardial tissue with a self-expanding Nitinol frame. This initial self-expandable valve iteration was followed by the Medtronic Evolut R valve and later by the newest-generation Evolut Pro valve (Mahtta et al., 2017). These heart valve devices are subjected to a broad range of deformation modes due to the anatomy and physiology of the heart valves, including radial, elliptical, axial length, bending, torsional, and hydrodynamic loads (Dagum et al., 1999; Vietmeier, 2015). The deformation is driven by cardiac motion between systole and diastole, muscular contractions, valve opening/ closing, and hemodynamic forces.

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15. EVALUATION OF MECHANICAL FATIGUE AND DURABILITY

Definition of in vivo boundary conditions - Identify loading modes - Quantify deformations/forces - Define deployed shapes

Device stress or strain analysis (FEA)

Fatigue demonstration test 400 M cycles

Simulated in vivo conditions

- Geometry - Constituitive material model - Crimp diameter - Deployed shapes

Structural component fatigue assessment Fatigue lifetime assessment Fatigue safety factor determination

Component fatigue tests

Material fatigue life determination

Dynamic failure mode testing

(S-N testing)

- Coupon geometry - Constituitive material model - Target stresses/strains

FIGURE 15.13

Example schematic of a structural component fatigue assessment using a stress- or strain-life approach. From ISO 5840 (ISO, 2010. 5840-3 Cardiovascular Implants—Cardiac Valve Prostheses—Part 3: Heart Valve Substitutes Implanted by Minimally Invasive Techniques).

The FDA (2010b) requires heart valve devices to follow the ISO 5840 guidelines (ISO, 2010) for all benchtop testing, including those for durability. Fig. 15.13 is extracted from ISO 5840 and illustrates the variety of comprehensive fatigue tests and analyses required for regulatory approval for durability. According to this ISO 5840 diagram, once the in vivo conditions are identified (upper left corner box), computational modeling (left box) is required to determine the worst case fatigue strains. The ISO standard also requires material fatigue testing (lower left box), as was described in the earlier examples of rotary bend fatigue of Co
Cr alloy to support the balloonexpandable frame and diamond coupon testing to support the Nitinol stent. As demonstrated for the Nitinol stent for femoropopliteal artery indications, the combination of benchtop testing and FEA provide fatigue lifetime assessment as indicated in the center box of Fig. 15.14. Component fatigue tests require both fatigue demonstration (upper right box) and dynamic failure mode (lower right box) testing. Dynamic failure mode is conducted on fully assembled heart valve devices and is intended to characterize the durability of the

FIGURE 15.14 Schematic of a cantilever-beam fatigue test of a structural heart valve frame extracted cell specimen. The extracted cell is cut from a structural heart device after full manufacturing (laser-cut tubing, expansion, and surface treatment), crimping into a delivery system, sterilization, simulated use, and deployment. The mean and cyclic displacements were determined from finite element analysis.

tissue leaflets (and attachment sutures). Testing is commonly done with an accelerated wear tester, whereby the metallic frame (e.g., Co
Cr or Nitinol) is constrained and a cyclic pulse pressure is applied to the leaflets for

III. UTILIZING VASCULAR MOTION DATA AND IMPLICATIONS

331

CASE STUDY 3: STRUCTURAL HEART IMPLANT DEVICE

FIGURE 15.15 A modified “staircase” method schematic to determine the 107-cycle fatigue strain limit with four test conditions (A
D). The fatigue parameters for condition E to 6 3 108 cycles is determined from extrapolated 107 results from measured slope, b.

2 3 108 cycles. Generally, a Stage 2 hypertensive pressure condition (arterial peak systolic pressure 160
179 mmHg, arterial diastolic pressure 100
109 mmHg) is chosen for these tests. The following is an example of a testing program for a structural heart device that provides both material fatigue life and fatigue demonstration in accord with the FDA guidance document and ISO 5840 standard. The device was modeled by FEA and the dominant deformations (pulsatile fatigue and commissure postdeflections) were determined to be accurately simulated with a cantileverbeam test of an extracted cell, as shown in Fig. 15.14. Testing in this manner minimizes the artifacts that may be encountered from more traditional pulsatile fatigue testing with deployment of the full device into a mock silicone vessel. A modified “staircase” method as described above from the Fatigue-to-Fracture standard (ASTM, 2017) was used for this testing. A total of four tests were conducted to 107 cycles with N 5 12 extracted cells per test, per the schematic diagram shown in Fig. 15.15. Cases A
C were chosen to achieve fatigue fractures between 103 and 105 cycles in order to establish the low-cycle fatigue limit and transition to

high-cycle fatigue. Case D was selected to have run-out to 107 cycles, thereby establishing the 107-cycle fatigue strain-limit line. Case E was chosen to run to 6 3 108 cycles with N 5 30 specimens in order to conform to 95% confidence interval with 90% reliability based on product FMEA with a minimum of 29 specimens with no fractures. In order to determine the fatigue strain runout conditions to 6 3 108 cycles, literature data were used to extrapolate from 107 cycles. For example, the high-cycle fatigue region of Fig. 15.15 illustrates a decreasing strain limit with increasing number of cycles. This high-cycle region is modeled with a power-law relationship, whereby εa 5 AN b , where εa is the strain amplitude, A is considered to be a constant, N is the number of cycles, and b is the power-law exponent, which is the high-cycle fatigue slope as shown in Fig. 15.15 (Basquin, 1910). Previous Nitinol fatigue literature determined that b is on the order of 20.02 (Gupta et al., 2015) and 20.04 (Pelton et al., 2013). This structural heart device was manufactured from early VAR Nitinol with a worst case fatigue strain limit of 0.4% for 107 fatigue cycles. With b 5 20.04, the extrapolated 6 3 108-cycle fatigue strain limit is approximately 85% of 0.4%, or 0.34%.

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332

15. EVALUATION OF MECHANICAL FATIGUE AND DURABILITY

FIGURE 15.16 Probability of fracture as a function of strain amplitude based on the N 5 12 extracted cell testing conditions shown in Fig. 15.15. Condition D is the fatigue strain limit for 107 cycles and condition E is the fatigue strain limit with N 5 30 specimens at 6 3 108 cycles.

This is a powerful method in that it uses extracted cells rather than full devices, so that each device can yield several cells and incorporates any possible fatigue-limiting manufacturing defects as well as effects of crimping, sterilization, and deployment. Further insight is gained by plotting these fatigue data with fracture probability as a function of strain amplitude as shown in Fig. 15.16. As discussed in the previous section, recent Nitinol fatigue testing used logistic regression analyses to demonstrate the statistical power of benchtop results (Pelton et al., 2017, 2018; Robertson et al., 2015). These benchtop fracture probability data may be readily compared to clinical fracture rates, which can be used to predict longer term durability and to improve device design. These comparisons also provide a potent validation of FEA and benchtop tests.

