Tissue Elasticity Imaging: Volume 1: Theory and Methods

Tissue Elasticity Imaging: Volume One: Theory and Methods offers an extensive treatment of the fundamentals and applications of this groundbreaking diagnostic modality. The book introduces elasticity imaging, its history, the fundamental physics, and the different elasticity imaging methods, along with their implementation details, problems and artefacts. It is an essential resource for all researchers and practitioners interested in any elasticity imaging modality. As many diseases, including cancers, alter tissue mechanical properties, it is not always possible for conventional methods to detect changes, but with elasticity images that are produced by slow tissue deformation or low-frequency vibration, these changes can be displayed.

• Offers the first comprehensive reference on elasticity imaging
• Discusses the fundamentals of technology and their limitations and solutions, along with advanced methods and future directions
• Addresses the technologies and applications useful to both researchers and clinical practitioners
• Includes an online reference section regularly updated with advances in technology and applications

• Language: English
• Publisher: Elsevier Science
• Release date: Nov 22, 2019
• ISBN: 9780128096833

Book preview

Tissue Elasticity Imaging

Volume 1: Theory and Methods

Edited by

S. Kaisar Alam

Imagine Consulting LLC, Dayton, NJ, United States, The Center for Computational Biomedicine Imaging and Modeling (CBIM), Rutgers University, Piscataway, NJ, United States

Brian S. Garra

Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices, and Radiological Health, FDA, Silver Spring, MD, United States

Table of Contents

Cover image

Title page

Copyright

Contributors

About the editors

Foreword

Preface

Acknowledgments

Chapter 1. An early history of elasticity imaging

1. Overview and personal observations from a radiologist

2. Early history of tissue elasticity determination

3. The early era of imaging tissue stiffness (late 1980s to mid-1990s)

4. Quantitative tissue stiffness determination and imaging (1990 to present)

5. Conclusion/discussion

Chapter 2. The governing theory of elasticity imaging

1. Introduction

2. Displacement and strain

3. Forces, stress, and equilibrium equation

4. Stress-strain relation for an elastic material and elastic constants

5. Equilibrium equations

6. Cylindrical and spherical coordinate systems

7. Basic solutions

8. Dynamic deformation

9. Examples of dynamic problems

10. Viscoelastic models

11. Dynamic deformation of a viscoelastic medium

12. Summary

Chapter 3. Vibration sonoelastography

1. Early results

2. Theory

3. Vibration phase gradient sonoelastography

4. Crawling waves

5. Clinical results

6. Reverberant shear wave fields

7. Conclusion

Chapter 4. Introduction to quasi-static elastography

1. Introduction and background

2. Deformation application and measurement

3. Interpretation of the measured deformation

4. Beyond linear elastic imaging: biomechanical imaging

5. Summary

Chapter 5. Acoustic radiation force and shear wave elastography techniques

1. Introduction

2. Physical basis for acoustic radiation force from ultrasonography

3. Acoustic radiation force imaging techniques

4. Shear wave elastography techniques

Chapter 6. Magnetic resonance elastography

1. Introduction

2. Acquisition

3. Inversions

4. Applications

5. Artifacts and quality control

6. Summary and conclusions

Chapter 7. Reconstructive elastography

1. Introduction

2. Solving the forward elasticity problem

3. Solving the inverse elastography problem

4. Advanced reconstruction methods

5. Discussion

Chapter 8. Lateral and shear strain imaging for ultrasound elastography

1. Introduction

2. Classification of lateral and shear strain estimation methods

3. One-dimensional deformation tracking and estimation

4. Two-dimensional deformation tracking and estimation

5. Clinical applications of lateral and shear strain estimation

6. Conclusion

Chapter 9. Optical elastography on the microscale

1. Introduction

2. Optical coherence elastography

3. Brillouin microscopy

4. Other techniques

5. Outlook

Index

Copyright

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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.