CONCLUSION Durability assessment of cardiovascular devices is an important part of the design

evaluation and regulatory submission process. As physicians and engineers gain a higherfidelity understanding of biomechanics, these complex motions must be incorporated into the testing regime to evaluate device durability. The confidence to predict lifetimes of cardiovascular devices to .108 cycles under relevant in vivo conditions has grown due to the incorporation of the “test-to-fracture” methods as outlined in this chapter. Determination of the experimental fatigue limit coupled with advanced computational analysis provides understanding of the in vivo behavior. This chapter summarized three distinct methods to evaluate durability of cardiovascular devices. The first case study outlined a combination of strain-life characterization, FEA, along with fracture mechanics for a Co
Cr balloon-expandable coronary stent. These tests and analyses showed that the stent should survive delivery, balloon expansion, as well as pulsatile fatigue with a safety factor of .1. Furthermore, the incorporation of crackgrowth mechanics allowed additional confidence for safety as well as a recommendation

III. UTILIZING VASCULAR MOTION DATA AND IMPLICATIONS

REFERENCES

for the range of device crack lengths that should be routinely inspected prior to use. The second case study was summarized for a Nitinol self-expanding stent intended for the superficial femoral and popliteal arteries. Here the fatigue assessment was determined with surrogate test articles that were manufactured from laser-machined tubing. These experiments allowed determination of a fatigue strain limit that was compared to benchtop pulsatile fatigue tests. Furthermore, FEA was used to determine the mean strains and strain amplitudes under severe cases of axial compression and bending. These scatter plots compared favorably with benchtop axial and bending tests. In addition, these fatigue data were compared with predictions with three generations of Nitinol material. Nitinol fatigue fractures initiate at microstructural impurities, such as inclusions, so materials with smaller inclusions and a lower inclusion volume fraction demonstrate a concomitant increase in the fatigue strain limit. The third case study described the durability investigation of a replacement heart valve device. A modified staircase method was used to determine the fatigue strain limit to 107 cycles. The results from these tests allowed the prediction of testing conditions to demonstrate durability to 6 3 108 cycles with a riskbased number of test articles. Greater insight into the fatigue behavior of the device was obtained by graphing the data as fracture probability as a function of strain amplitude. The methods described here to determine durability are essential to reduce the risk of in vivo fractures and, therefore, improve safety of implanted cardiovascular devices.

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849. Dordoni, E., Petrini, L., Wu, W., Migliavacca, F., Dubini, G., Pennati, G., 2015. Computational modeling to predict fatigue behavior of NiTi stents: what do we need? J. Funct. Biomater. 6 (2), 299
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246. FDA, 1995. Guidance Document for Intravascular Stents. FDA, 2005. Guidance Document for Intravascular Stents. FDA, 2010a. Guidance Document for Intravascular Stents. FDA, 2010b. FDA Heart Valves—Investigational Device Exemption (IDE) and Premarket Approval (PMA) Applications. FDA. Ganguly, A., Simons, J., Schneider, A., Keck, B., Bennett, N. R., Herfkens, R.J., et al., 2011. In-vivo imaging of femoral artery Nitinol stents for deformation analysis. J. Vasc. Interv. Radiol. 22 (2), 244
249. Gokgol, C., Schumann, S., Diehm, N., Zheng, G., Buchler, P., 2017. In vivo quantification of the deformations of the femoropopliteal segment: percutaneous transluminal angioplasty vs Nitinol stent placement. J. Endovasc. Ther. 24 (1), 27
34. Gong, X.-Y., Chwirut, D.J., Mitchell, M.R., Choules, B.D., 2009. Fatigue to fracture: an informative, fast, and reliable approach for assessing medical implant durability. J. ASTM Int. 6 (7), 1
10. Gupta, S., Pelton, A.R., Weaver, J.D., Gong, X.Y., Nagaraja, S., 2015. High compressive pre-strains reduce the bending fatigue life of Nitinol wire. J. Mech. Behav. Biomed. Mater. 44, 96
108. Hooker, E.A., O’Brien, D.J., Danzl, D.F., Barefoot, J.A.C., Brown, J.E., 1989. Respiratory rates in emergency department patients. J. Emerg. Med. 7 (2), 129
132. ISO, 2008. 25539-2 Cardiovascular Implants—Endovascular Devices—Part 2: Vascular Stents. ISO, 2010. 5840-3 Cardiovascular Implants—Cardiac Valve Prostheses—Part 3: Heart Valve Substitutes Implanted by Minimally Invasive Techniques. Littlee, R.E., 1975. Manual on Statistical Planning and Analysis, vol. STP588. ASTM International. Mahtta, D., Elgendy, I.Y., Bavry, A.A., 2017. From CoreValve to Evolut PRO: reviewing the journey of selfexpanding transcatheter aortic valves. Cardiol. Ther. 6 (2), 183
192.

Maleckis, K., Deegan, P., Poulson, W., Sievers, C., Desyatova, A., MacTaggart, J., et al., 2017. Comparison of femoropopliteal artery stents under axial and radial compression, axial tension, bending, and torsion deformations. J. Mech. Behav. Biomed. Mater. 75, 160
168. Manson, S.S., Halford, G.R., 2006. Fatigue and Durability of Structural Materials. ASM International. Marrey, R.V., Burgermeister, R., Grishaber, R.B., Ritchie, R. O., 2006. Fatigue and life prediction for cobaltchromium stents: a fracture mechanics analysis. Biomaterials. 27 (9), 1988
2000. Mitchell, M.R., 1996. Fundamentals of modern fatigue analysis for design, ASM Handbook, Fatigue and Fracture, vol. 19. ASM International, Materials Park, OH, pp. 227
262. Morlock, M., Schneider, E., Bluhm, A., Vollmer, M., Bergmann, G., Muller, V., et al., 2001. Duration and frequency of every day activities in total hip patients. J. Biomech. 34, 873
881. Nikanorov, A., Schillinger, M., Zhao, H., Minar, E., Schwartz, L.B., 2009. Assessment of self-expanding Nitinol stent deformations implanted into the femoropopliteal artery. In: Paper Presented at the SVS Vascular Annual Meeting. Society for Vascular Surgery, Denver, CO. Otsuka, K., Ren, X., 2005. Physical metallurgy of Ti
Ni-based shape memory alloys. Prog. Mater. Sci. 50, 511
678. Pelton, A.R., 2011. Nitinol fatigue: a review of microstructures and mechanisms. J. Mater. Eng. Perform. 20 (4), 613
617. Pelton, A.R., Schroeder, V., Mitchell, M.R., Gong, X.-Y., Barney, M., Robertson, S.W., 2008. Fatigue and durability of Nitinol stents. J. Mech. Behav. Biomed. Mater. 1, 153
164. Pelton, A.R., Fino-Decker, J., Vien, L., Bonsignore, C., Saffari, P., Launey, M., et al., 2013. Rotary-bending fatigue characteristics of medical-grade Nitinol wire. J. Mech. Behav. Biomed. Mater. 27, 19
32. Pelton, A.R., Pelton, S.M., Ulmer, J., Niedermaier, D., Plaskonka, K., Mitchell, M.R., et al., 2017. The use of next generation Nitinol for medical implants. In: European Symposium on Vascular Biomaterials. Strasbourg, France, pp. 35
44. Pelton, A.R., Pelton, S.M., Jo¨rn, T., Ulmer, J., Niedermaier, D., Plaskonka, K., et al., 2018. The quest for fatigueresistant Nitinol for medical implants. In: Mitchell, M. R., Berg, B., Woods, T. (Eds.), Fourth Symposium on Fatigue and Fracture of Metallic Medical Materials and Devices (STP1616), accepted for publication. ASTM. Poulson, W., Kamenskiy, A., Seas, A., Deegan, P., Lomneth, C., MacTaggart, J., 2018. Limb flexion-induced axial compression and bending in human femoropopliteal artery segments. J. Vasc. Surg. 67 (2), 607
613.

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Ritchie, R.O., Lubock, P., 1986. Fatigue life estimation procedures for the endurance of a cardiac valve prosthesis: stress/life and damage-tolerant analyses. J. Biomech. Eng. 108, 153
160. Robertson, S.W., Pelton, A.R., Ritchie, R.O., 2012. Mechanical fatigue and fracture of Nitinol. Int. Mater. Rev. 57 (1), 1
36. Robertson, S.W., Launey, M., Shelley, O., Ong, I., Vien, L., Senthilnathan, K., et al., 2015. A statistical approach to understand the role of inclusions on the fatigue resistance of superelastic Nitinol wire and tubing. J. Mech. Behav. Biomed. Mater. 51, 119
131. Saffari, P., 2012. Best practices for FEA simulation of a stent. In: Paper Presented at the SIMULIA Regional User Meeting 2012. Linz, Austria. Scheinert, D., Scheinert, S., Sax, J., Piorkowski, C., Bra¨unlich, S., Ulrich, M., et al., 2005. Prevalence and clinical impact of stent fractures after femoropopliteal stenting. J. Am. Coll. Cardiol. 45, 312
315. Silva, M., 2002. Average patient walking activity approaches two million cycles per year. J. Arthroplasty 17, 693
697. Simons, J.W., Dalal, A., Shockey, D.A., 2010. Loaddeformation behavior of Nitinol stents. Exp. Mech. 50 (6), 835
843. Suh, G.Y., Les, A.S., Tenforde, A.S., Shadden, S.C., Spilker, R.L., Yeung, J.J., et al., 2011. Quantification of particle

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residence time in abdominal aortic aneurysms using magnetic resonance imaging and computational fluid dynamics. Ann. Biomed. Eng. 39 (2), 864
883. Suh, G.Y., Choi, G., Herfkens, R.J., Dalman, R.L., Cheng, C.P., 2013. Respiration-induced deformations of the superior mesenteric and renal arteries in patients with abdominal aortic aneurysms. J. Vasc. Interv. Radiol. 24 (7), 1035
1042. Suresh, S., 1998. Fatigue of Materials, second ed. Cambridge University Press. Tabanli, R.M., Simha, N.K., Berg, B.T., 1999. Mean stress effects on fatigue of NiTi. Mater. Sci. Eng. A 273-275, 644
648. Tabanli, R.M., Simha, N.K., Berg, B.T., 2001. Mean strain effects on the fatigue properties of superelastic NiTi. Metall. Mater. Trans. A 32 (7), 1866
1869. Thourani, V.H., Kodali, S., Makkar, R.R., Herrmann, H. C., Williams, M., Babaliaros, V., et al., 2016. Transcatheter aortic valve replacement versus surgical valve replacement in intermediate-risk patients: a propensity score analysis. Lancet 387 (10034), 2218
2225. Vietmeier, K., 2015. Understanding the unique properties of Nitinol Porticot transcatheter aortic valve implantation system. Radcliffe Cardiol. 1
3. ¨ ber die Festigkeitsversuche mit Eisen Wo¨hler, A., 1870. U and Stahl. Zeitschrift fu¨r Bauwesen 20, 73
106.

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C H A P T E R

16

Clinical Implications of Vascular Motion K. Ouriel Syntactx LLC, New York, NY, United States

As a nonengineer author, but as a vascular surgeon with hands-on experience with the cardiovascular structures of the human body, this chapter differs from most others in this book. While I have witnessed firsthand the visual and tactile implications of medical device failures over the last four decades, the beauty and simplicity of vascular structures has been astounding. That a large blood vessel such as the aorta, transporting blood from the heart to the viscera and limbs at a rate of many liters per minute, can function for a century without malfunction is truly awe-inspiring. My first exposure to the aorta was as a thirdyear medical student at the University of Chicago in 1979, observing an open surgical aneurysm repair by Dr. Christopher Zarins. The human aorta is a structure that, despite engineering attempts, cannot be reproduced artificially. Eons of evolution have resulted in a biological structure with a level of failure that is far, far below that of even the most advanced medical device. Forget 400 million cycles. This organ functions over 3 billion cycles during a lifetime; every day, throughout the world, in 8 billion individuals, with failure in the form of aneurysms or occlusive disease in only a small

Handbook of Vascular Motion DOI: https://doi.org/10.1016/B978-0-12-815713-8.00016-4

minority of people, and usually because of or at least exacerbated by indiscretions such as smoking, poor eating habits, or a sedentary lifestyle. Consider the ocean liner Titanic. In 1912, this was a new, shiny structure at the pinnacle of nautical architecture and engineering. Picture the deck rails of the ship, something familiar to anyone who has seen the 1997 James Cameron movie (Fig. 16.1). These props are only replicas of the original ship, but compare them to what was discovered by Dr. Robert Ballard in 1985 at the bottom of the North Atlantic, 73 years after it sank; the rails of the ship had deteriorated markedly. Note the corrosive process of metallic failure that occurred despite a lack of pulsatility, musculoskeletal/respiration motion, or other deformations, and at sodium and chlorine compositions like plasma, and a pH of 8.2 (and decreasing yearly from global warming)—only slightly more basic than that of blood. In full disclosure, sea water contains much higher concentrations of chloride than does human blood, and the Titanic sailed one year before the discovery of stainless steel; moreover, the steel used by the Belfast shipbuilders Harland and Wolff was higher in sulfur than

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FIGURE 16.2 Coronary stent fracture classification. FIGURE 16.1 The ship Titanic. Failure of the structure after seven decades beneath the sea (http://news.bbcimg. co.uk/media/images/49200000/jpg/_49200435_titanticbowrailing.jpg). Left panel—Scene from the 1997 film. Right panel—Photograph of the Titanic deck railings. From BBC images.

was customary at the time (https://www.cbc. ca/newsblogs/technology/quirks-quarks-blog/ 2012/04/poor-choice-of-materials-made-titanicmore-vulnerable.html and https://www.capitalsteel.net/news/blog/steel-titanic). So, its metallic structure was more prone to pitting corrosion and more brittle than metals of today. But you get the idea. With these and many other, similar observations in mind, it is not surprising that anything we put in the human body fails over time. Whether it is a coronary stent, an aortic endograft, a transcatheter-placed aortic valve, or a lower extremity arterial stent, eventually, failure will occur.

CLINICAL CONSEQUENCES OF CORONARY STENT FRACTURE As one example, in a study by Biscaglia et al. (2016), stent fracture was detected at the time of implantation of second-generation drug-eluting coronary stents in 115 (13.8%) of 832 patients with physical factors thought to predispose to stent fracture. These factors included overlapping stents, tortuous arteries,

Types I and II stent fractures involve strut fractures where the stent remains in a single contiguous piece. Types III and IV fractures involve a complete transverse fracture of the stent with and without displacement (Kan et al., 2016). From Kan, J., Ge, Z., Zhang, J.J., Liu, Z.Z., Tian, N.L., Ye, F., et al., 2016. Incidence and clinical outcomes of stent fractures on the basis of 6,555 patients and 16,482 drug-eluting stents from 4 centers. JACC Cardiovasc. Interv. 9, 1115 1123, Figure 1.

severe calcification, or bifurcation stents, which represented 43% of the total population of patients undergoing coronary stent placement over the same period. Stent fractures were graded using the classification outlined by Popma et al. (2009). When followed for 9 months postintervention, device-oriented composite endpoint (DOCE) events were statistically more frequent in patients with more severe Type III/IV stent fracture compared to those without fracture or those with less severe Type I/II fracture (Fig. 16.2). At 9 months, DOCE occurred in 13/37 (35%) of patients with Type III/IV stent fracture, compared to 11/78 (14%) of patients with Type I/II fracture and 111/717 (15%) of patients without fracture (P 5 .006) (Fig. 16.3). Definitive stent thromboses were more frequent in those with Type III/IV fracture, occurring in 5/37 patients (14%) compared to 2/78 (3%) of patients with Type I/II fracture and 6/717 (1%) of patients without fracture (P 5 .02). In a multivariable analysis, the 9-month DOCE rate was related to advanced age (P 5 .04), ST-segment myocardial infarction (P 5 .01), and Type III/IV stent fracture at implantation (P 5 .001).