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A catalogue record for this book is available from the British Library

ISBN: 978-0-12-809661-1

For information on all Elsevier publications visit our website at https://www.elsevier.com/books-and-journals

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Acquisition Editor: Anita Koch

Editorial Project Manager: Lindsay Lawrence

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Contributors

Salavat R. Aglyamov,     Department of Mechanical Engineering, University of Houston, Houston, TX, United States

Paul E. Barbone,     Department of Mechanical Engineering, Boston University, Boston, MA, United States

Jeremy J. Dahl,     Department of Radiology, Stanford University, Stanford, CA, United States

Marvin M. Doyley,     Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, United States

Bogdan Dzyubak,     Department of Medical Physics, Mayo Clinic, Rochester, MN, United States

Kevin J. Glaser,     Medical Physics, Mayo Clinic, Rochester, MN, United States

Timothy J. Hall,     Department of Medical Physics, University of Wisconsin, Madison, WI, United States

Carl D. Herickhoff,     Department of Radiology, Stanford University, Stanford, CA, United States

Brendan F. Kennedy

BRITElab, Harry Perkins Institute of Medical Research, QEII Medical Centre, Nedlands, WA, Australia

Department of Electrical, Electronic and Computer Engineering, School of Engineering, The University of Western Australia, Perth, WA, Australia

Robert M. Lerner

Department of Clinical Imaging, University of Rochester, Rochester, NY, United States

Department of Diagnostic Imaging, Rochester General Hospital, Rochester Regional Health, Rochester, NY, United States

Assad A. Oberai,     Department of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, CA, United States

Kevin J. Parker

William F. May Professor of Engineering, Professor of Electrical and Computer Engineering, of Biomedical Engineering, and of Imaging Sciences (Radiology), University of Rochester, Rochester, NY, United States

Dean Emeritus, School of Engineering & Applied Sciences, University of Rochester, Rochester, NY, United States

David D. Sampson

Optical+Biomedical Engineering Laboratory, Department of Electrical, Electronic and Computer Engineering, The University of Western Australia, Perth, WA, Australia

University of Surrey, Surrey, United Kingdom

Arsenii V. Telichko,     Department of Radiology, Stanford University, Stanford, CA, United States

Tomy Varghese,     Department of Medical Physics University of Wisconsin School of Medicine and Public Health University of Wisconsin–Madison, Madison, WI, United States

Philip Wijesinghe

Optical+Biomedical Engineering Laboratory, Department of Electrical, Electronic and Computer Engineering, The University of Western Australia, Perth, WA, Australia

BRITElab, Harry Perkins Institute of Medical Research, QEII Medical Centre, Nedlands, WA, Australia

About the editors

S. Kaisar Alam, Ph.D.

President and Chief Engineer, Imagine Consulting LLC, Dayton, NJ, United States

Visiting Research Faculty, Center for Computational Biomedicine Imaging and Modeling (CBIM), Rutgers University, Piscataway, NJ, United States

Adjunct Faculty, Electrical & Computer Engineering, The College of New Jersey (TCNJ), Ewing, NJ, United States

Dr. S. Kaisar Alam received his B.Tech (Honors) from IIT, Kharagpur, India. Following a 3-year stint as a Lecturer at RUET, Bangladesh, he came to the University of Rochester, Rochester, New York, for graduate studies and received his M.S. and Ph.D. degrees in electrical engineering in 1991 and 1996, respectively. After spending 3   years (1995–1998) as a postdoctoral fellow at the University of Texas Health Science Center, Houston, Dr. Alam was a Principal Investigator at Riverside Research, New York, from 1998 to 2013, working on a variety of research topics in biomedical imaging. He was the Chief Research Officer at Improlabs Pte Ltd, an upcoming tech startup in Singapore until 2017. Then he founded his own consulting company for biomedical image analysis, signal processing, and medical imaging. He has also been involved in training and mentoring high school students. He has been a visiting research professor at CBIM, Rutgers University, Piscataway, New Jersey (since 2013), a visiting professor at IUT, Gazipur, Bangladesh (2010 and 2012), and an adjunct faculty at The College of New Jersey (TCNJ), Ewing, New Jersey (since 2017).