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Cumulative incidence of DOCE (%)

40 NO SF SF I-II SF III-IV

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0

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FIGURE 16.3 Cumulative rate of DOCE events in patients without coronary SF, and with Types I/II and III/ IV fractures detected at the time of stent implantation (Biscaglia et al., 2016). From Biscaglia, S., Tebaldi, M., Tumscitz, C., Pavasini, R., Marchesini, J., Gallo, F., et al., 2016. Prospective identification of stent fracture by enhanced stent visualization system during percutaneous coronary intervention. Circ. J. 81, 82 89.

This example of important, clinically relevant sequelae after drug-eluting stent fracture is not unique to balloon-expandable coronary stents. Failure of other medical devices can also be accompanied by clinical consequences, occasionally with immediate, devastating consequences.

CLINICAL CONSEQUENCES OF LOWER EXTREMITY ARTERY STENT FRACTURE Similarly, not all stent fractures are created equal in the lower extremity arteries. Furthermore, not all stents are equally likely to fracture. In general, greater stent fracture rates were correlated with longer stented segments, stent overlap, more distal location, and stent designs. Higashiura et al. (2009) reported on a large series of patients with iliac stents and found a 5.0% nitinol stent fracture rate. The occurrence

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of fracture correlated with multiple overlapped stents, more distal placement in the external iliac artery (vs common iliac artery), and greater occlusion rate. The location of fracture tended to be at the iliac artery bend location due to hip flexion. The higher fracture rate in the more distal portions of the iliac arteries is contrasted by the very low fracture rates (B1%) reported in the common iliac arteries (Aihara et al., 2014). Interestingly, some have reported that moving more distally into the iliofemoral region, stents crossing the inguinal ligament were not more frequently associated with fracture, at least with self-expanding covered stents (Calligaro et al., 2013). The portion of the peripheral vasculature where the medical community has had the greatest amount of experience relating the impact of stent fractures to clinical sequelae is the femoropopliteal artery. This is due to the extremely mobile environment of femoropopliteal artery causing a high rate of stent fractures (Cheng et al., 2010; Guidoin et al., 2000; Nikanorov et al., 2008), as well as the utilization of a wide variety of stent designs and procedural details that result in a wide range of stent fracture rates and severities (Rits et al., 2008). The published stent fracture rates vary from 0% to 65% and span the range from single strut fracture (Type I) to complete fragmentation and displacement (Type IV). Scheinert et al. (2005) reported that the prevalence of fracture is correlated with longer stented length, increasing number of overlapped stents, and particular stent designs. Furthermore, stent fracture was correlated with the loss of primary patency at 12 months, and severe fractures (Type III or IV) correlated with significantly higher reobstruction as compared to mild fractures (Type I). Upon the review of 11 femoropopliteal stenting studies, Rits et al. (2008) tabulated 193 stent fractures out of 848 limbs treated over an average follow-up time of 15 months, resulting in an overall fracture rate of at least 23% (“at least” because fractures tend to be grossly underreported).

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Interestingly, since lower extremity motion is the cause of iliofemoropopliteal artery deformations, which in turn cause lower extremity arterial stent fractures, it follows that more physical activity would correlate with greater incidence of stent fractures. This is in fact true. In a study of 40 consecutive patients with nitinol stent implanted in their superficial femoral arteries, the strongest independent determinant associated with stent fracture was walking .5000 steps per day (P 5 .0027) (Iida et al., 2006). Vigorous activity was in fact more correlated to stent fracture than long lesion length, multiple overlapped stents, more distal location of stenting, and total chronic occlusion. To take it a step further, there is preliminary evidence suggesting that highly repetitive and/or high-flexion physical activity in patients with femoropopliteal artery stents have a greater incidence of clinical sequelae. A patient treated with a highly flexible nitinol stent with generally low fracture rates (LifeStent, manufactured by Bard and formerly by Edwards Lifesciences) experienced multiple stent fractures that led to restenosis requiring reintervention (Diehm et al., 2009). Also, a patient experienced restenosis and late stent thrombosis associated with a superficial femoral artery stent fracture after a long-distance bicycle tour (Linnemann et al., 2012). On a related note, while a rare phenomenon, elite competitive cyclists can experience performance-limiting iliac artery endofibrosis due to repetitive, highangle flexion of the hip (Peach et al., 2012; Weinberg and Jaff, 2012).

CLINICAL CONSEQUENCES OF EARLY AORTIC ENDOGRAFT FAILURES A particularly complex example of clinical consequences due to vascular mobility came in the treatment of abdominal aortic aneurysms (AAA) with early aortic endografts placed

through transfemoral access with a procedure now known as endovascular aneurysm repair (EVAR). Clinical events culminating in aneurysm rupture and death occurred over medium and long-term follow-up, events due to an underestimation of the hostility within an aortic aneurysm sac. These miscalculations were magnified by a failure to consider the mechanical interactions between the endograft fabric, the metallic stents, and the sutures holding the two together. The story of EVAR is a good one, however, with a reasonably happy ending. AAA occur in approximately 5% of the population (Li et al., 2013). In a study conducted for the US Preventive Services Task Force, the rate of AAA increased to approximately 7% in smokers above age 70 (Fleming et al., 2005). The risk of complications from AAA, principally rupture and death, is related to the size of the aneurysm. While other factors enter into the equation of rupture risk, for example, the shape of the aneurysm, the rate of enlargement of the sac, the patient’s medical comorbidities such as female gender, smoking, and hypertension (diabetes may be protective)—by and large, the diameter of the aneurysm sac has been the factor most closely linked to rupture (Chisci et al., 2018; Collin, 1994; Fillinger et al., 2004; Lindquist Liljeqvist et al., 2017; Ouriel et al., 1992). AAA less than 50 mm in diameter rarely rupture, but the risks increase in larger aneurysms, and the rate increases exponentially above 60 or 70 mm. Prior to the midportion of the 20th century, no definitive treatment for AAA existed. In 1951, however, Dubost et al. (1951) reported the first surgical repair of an aortic aneurysm, using a preserved human cadaveric aortic homograft. Thereafter, open surgical repair became the standard treatment for AAA of sufficient size. Homografts were associated with aneurysmal degeneration over time and were supplanted by synthetic polyester tubes with improved durability as the graft of choice for aortic repair (Fig. 16.4) (Voorhees et al., 1952).

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FIGURE 16.4 Open surgical repair of an abdominal aortic aneurysm. The graft is sutured within the lumen of the aneurysm sac, and the sac is sutured over the graft to protect it from the abdominal contents. From Stanford healthcare.org.

The results of open surgery were, in general, good. The mortality diminished with increased operator technical skills and better grafts. The morbidity of open surgical repair, however, remained significant. Mortality, while approximately 5% overall (Greenhalgh et al., 2004), was much higher in elderly and frail patients (Grant et al., 2011; Schlosser et al., 2010). Noting the high morbidity and mortality of open aneurysm repair in patients with multiple comorbid conditions, the very population that are prone to aneurysms, Dr. Juan Parodi sought to develop a less invasive treatment for AAA. His work began in the 1970s while in fellowship training at the Cleveland Clinic (Parodi and Ferreira, 2000). By the late 1980s, Dr. Parodi had developed a device that used a standard aortic polyester graft affixed with a balloon-expandable stent at the proximal aspect of the graft. The device, constrained within a sheath, could be introduced through a small incision in the groin, and threaded transfemorally, through the iliac arteries, and into

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the aneurysm. After withdrawal of the sheath and expansion of the stents, blood flow was directed through the device, and the aneurysm sac was sealed from pressurized arterial flow. In 1989, Parodi was ready to use his device in humans. On September 6, 1990, Parodi performed the first successful EVAR procedure. Parodi et al. (1991) performed four more cases over the following 8 months and published his initial series in 1991. The technology was rapidly developed by numerous medical device companies. MinTec (Freeport, Grand Bahamas) was one of the first companies to introduce an EVAR device into the marketplace, the Stentor endograft. Stentor incorporated polyester fabric sutured to a nitinol stent framework, delivered through an 18 Fr sheath, remarkably small at that time. EndoVascular Technologies (Menlo Park, CA, Ancure device), Cook Medical (Bloomington, IN, Zenith device), AneuRx (acquired by Medtronic, Santa Rosa, CA), World Medical (Sunrise, FL, Talent device, also acquired by Medtronic), W.L. Gore (Flagstaff, AZ), and others followed suit with their own devices. The early EVAR devices, while studied extensively and with enthusiasm, were fraught with problems. Most notably, the metallic stents fractured, sometimes with devastating consequences from fabric tears, endograft migration, and/or loss of seal. Rupture after repair occurred all too frequently with early devices. Here are a few of the engineering misadventures of 25 years ago, including stent fracture and fabric tears, which can culminate in devastating clinical consequences. As one example, an analysis of failed MinTec Stentor devices was reported in 2000 (Guidoin et al., 2000). Devices from the EUROSTAR registry were explanted for migration, endoleak, limb thrombosis, or aneurysm expansion in five patients. An additional device was obtained at autopsy. The six devices were examined visually, chemically, and with scanning electron microscopy.

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Multiple device malfunctions were observed, including yarn damage with the formation of macroscopic fabric defects (an issue that would come to be described as Type IIIb endoleaks when observed radiographically) and suture breaks with dislocation of the metallic skeleton. Chemical analysis of the nitinol wires revealed nonhomogenous concentrations of titanium and nickel with carbon elements in the superficial layer atop a deeper stratum of oxidized titanium with a low nickel concentration. A subsequent study of 21 explanted Stentor devices confirmed pitting and corrosion of the nitinol wires, precursors of material failure (Heintz et al., 2001). The Stentor device was acquired by Boston Scientific and, with some device modifications, it reappeared as the Vanguard device (Maynar et al., 1998). Early results with Vanguard were acceptable (Lundbom et al., 1999). A 75-patient French Vanguard series with 18-month mean follow-up found a 28% reintervention rate. Most of the secondary procedures were for limb occlusions or stenoses (Becquemin et al., 1999). Longer term reports with the Vanguard device documented more device durability issues (Fig. 16.5). Suture breaks, fabric tears, and stent fractures were observed with unexpectedly high frequencies, and the device was abandoned (Chuter, 2003; Yin et al., 2008; Riepe et al., 2002; Beebe et al., 2001; Jacobs et al., 2003). Device failures were not without clinical consequences. Type IIIb endoleaks, while individually small, are high in pressure due to the direct communication between the arterial lumen and the aneurysm sac. Type IIIb endoleaks, however, are notoriously difficult to diagnose (Fig. 16.5, right panel). Aneurysm enlargement without an obvious endoleak can be followed by surprising findings at surgical exploration (Fig. 16.6). Such device malfunctions, when detected, result in secondary procedures, each with their own morbidity and mortality, even when performed endovascularly (Sampram et al., 2003; Kelso et al., 2009).

FIGURE 16.5 Left panel—fabric tears in the main body of an explanted Vanguard device (Jacobs et al., 2003). Right panel—very small Type IIIb endoleak in the limb of an AneuRx endograft (Medtronic, Santa Rosa, CA), detected with magnified selective angiography of graft limb. From Matsumura, J.S., Ryu, R.K., Ouriel, K., 2001. Identification and implications of transgraft microleaks after endovascular repair of aortic aneurysms. J. Vasc. Surg. 34, 190 197.

FIGURE 16.6 Jets of blood from fabric defects in the main body of an AneuRx endograft at the time of open surgical explantation for sac enlargement. From Ouriel, K., 2002. Image in clinical medicine. Abdominal aortic aneurysm. N. Engl. J. Med. 346, 1467.

When these malfunctions are not detected, the problem can result in aneurysm rupture and death of the patient (Schlosser et al., 2009). As is often the case with new technology, a phase of irrational exuberance is followed by cautious constraint. Even today, at a time

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NEW ENDOGRAFTS: ARE WE RELIVING PAST PROBLEMS?

when AAA are treated with endovascular technology in most patients (Dua et al., 2014), some continue to argue for open surgical repair as a first choice in patients who can tolerate the operation. The draft guidance of the National Institute for Health and Care Excellence (NICE) (2018) in the United Kingdom recommends that patients with AAA should not be offered EVAR if open surgical repair can be tolerated. Whether this draft guidance will change practice, or even be incorporated into the final guidance, remains to be seen.

NEW ENDOGRAFTS: ARE WE RELIVING PAST PROBLEMS? One of the drawbacks of initial EVAR technology was the diameter of the delivery systems, initially 8 mm in outer diameter and subsequently reduced to 6 mm or even smaller with later generation devices. For whatever reason, possibly due to compromises made in the quest to reduce delivery system profiles, or possibly an artifact of better postoperative imaging technology, an increase in stent facture rate has reappeared. At the 2017 Greenberg Stent Summit, the Medtronic engineering team presented a high frequency of Endurant EVO stent fractures that was responsible for the company deciding not to commercialize the device. The stent fractures were a result of unexpected tensile stresses on the intradose of stent strut apices due to oversizing the stent components in relation to the graft. Further, Cordis presented a series of 38 stent fractures in 19/190 subjects (10.0%) enrolled in the INSPIRATION pivotal clinical trial of the INCRAFT device. The fractures occurred through full 4-year and partial 5-year follow-up. Each of the fractures in the INSPIRATION trial was in the bare transrenal stent, and all have been asymptomatic, at least thus far. Cordis (2018) did a thorough investigation of the fractures, and the following was reported in

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the Executive Summary supplied to the FDA Panel (verbatim transcript, edited for length and style). The top-line summary of their analysis was that stent fractures occurred in 10% of the patients through 4 5-year follow-up, but all fractures were located within the bare suprarenal stent, and none were associated with clinical sequelae. The details are as follows: • None of the 19 patients with fractures experienced any clinical consequences as a result of fracture. There were no main body (aortic bifurcate) migrations, Type Ia endoleaks, vessel perforations, aneurysm sac enlargements, sac ruptures, or strut embolizations in patients with fracture. • A root cause analysis concluded that the primary cause of fracture was cardiacinduced cyclic axial deformation. This was supported by more recent findings in scientific literature related to biomechanics of the transrenal aorta and computational and bench studies that reproduced the stent strut fractures observed in the clinic under cyclic axial deformations. • Potential clinical consequences of transrenal stent strut fracture were identified and evaluated: (1) device migration due to the loss of fixation, (2) Type Ia endoleak due to inadequate sealing, (3) strut embolization due to multiple fractures, (4) arterial perforations, (5) increased nickel release due to fractured strut ends, and (6) pitting corrosion at fractured strut ends. From the results of this investigation, Cordis concluded that the risk of clinical consequences due to transrenal stent strut fractures was acceptable, based on the following findings: • The clinical outcomes through 4 years in the INSPIRATION study did not show any of the above-listed six potential consequences as attributable to stent strut fracture. • No clinical consequences were associated with stent strut fractures in the

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•

•

•

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INNOVATION study (60-subject European CE-Mark study) through 5 years, or to date in the INSIGHT study (150-subject European postmarket clinical follow-up study) through 1 year. A total of 6638 INCRAFT devices were distributed globally through March 2018. This worldwide commercial experience has not indicated a safety risk for any of the six identified potential consequences noted above. There have been two reports of stent strut fractures. Acute and chronic bench testing with as many as 10 transrenal stent strut fractures did not compromise resistance to migration to the extent that clinical migration would be anticipated. Bench testing with up to 14 strut fractures indicated adequate sealing (resistance to Type I endoleaks). The probability of 11 fractures occurring over 10 years, derived from a combination of computational modeling, bench testing, scientific literature, and statistical analysis, was estimated to be less than 0.15%. This probability of fracture propagation across the device lifetime possibly leading to an event was estimated to be less than this level, considering neointimal growth and embedded struts. Bench testing on intact and fractured stents met acceptance criteria and demonstrated that fractured strut surfaces resulted in minimal risk for susceptibility to in vivo corrosion, and a negligible increase in nickel ion release.