Dr. Alam has been active in research for more than 30   years. His research interests include diagnostic and therapeutic applications of ultrasound and optics, and signal/image processing with applications to medical imaging. The areas of his most active research include elasticity imaging and quantitative ultrasound; he is among a few researchers with experience in both quasistatic and dynamic elasticity imaging. Dr. Alam has written over 40 papers in international journals and holds several patents. He is a coauthor of the textbook Computational Health Informatics (to be published late 2019 or early 2020 by CRC Press). He is a Fellow of AIUM, a Senior Member of IEEE, and a Member of Sigma Xi, AAPM, ASA, and SPIE. Dr. Alam has served in the AIUM Technical Standards Committee and the Ultrasound Coordinating Committee of the RSNA Quantitative Imaging Biomarker Alliance (QIBA). He is an Associate Editor of Ultrasonics (Elsevier) and Ultrasonic Imaging (Sage). Dr. Alam was a recipient of the prestigious Fulbright Scholar Award in 2011–2012.

Brian S. Garra, M.D.

Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, FDA, Silver Spring, MD, United States

Dr. Brian S. Garra completed his residency training at the University of Utah and spent 3   years as an Army radiologist in Germany before returning to Washington DC and the National Institutes of Health in the mid 1980s. After 4   years at the NIH, he joined the faculty of Georgetown University as Director of Ultrasound. In 1998, he left Georgetown to become Professor & Vice Chairman of Radiology at the University of Vermont/Fletcher Allen Healthcare. In 2009, Dr. Garra returned to the Washington DC area as Chief of Imaging Systems & Research in Radiology at the Washington DC Veterans Affairs Medical Center. In April 2010, he also joined the FDA as an Associate Director in the Division of Imaging and Applied Mathematics/OSEL. In 2018, he left the VA and currently splits his time between the FDA and private practice radiology in Florida.

Dr. Garra's clinical activities include spinal MRI and general ultrasound. His research interests include PACS, digital signal processing, and quantitative ultrasound including Doppler, ultrasound elastography, and photoacoustic tomography. He was chair of the FDA radiological Devices Panel from 1999 to 2002 and has been involved in the approval of several new technologies including high resolution breast ultrasound, the first digital mammographic system, the first computer-aided detection system for mammography, and the first computer-aided nodule detection system for chest radiographs as well as the ultrasound contrast agent albunex. He also led the team that developed the AIUM breast ultrasound accreditation program, and helped develop the ARDMS registry in breast ultrasound. He is currently also Vice Chairman of the Ultrasound Coordinating Committee of the RSNA Quantitative Imaging Biomarker Alliance (QIBA) and is the Principal Author of the forthcoming QIBA Ultrasound Shear Wave Speed Profile which will provide a standard approach to acquisition of shear wave speed data for research, clinical application, and regulatory testing.

Foreword

Given the heavy relatively successful use of manual palpation over the past few thousand years, the ultrasound community, and medicine in general, was very excited to understand and realize the possibility of measuring and imaging the stiffness of tissues. This included tissues too deep for manual palpation. Improving the spatial and quantitative fidelity of elasticity images was addressed aggressively. Also pursued were many extensions related to elastic properties, such as the anisotropy of elasticity, the complex elastic modulus (viscous and elastic components), and elasticity as a function of time under compression.

This two-volume book Tissue Elasticity Imaging extensively covers the principles, implementation, and applications of all these approaches to image the biomechanical properties of tissues. The achieved and future biomedical applications of these many capabilities are also well explained, as are important optical and magnetic resonance imaging techniques that followed, and that sometimes leaped ahead of the many ultrasound developments.

These rapid advances are brought to life for the reader of these books by physicians and other imaging scientists and engineers who made leading advances in each of the covered areas. I initially wished to list key lead authors with a summary of their contributions, but that would essentially be repeating most of the table of contents. The editors of these books, Drs. Brian Garra and S. Kaisar Alam, excelled in recruiting the many luminaries to author the various chapters, defining the topics, and editing the work for readability by the target audience of imaging scientists, engineers, entrepreneurs, clinicians, and operators of the systems. The work should serve as a definitive reference for those teaching and those writing shorter explanations for various groups. This is a much-needed work in the field. Luckily, it will not be the last, as advances are and will continue to be made.