Other elements of risk mitigation were noted as follows: • All stent strut fractures with INCRAFT have occurred at the transrenal stent and away from the aneurysm sac, indicating a low possibility of directly pressurizing the aneurysm sac. The transrenal stent is a bare stent (without graft) and therefore poses negligible risk of breaching the graft

material and creating a Type III endoleak. • While nonclinical evaluations have demonstrated a low risk of device migration and Type I endoleak due to fracture, neointimal growth on the transrenal stent further mitigates the risk of these events in vivo. So, it appears that stent fracture is an ongoing concern even for next-generation aortic endograft designs. In both the Medtronic Endurant EVO and Cordis INCRAFT cases, the quest for lower delivery profiles can be implicated as potential fatigue compromises; however, it is also known that improved imaging technology increases fracture detection rate. Thus the industry is reliving past problems, not necessarily because the occurrence of fractures is increasing, but rather that they have been there all along, and we now have better tools to detect them.

POSTIMPLANTATION SURVEILLANCE FOR DEVICE FAILURE During a pivotal clinical trial for regulatory approval, testing, usually in the form of imaging studies, is necessary to identify known and unknown risks of the device. Postapproval studies (PAS) may also be necessary to gather additional data on a larger number of patients that more closely resemble the real-world population where the device will be used. Nonroutine imaging studies may also be required in the PAS if the pivotal study was in any way insufficient in gauging the frequency and risks of device failure. Real-world surveillance, however, may differ markedly from that employed in the initial clinical investigations. When clinical trials identify a very low rate of an event, or when the consequences of that event are nil,

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surveillance is not indicated. A mentor once said, “if a test will not change your management of a patient, do not order it.” This caveat rings true for medical device failure. For instance, certain failures categorically occur without any clinical sequelae. Imaging surveillance for the failure is superfluous in these cases. If the clinical consequences of the failure are minimal, surveilling for the event will not change the patient’s clinical management. Further, imaging studies may be harmful. At the very least, diagnostic tests such as computed tomography (CT) are expensive. At their worst, they expose patients to ionizing radiation which, with repeated testing over the lifetime of the patient, results in an increased risk of cancer (Jones et al., 2010).

Example of Endovascular Aneurysm Repair The choice of a specific type of surveillance test is also made based upon a benefit risk assessment. If failures can be identified and characterized with a less invasive test, that test should be used preferentially. An example is Bmode ultrasound after EVAR. If all remediable device failures (e.g., endograft migration or loss of seal) culminate in aneurysm sac enlargement, and if ultrasound can reliably detect aneurysm sac dimensional changes over time, ultrasound is a valuable surveillance test. However, aneurysms can rupture without any change in size. If an aneurysm is already 60 or 70 mm in diameter, it can rupture without increasing to 70 or 80 mm in diameter. Thus size alone is insufficient for surveillance of an aneurysm. An appropriate post-EVAR surveillance test would also need to detect high-pressure endoleaks from the loss of seal at the proximal or distal attachment sites (Types Ia and Ib), between endograft components (Type IIIa), or through the fabric (Type IIIb). For this reason, while B-mode ultrasound alone is not a good

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FIGURE 16.7 A Type II endoleak originating from a lumbar artery, detected by color duplex ultrasonography. From Chaikof, E.L., Dalman, R.L., Eskandari, M.K., Jackson, B. M., Lee, W.A., Mansour M.A., et al., 2018. The Society for Vascular Surgery practice guidelines on the care of patients with an abdominal aortic aneurysm. J. Vasc. Surg. 67, 2 77.e2.

surveillance test, the addition of color Doppler to the ultrasound image, a test known as “color duplex ultrasound,” adds to the power of postEVAR surveillance. Endoleaks can be visualized with color Doppler (Fig. 16.7), as can problems within the graft limbs. The 2018 Society for Vascular Surgery practice guidelines on the care of patients with aortic aneurysms recognizes the benefits of color duplex over radiation-based CT for the long-term follow-up after aneurysm repair (Chaikof et al., 2018). The guidelines recommend consideration of color duplex ultrasound as a routine surveillance test in patients who have no endoleak and no sac enlargement on 1-year noncontrast/contrast CT scans.

Example of Percutaneous Coronary Intervention In contrast to surveillance after EVAR, consider the example of restenosis after percutaneous coronary intervention (PCI) with stents. Unlike larger, superficially located arterial

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FIGURE 16.8 Results of the ReACT trial. While the use of routine coronary angiography after PCI resulted in more reinterventions during the first year (left pane), this did not translate into clinical benefit (right pane). From Shiomi, H., Morimoto, T., Kitaguchi, S., Nakagawa, Y., Ishii, K., Haruna, Y., et al., 2017. The ReACT trial: Randomized Evaluation of Routine Follow-up Coronary Angiography After Percutaneous Coronary Intervention trial. JACC Cardiovasc. Interv. 10, 109 117.

reconstructions, coronary stents are difficult to interrogate for in-stent restenosis (ISR). While it is easy to perform a color duplex assessment of a carotid stent or a superficial femoral artery drug-coated balloon angioplasty, evaluation of a coronary stent requires semi-invasive coronary angiography. Two questions arise for the surveillance of patients with coronary stents. First, how invasive are the procedures required to identify ISR? Second, once identified, should asymptomatic ISR be treated? Initially, coronary angiography was used routinely after PCI. Absent robust data, postintervention angiography was abandoned and is not recommended in the United States and European societal PCI guidelines (Neumann et al., 2019; Levine et al., 2011; Kolh and Windecker, 2014). The practice of post-PCI angiography, however, remained an important aspect of interventional practice in Japan (Puri et al., 2017). One thing was clear: Routine postPCI coronary angiography detected more asymptomatic ISR and resulted in more reinterventions. What remained undefined was the risk of angiography (likely small) and, more importantly, the clinical benefit (or harm) of treating asymptomatic ISR.

The use of post-PCI angiography was addressed with the recent ReACT trial. This Japanese trial was performed in 22 centers and enrolled 700 subjects randomly assigned to routine follow-up with coronary angiography 8 12 months after PCI (n 5 349), or to clinical follow-up alone (n 5 351). Repeat PCI was performed more frequently during the first year in the routine follow-up angiography group than in the clinical follow-up arm, 12.8% versus 3.8%, respectively (P , .001, Fig. 16.8). However, the primary endpoint of death, myocardial infarction, acute coronary syndrome, or hospitalization for heart failure occurred at similar frequencies in the two groups, 22.4% in the routine follow-up angiography group versus 24.7% in the clinical follow-up group (P 5 .70). The authors concluded that routine coronary angiography after PCI was of no clinical benefit. Whether this trial will result in practice changes in Japan remains to be seen.

Conclusions on Surveillance Testing for Device Failure Like most questions in medicine, the answer to whether routine surveillance is necessary

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after device implantation is both yes and no. Yes, for patients who undergo implantation of a medical device as part of an initial clinical investigation. Surveillance is needed to identify the frequency and consequences of device failures, information unknown at the outset. But no, surveillance is not indicated for patients treated with a device where the frequency of a given failure is low, or the consequences of failure are trivial.

CONCLUSION Treatment decisions begin well before a device is ever implanted. Device durability has always played an important role in this regard. As one example, the indications for EVAR early in the evolution of endograft technology are completely different from today. In the 1990s, incomplete information on long-term endograft durability created hesitancy to use the technology in younger patients with longlife expectancy. The information that was available suggested that durability was poor, compounding the reticence to employ EVAR in patients who could otherwise withstand an open surgical procedure. Fast-forward two decades. We now have information to suggest that the durability of modern, marketed endovascular grafts is excellent. Device deficiency issues still occur, including limb occlusion, late endoleak, endograft migration, stent fracture, fabric tears, limb disunion, etc. However, the rate of these events is much lower than with antecedent technologies. Further, redundancies engineered into the design of current devices provide a greater margin of safety. If one component of a device malfunctions, redundant features may prevent immediate, devastating clinical consequences. These improvements underlie the observation that patients undergoing aneurysm repair are treated with EVAR in most cases today. Open surgical procedures are now

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relegated, for the most part, to patients with anatomic contraindications to EVAR. The coronary artery, lower extremity artery, and abdominal aortic examples presented herein illustrate concepts that underlie how clinical decision-making must address medical device durability issues to arrive at the best care for patients. First, the clinician needs to recognize the limitations of the devices under consideration for each patient so that an appropriate device can be chosen. Second, known limitations should guide the use of appropriate postimplant testing to identify failure, in particular if the failure might be associated with adverse clinical consequences. Lastly, when failures are identified, they should be addressed in a timely manner, before the failure adversely or irreversibly affects the health and welfare of the patient.

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patients with an abdominal aortic aneurysm. J. Vasc. Surg. 67, 2 77.e2. Cheng, C.P., Choi, G., Herfkens, R.J., Taylor, C.A., 2010. The effect of aging on deformations of the superficial femoral artery resulting from hip and knee flexion: potential clinical implications. J. Vasc. Interv. Radiol. 21, 195 202. Chisci, E., Alamanni, N., Iacoponi, F., Michelagnoli, S., Procacci, T., Colombo, G., et al., 2018. Grading abdominal aortic aneurysm rupture risk. J. Cardiovasc. Surg. (Torino) 59, 87 94. Chuter, T.A., 2003. The choice of stent-graft for endovascular repair of abdominal aortic aneurysm. J. Cardiovasc. Surg. (Torino) 44, 519 525. Collin, J., 1994. Risk of rupture in abdominal aortic aneurysm. Lancet 343, 539. Cordis, 2018. INCRAFT AAA Stent Graft System, Final Executive Summary, Circulatory System Devices Panel. A Cardinal Heath company, Milpitas, CA. Diehm, N., Schumacher, A., Luthi, R., Kalka, C., Baumgartner, I., Do, D.D., 2009. Fracture of a highly flexible nitinol stent after repeated bending of the knee joint during vigorous exercise. J. Vasc. Interv. Radiol. 20, 987 988. Dua, A., Upchurch Jr., G.R., Lee, J.T., Eidt, J., Desai, S.S., 2014. Predicted shortfall in open aneurysm experience for vascular surgery trainees. J. Vasc. Surg. 60, 945 949. Dubost, C., Allary, M., Oeconomos, 1951. Aneurysm of the abdominal aorta treated by resection and graft. Arch. Mal. Coeur. Vaiss. 44, 848 851. Fillinger, M.F., Racusin, J., Baker, R.K., Cronenwett, J.L., Teutelink, A., Schermerhorn, M.L., et al., 2004. Anatomic characteristics of ruptured abdominal aortic aneurysm on conventional CT scans: implications for rupture risk. J. Vasc. Surg. 39, 1243 1252. Fleming, C., Whitlock, E.P., Beil, T.L., Lederle, F.A., 2005. Screening for abdominal aortic aneurysm: a bestevidence systematic review for the U.S. Preventive Services Task Force. Ann. Intern. Med. 142, 203 211. Grant, S.W., Grayson, A.D., Purkayastha, D., Wilson, S.D., McCollum, C., Programme Participants in the Vascular Governance North West, 2011. Logistic risk model for mortality following elective abdominal aortic aneurysm repair. Br. J. Surg. 98, 652 658. Greenhalgh, R.M., Brown, L.C., Kwong, G.P., Powell, J.T., Thompson, S.G., EVAR trial participants, 2004. Comparison of endovascular aneurysm repair with open repair in patients with abdominal aortic aneurysm (EVAR trial 1), 30-day operative mortality results: randomised controlled trial. Lancet 364, 843 848. Guidoin, R., Marois, Y., Douville, Y., King, M.W., Castonguay, M., Traore, A., et al., 2000. First-generation aortic endografts: analysis of explanted Stentor devices

from the EUROSTAR Registry. J. Endovasc. Ther. 7, 105 122. Heintz, C., Riepe, G., Birken, L., Kaiser, E., Chakfe, N., Morlock, M., et al., 2001. Corroded nitinol wires in explanted aortic endografts: an important mechanism of failure? J. Endovasc. Ther. 8, 248 253. Higashiura, W., Kubota, Y., Sakaguchi, S., Kurumatani, N., Nakamae, M., Nishimine, K., et al., 2009. Prevalence, factors, and clinical impact of self-expanding stent fractures following iliac artery stenting. J. Vasc. Surg. 49, 645 652. Iida, O., Nanto, S., Uematsu, M., Morozumi, T., Kotani, J., Awata, M., et al., 2006. Effect of exercise on frequency of stent fracture in the superficial femoral artery. Am. J. Cardiol. 98, 272 274. Jacobs, T.S., Won, J., Gravereaux, E.C., Faries, P.L., Morrissey, N., Teodorescu, V.J., et al., 2003. Mechanical failure of prosthetic human implants: a 10-year experience with aortic stent graft devices. J. Vasc. Surg. 37, 16 26. Jones, C., Badger, S.A., Boyd, C.S., Soong, C.V., 2010. The impact of radiation dose exposure during endovascular aneurysm repair on patient safety. J. Vasc. Surg. 52, 298 302. Kan, J., Ge, Z., Zhang, J.J., Liu, Z.Z., Tian, N.L., Ye, F., et al., 2016. Incidence and clinical outcomes of stent fractures on the basis of 6,555 patients and 16,482 drugeluting stents from 4 centers. JACC Cardiovasc. Interv. 9, 1115 1123. Kelso, R.L., Lyden, S.P., Butler, B., Greenberg, R.K., Eagleton, M.J., Clair, D.G., 2009. Late conversion of aortic stent grafts. J. Vasc. Surg. 49, 589 595. Kolh, P., Windecker, S., 2014. ESC/EACTS myocardial revascularization guidelines 2014. Eur. Heart J. 35, 3235 3236. Levine, G.N., Bates, E.R., Blankenship, J.C., Bailey, S.R., Bittl, J.A., Cercek, B., et al., 2011. 2011 ACCF/AHA/ SCAI guideline for percutaneous coronary intervention. A report of the American College of Cardiology Foundation/American Heart Association Task Force on practice guidelines and the Society for Cardiovascular Angiography and Interventions. J. Am. Coll. Cardiol. 58, e44 e122. Li, X., Zhao, G., Zhang, J., Duan, Z., Xin, S., 2013. Prevalence and trends of the abdominal aortic aneurysms epidemic in general population—a meta-analysis. PLoS One 8, e81260. Lindquist Liljeqvist, M., Hultgren, R., Siika, A., Gasser, T. C., Roy, J., 2017. Gender, smoking, body size, and aneurysm geometry influence the biomechanical rupture risk of abdominal aortic aneurysms as estimated by finite element analysis. J. Vasc. Surg. 65, 1014 1021.e4.