Paul L. Carson, Ph.D.

University of MichiganAnn Arbor, MichiganUnited States

July 14, 2019

Preface

Since its modest beginning in the late 1980s to early 1990s, elastography has gained wide acceptance in many clinical applications, e.g., detection, diagnosis, and treatment monitoring. To assess the growth of elastography, we performed a PubMed search for elastography. The total number of results was 4711 if we searched only the title. We have observed that some papers on elastography do not include elastography in the title but include it in the abstract. Accordingly, we also performed a title/abstract search for elastography: the number of papers went up to 7912. To provide a perspective on the rapid growth, these numbers were 1 and 1, respectively, if we limited the search to only the year 1991. These numbers increased to 16 and 22 (title/abstract) in 2001, 265 and 399 (title/abstract) in 2011, and 729 and 1305 (title/abstract) in 2018. Clearly from these yearly numbers, the ascent of elastography has been rapid, especially during the last decade.

Physicians have known for a long time that tissue elasticity changes with (or due to) disease and routinely used palpations to aid in diagnostic evaluations. If the reader ever went to a physician with an abdominal complaint, the physician probably palpated the abdomen, including the liver. Hippocrates (a Greek physician who lived during Greece's Classical period and is widely regarded as the father of medicine) wrote about abdominal swellings in The Book of Prognostics: …Such swellings as are soft, free from pain, and yield to the finger…and are less dangerous than the others. …then, as are painful, hard, and large, indicate danger of speedy death; but such as are soft, free of pain, and yield when pressed with the finger, are more chronic than these.

Manual palpation, however, is subjective and highly dependent on the physician expertise. The measurements are nonquantitative and not very useful for small or deep lesions. Several researchers explored the clinical use of tissue elasticity in the 1980s. Eventually, Robert Lerner and Kevin Parker published the first journal paper on dynamic elastography (vibration sonoelastography) in 1988. Jonathan Ophir introduced quasi-static elastography in 1991. Many other elastography variants have been invented since then, and a brief history describing many of them may be found in Chapter 1 of Volume 1. Elastography methods do not typically suffer from the limitations of manual palpation. Furthermore, quantitative elastography allows objective monitoring of change over time. Typically, medical imaging modalities measure and display parameters that vary only a few percent between normal and pathological tissues. In contrast, elastography modalities (especially the modalities that image a modulus) can exploit parameter ranges of up to six orders of magnitude! Elastography is probably the only modality with this (very large dynamic range) advantage.

Dr. Brian Garra and I have been involved with elastography since its early days. We discussed editing a reference book on elastography several times in the past. We felt a few of years ago that the time was finally right for us to put this book together. As an Associate Editor of the Elsevier Journal Ultrasonics, I knew our Publisher (at the time) Ysabel Ermers. We approached Ysabel, and she put us in touch with Elsevier's Acquisition Editor Dr. Anita Koch. With Anita's help, we finalized the plan for the book. The book was approved soon afterward. Brian and I wanted the book to be useful for introducing someone to elasticity imaging as well as a reference for someone more advanced in the art. Some of the specifics in the chapters of both volumes will become somewhat outdated within a short time. However, the basics and the general information will remain useful. The readers can search the Internet (e.g., Google, PubMed, etc.) and contact the authors in this book and other experts for guidance on the state of the art. The readers can also consult the companion website for this book at https://www.elsevier.com/books-and-journals/book-companion/978-0-12-809661-1.

There were many options with respect to the organization of the book. We decided to divide the book into two volumes. Volume 1 discusses theory and methods of elasticity imaging, and Volume 2 discusses clinical applications of elasticity imaging modalities. In Volume 1, Chapter 1 takes the readers through a brief history of elastography, starting with some discussion about preimaging days. Chapter 2 provides a unified view of the governing theory of elastography. (Individual chapters in Volume 1 have expanded on the theory for each modality, as needed.) Chapter 3 describes vibration sonoelastography, the first elasticity imaging method. It is followed by a detailed description of quasi-static elastography in Chapter 4. A thorough treatment of dynamic elastography techniques based on acoustic radiation force and shear wave is provided in Chapter 5. Chapter 6 describes magnetic resonance elastography. Inverse problems and modulus construction are briefly treated in Chapter 7. Chapter 8 describes lateral and shear strain imaging. The volume concludes with a detailed chapter on optical elastography (Chapter 9).

In Volume 2, nine chapters discuss several major clinical applications of elastography. This volume can also serve to introduce basic scientists to an array of clinical applications, their current challenges, and future prospects. Even after three decades of development, elastography is a rapidly expanding field. Given the ever-increasing number of labs, researchers, and commercial endeavors, we believe that such progress (in new methods and clinical applications) is likely to continue for many years.

We recruited leading researchers to write the chapters and would like to thank all the authors who contributed. In addition, we would like to thank the reviewers who provided helpful comments for all the chapters. Their service was crucial in ensuring the quality of the chapters. The names of the reviewers are indicated below in an alphabetical order to acknowledge their service.

S. Kaisar Alam

Dayton, New Jersey, USA

October 1, 2019

Chapter reviewers:

Volume 1: Theory and methods

Arun K. Thittai

Assad A. Oberai

David Bradway

EEW Van Houten

Guy Cloutier

James F. Greenleaf

Jean-Luc Gennisson

Kirill Larin

Mark Palmeri

Marvin M. Doyley

Matthew Urban

Michael Richards

Salavat Aglyamov

Thomas A. Krouskop

Tom Seidl

Tomek Czernuszewicz

Yogesh Kannan Mariappan

Acknowledgments

Editing this important reference book was much harder and at the same time, much more fulfilling than I could have ever imagined. First and foremost, I want to thank the Almighty. He gave me the power to pursue my dreams and this book. I could never have done this without my faith in Him. This book happened because He wished it to be.

I am ever grateful to my deceased parents who always encouraged me to pursue my dreams. Thank you my dear wife, daughter, and son for your constant patience and support, especially during difficult times. My younger brother and sister have been my source of strength since they were born. Their spouses and children have been a source of inspiration and joy for me. I have a large number of uncles, aunts, cousins, nephews, and nieces, who have always supported me. I am lucky to have all of you as my family.

I also want to thank many individuals whom I regard as mentors and friends. They include my childhood mentor Dr. Kazi Khairul Islam, my doctoral advisor Dr. Kevin J. Parker, my postdoc supervisor late Dr. Jonathan Ophir, my former supervisors Dr. Ernie Feleppa and late Dr. Fred Lizzi, and my coeditor Dr. Brian Garra. (Brian also provided the artwork used to design the cover.).

I am also indebted to many family members, friends, and colleagues, and it would be impossible to thank them all individually. I am lucky to have been your family, friend, and colleague. Thank you all!

Last but not the least, thanks to everyone in the Elsevier team. Special thanks to our Acquisition Editor (Dr. Anita Koch), Editorial Project Managers (Lindsay Lawrence, Jennifer Horigan, and Amy Clark), Project Manager (Paul Prasad Chandramohan), Cover Designer (Matthew Limbert), and many other individuals who worked behind the scenes to make this book a reality.

S. Kaisar Alam

Dayton, New Jersey, USA

October 1, 2019

Chapter 1

An early history of elasticity imaging

Robert M. Lerner ¹ , ²       ¹ Department of Clinical Imaging, University of Rochester, Rochester, NY, United States      ² Department of Diagnostic Imaging, Rochester General Hospital, Rochester Regional Health, Rochester, NY, United States

Abstract

The antecedents of elastography included some landmark studies of tissue motion in the 1950s through the early 1980s, aided by the increasing sophistication of Doppler, pulse-echo, and digital signal processing systems. We review the progression of tissue motion studies and then the step to true two-dimensional imaging of tissue stiffness. By the mid-1990s, a number of major branches of elastographic imaging using shear waves, or compression steps, were established. The perspectives of a radiologist during that period are also provided for context.