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Linnemann, B., Thalhammer, A., Wolf, Z., Tirneci, V., Vogl, T.J., Edelgard Lindhoff-Last, A., 2012. Late peripheral stent thrombosis due to stent fracture, vigorous exercise and hyporesponsiveness to clopidogrel. Vasa 41, 136 144. Lundbom, J., Hatlinghus, S., Wirsching, J., Amundsen, S., Staxrud, L.E., GjLlberg, T., et al., 1999. Endovascular treatment of abdominal aortic aneurysms in Norway: the first 100 patients. Eur. J. Vasc. Endovasc. Surg. 18, 506 509. Matsumura, J.S., Ryu, R.K., Ouriel, K., 2001. Identification and implications of transgraft microleaks after endovascular repair of aortic aneurysms. J. Vasc. Surg. 34, 190 197. Maynar, M., de Blas, M., Reyes, R., Egana, J.M., Carreira, J. M., Pulido-Duque, J.M., et al., 1998. Endovascular treatment of abdominal aorta aneurysms using bifurcated endoprosthesis. Rev. Clin. Esp. 198, 200 206. Neumann, F.J., Sousa-Uva, M., Ahlsson, A., Alfonso, F., Banning, A.P., Benedetto, U., et al., 2019. 2018 ESC/ EACTS guidelines on myocardial revascularization. Eur. Heart J. 40 (2), 87 165. National Institute for Health and Care Excellence (NICE), 2018. Endovascular aneurysm sealing for abdominal aortic aneurysm. Interventional Procedures Guidance [IPG547]. National Institute for Health and Care Excellence. Nikanorov, A., Smouse, H.B., Osman, K., Bialas, M., Shrivastava, S., Schwartz, L.B., 2008. Fracture of selfexpanding nitinol stents stressed in vitro under simulated intravascular conditions. J. Vasc. Surg. 48, 435 440. Ouriel, K., 2002. Image in clinical medicine. Abdominal aortic aneurysm. N. Engl. J. Med. 346, 1467. Ouriel, K., Green, R.M., Donayre, C., Shortell, C.K., Elliott, J., DeWeese, J.A., 1992. An evaluation of new methods of expressing aortic aneurysm size: relationship to rupture. J. Vasc. Surg. 15, 12 18. Discussion 19-20. Parodi, J.C., Ferreira, M., 2000. Historical prologue: why endovascular abdominal aortic aneurysm repair? Semin. Interv. Cardiol. 5, 3 6. Parodi, J.C., Palmaz, J.C., Barone, H.D., 1991. Transfemoral intraluminal graft implantation for abdominal aortic aneurysms. Ann. Vasc. Surg. 5, 491 499. Peach, G., Schep, G., Palfreeman, R., Beard, J.D., Thompson, M.M., Hinchliffe, R.J., 2012. Endofibrosis and kinking of the iliac arteries in athletes: a systematic review. Eur. J. Vasc. Endovasc. Surg. 43, 208 217. Popma, J.J., Tiroch, K., Almonacid, A., Cohen, S., Kandzari, D.E., Leon, M.B., 2009. A qualitative and quantitative

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angiographic analysis of stent fracture late following sirolimus-eluting stent implantation. Am. J. Cardiol. 103, 923 929. Puri, R., de la Torre Hernandez, J.M., Auffret, V., 2017. Routine surveillance coronary angiography post-PCI: should we ReACT and change our routine? JACC Cardiovasc. Interv. 10, 118 120. Riepe, G., Heintz, C., Kaiser, E., Chakfe, N., Morlock, M., Delling, M., et al., 2002. What can we learn from explanted endovascular devices? Eur. J. Vasc. Endovasc. Surg. 24, 117 122. Rits, J., van Herwaarden, J.A., Jahrome, A.K., Krievins, D., Moll, F.L., 2008. The incidence of arterial stent fractures with exclusion of coronary, aortic, and non-arterial settings. Eur. J. Vasc. Endovasc. Surg. 36, 339 345. Sampram, E.S., Karafa, M.T., Mascha, E.J., Clair, D.G., Greenberg, R.K., Lyden, S.P., et al., 2003. Nature, frequency, and predictors of secondary procedures after endovascular repair of abdominal aortic aneurysm. J. Vasc. Surg. 37, 930 937. Scheinert, D., Scheinert, S., Sax, J., Piorkowski, C., Braunlich, S., Ulrich, M., et al., 2005. Prevalence and clinical impact of stent fractures after femoropopliteal stenting. J. Am. Coll. Cardiol. 45, 312 315. Schlosser, F.J., Gusberg, R.J., Dardik, A., Lin, P.H., Verhagen, H.J., Moll, F.L., et al., 2009. Aneurysm rupture after EVAR: can the ultimate failure be predicted? Eur. J. Vasc. Endovasc. Surg. 37, 15 22. Schlosser, F.J., Vaartjes, I., van der Heijden, G.J., Moll, F.L., Verhagen, H.J., Muhs, B.E., et al., 2010. Mortality after elective abdominal aortic aneurysm repair. Ann. Surg. 251, 158 164. Shiomi, H., Morimoto, T., Kitaguchi, S., Nakagawa, Y., Ishii, K., Haruna, Y., et al., 2017. The ReACT trial: Randomized Evaluation of Routine Follow-up Coronary Angiography After Percutaneous Coronary Intervention trial. JACC Cardiovasc. Interv. 10, 109 117. Voorhees Jr., A.B., Jaretzki 3rd, A., Blakemore, A.H., 1952. The use of tubes constructed from vinyon “N” cloth in bridging arterial defects. Ann. Surg. 135, 332 336. Weinberg, I., Jaff, M.R., 2012. Nonatherosclerotic arterial disorders of the lower extremities. Circulation 126, 213 222. Yin, T., Guidoin, R., Corriveau, M.M., Nutley, M., Xu, L., Marinov, G.R., et al., 2008. Specific shortcomings of endograft design. J. Long Term Eff. Med. Implants 18, 181 204.

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Product Development and Business Implications C. Myers1, B. Wolf1, M. Nilson2, A. Byrne2, S. Rush3, J. Elkins4, A. Ragheb5, B. Roeder5, R. Swift5, J. Metcalf 5, T. Duerig6 and Christopher P. Cheng7 1

Medtronic, Dublin, Ireland 2W.L. Gore & Associates, Newark, DE, United States 3Terumo Corporation, Tokyo, Japan 4Serial Entrepreneur and Corporate Executive 5Cook Group, Bloomington, IN, United States 6Confluent Medical Technologies, Fremont, CA, United States 7Division of Vascular Surgery, Stanford University, Stanford, CA, United States

Developing appropriate mechanical boundary conditions is critical for designing and evaluating vascular implants for safety, efficacy, and regulatory approval. However, the author acknowledges that investing in this activity at the beginning of the product development process may feel sluggish, delaying the engineering team from getting to the “good stuff.” But the boundary conditions are the good stuff, or at least a lack of attention to the boundary conditions can lead to bad stuff. Really bad stuff! It is better to take your time and invest in figuring out the dynamic vascular anatomy

Handbook of Vascular Motion DOI: https://doi.org/10.1016/B978-0-12-815713-8.00017-6

during the early portion of product development than to discover it too late. Device designs can be changed with relatively low costs and short delays early on, while the required resources to make these changes increase exponentially as the team crosses into design freeze and clinical trial territory. Worse, if mistakes are discovered at the end of a pivotal trial, the associated costs or delays to fix the issue may convince a business to cancel the product altogether. Worst of all, a mistake could lead to patient safety issues. But don’t take my word for it. Here are six stories from

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medical device industry veterans focusing on the product development and business implications of understanding vascular motion boundary conditions.

THE ENDURANT EVO EXPERIENCE Craig Myers, Ben Wolf

So Close Using state-of-the-art fatigue and durability test equipment, along with an increased focus on advanced imaging modalities to understand the complex in vivo environment, Medtronic had tested the Endurant Evo AAA Stent Graft System thoroughly and ensured it would perform as expected in clinical use. After nearly 10 years of development effort, including a clinical trial and incorporated learning from the previous generati