Keywords

Elasticity; Elastography; Imaging; Shear waves; Stiffness; Tissue motion; Viscoelastic

1. Overview and personal observations from a radiologist

Tissue elasticity imaging provides medical or biological images with pixels that qualitatively or quantitatively correspond to measures of tissue stiffness related to clinical palpation. Qualitative elasticity imaging refers to a region of interest that responds differently to a perturbing force than the adjacent tissue, whereas quantitative elasticity imaging refers to a region of interest where a measured value is assigned that is a fundamental mechanical property such as elasticity. It was developed to provide objective biomechanical information to complement conventional medical ultrasonographic imaging. Conventional medical ultrasonographic imaging (B-scan) is based on relative amplitudes of backscattered longitudinal waves (echogenicity), which show no direct correlation to organ and lesion stiffness [1,2]. To better understand tissue elasticity imaging's place in history, a brief description of medical ultrasonography and tissue stiffness considerations is necessary.

Medical ultrasonographic imaging equipment initially mimicked underwater sonar using the speed of sound in water for designing ultrasonographic equipment as an echolocation system presuming biological tissue behaved much like water. When considering a relevant biological tissue as composed mainly of water, the optimum parameters for medical imaging required low megahertz frequencies for adequate depth of penetration of longitudinal waves into deep tissues, with minimal attenuation and with best image detail (smallest wavelength). Initially, bistable images of anatomy were produced from specular reflected echoes originating from organ boundaries and interfaces based on longitudinal wave (bulk modulus) impedance mismatches. These images were able to identify fluid, gas, bone, or calcium but could not differentiate specific organs by their echogenicity. By quantifying the strengths of the weak backscattered echo amplitudes from the small scattering centers in tissue, grayscale (B-scan or brightness mode) images were produced that depicted patient anatomy in a range of contrast detail with different echogenicity patterns. Although some organs in the normal state had characteristic relative echogenicity when compared with other organs, no elastic or viscous mechanical tissue properties could be gleaned from the images, as echogenicity is a complex interaction of the basic speckle pattern of the ultrasonographic instrument and the distribution and strength of the scattering centers in the tissue/organ [3,4]. The images of relative tissue echogenicity based on bulk impedance (longitudinal wave propagation) mismatches have been extraordinarily useful in medicine, depicting normal and abnormal anatomy, organ size, focal lesions, abnormal masses, fluid collections, relative tissue motion, and subjective compliance of tissues to applied transducer pressure. Because shear waves do not propagate through water and are rapidly attenuated in biological tissues at megahertz frequencies [5], they were not considered useful for medical ultrasonographic.

Recognition that subjective tissue stiffness by palpation was not correlated to echogenicity became the motivation for developing a method to image stiffness after a pilot study suggested tissue stiffness as detected by clinical palpation was a better predictor of prostate cancer than echogenicity [1,2,6].

If it's not hard, it's not cancer was a quote by Charles Huggins (Nobel laureate for the discovery of the hormonal treatment of prostate cancer) that was subsequently related to the author by Harry Fischer, MD, a noted X-ray contrast media researcher and former chairman of the Radiology Department at the University of Rochester.

Clearly, there was more to tissue stiffness (hardness) than was being depicted by changes in echogenicity on conventional ultrasonographic equipment. This led to an early project to image objective tissue stiffness with ultrasonography, which would be independent of echogenicity. Complementary studies to measure the elastic properties of prostate tissue in vitro as compared to pathology were subsequently reported [1,7–10].

My initial studies (circa 1982 in collaboration with Professor Robert Waag of the University of Rochester) started with graded compression of a stack of two sponges, one stiffer than the other, with detection of the radio frequency (RF) ultrasound signals from regions in each sponge subjected to increasing degrees of compression. Offline computer processing of the data to detect the correlation length of the sponge scattering elements from each sponge showed that for a certain degree of compression, the stiff sponge maintained its correlation length, whereas, at the same compression level, the softer sponge could no longer show a correlation length. Although the concept showed promise in distinguishing a hard from soft sponge, the computational