Quantification of Biophysical Parameters in Medical Imaging Ingolf Sack Tobias Schaeff ter Editors 123 Quantification of Biophysical Parameters in Medical Imaging Ingolf Sack • Tobias Schaeffter Editors Quantification of Biophysical Parameters in Medical Imaging Editors Ingolf Sack Tobias Schaeffter Department of Radiology Medical Physics Humboldt University and Metrological Information Technology of Berlin Charité University Hospital Physikalisch-Technische Bundesanstalt Berlin Berlin Germany Germany ISBN 978-3-319-65923-7 ISBN 978-3-319-65924-4 (eBook) https://doi.org/10.1007/978-3-319-65924-4 Library of Congress Control Number: 2017964376 © Springer International Publishing AG 2018 This work is subject to copyright. 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Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Acknowledgements The authors of this book wish to thank the many colleagues and collaborators from whom they received continuous support, inspiration, scientific advice, and positive criticism. The endeavor of writing a book like this would not have been possible without prospering communication and collaboration across the established borders of disciplines and institutions. Many researchers involved in writing chapters of this book have ties to both clinical research and basic science and dedicate themselves to obtaining a higher precision, improved accuracy, and better understanding of clinical imaging markers. This spirit has evolved in the new research training group BIOQIC, Biophysical Quantitative Imaging towards Clinical Diagnosis, which is funded by the German Research Foundation (DFG GRK2260). The authors are grateful to the DFG and their reviewers for having been granted this unique oppor- tunity to establish such an interdisciplinary training program in the important fields of biophysics, medical imaging technologies, and clinical radiology as covered by this book. v Contents 1 Introduction: Medical Imaging for the Quantitative Measurement of Biophysical Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Ingolf Sack and Tobias Schaeffter Part I Biological and Physical Fundamentals 2 The Fundamentals of Transport in Living Tissues Quantified by Medical Imaging Technologies . . . . . . . . . . . . . . . . . . . . . . 9 Sebastian Hirsch, Tobias Schaeffter, and Ingolf Sack 3 Mathematical Modeling of Blood Flow in the Cardiovascular System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Alfonso Caiazzo and Irene E. Vignon-Clementel 4 A Biphasic Poroelasticity Model for Soft Tissue . . . . . . . . . . . . . . . . . . . 71 Sebastian Hirsch 5 Physical Properties of Single Cells and Collective Behavior . . . . . . . . . . 89 Hans Kubitschke, Erik W. Morawetz, Josef A. Käs, and Jörg Schnauß 6 The Extracellular Matrix as a Target for Biophysical and Molecular Magnetic Resonance Imaging . . . . . . . . . . . . . . . . . . . 123 Angela Ariza de Schellenberger, Judith Bergs, Ingolf Sack, and Matthias Taupitz Part II Medical Imaging Technologies 7 Mathematical Methods in Medical Image Processing . . . . . . . . . . . . . . 153 Gitta Kutyniok, Jackie Ma, and Maximilian März 8 Acceleration Strategies for Data Sampling in MRI . . . . . . . . . . . . . . . . 167 Christoph Kolbitsch and Tobias Schaeffter 9 4D Flow MRI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 Sebastian Schmitter and Susanne Schnell vii viii Contents 10 CEST MRI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213 Martin Kunth and Leif Schröder 11 Innovative PET and SPECT Tracers . . . . . . . . . . . . . . . . . . . . . . . . . . . 255 Ulrich Abram 12 Methods and Approaches in Ultrasound Elastography . . . . . . . . . . . . 281 Heiko Tzschätzsch 13 Photoacoustic Imaging: Principles and Applications . . . . . . . . . . . . . . 303 Jan Laufer 14 Fundamentals of X-Ray Computed Tomography: Acquisition and Reconstruction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325 Marc Dewey and Marc Kachelrieß Part III Applications 15 Quantification of Myocardial Effective Transverse Relaxation Time with Magnetic Resonance at 7.0 Tesla for a Better Understanding of Myocardial (Patho)physiology . . . . . . . . . . . . . . . . . 343 Till Huelnhagen, Teresa Serradas-Duarte, Fabian Hezel, Katharina Paul, and Thoralf Niendorf 16 Extracellular Matrix-Specific Molecular MR Imaging Probes for the Assessment of Aortic Aneurysms . . . . . . . . . . . . . . . . . . . . . . . . 373 Julia Brangsch, Carolin Reimann, and Marcus R. Makowski 17 Diffusion-Based MRI: Imaging Basics and Clinical Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383 Michael Scheel 18 Quantification of Functional Heterogeneities in Tumors by PET Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395 Winfried Brenner, Florian Wedel, and Janet F. Eary 19 Tumor Characterization by Ultrasound Elastography and Contrast-Enhanced Ultrasound . . . . . . . . . . . . . . . . . . . . . . . . . . . 411 Thomas Fischer, Anke Thomas, and Dirk-André Clevert 20 Sensitivity of Tissue Shear Stiffness to Pressure and Perfusion in Health and Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . 429 Jing Guo, Florian Dittmann, and Jürgen Braun 21 Radionuclide Imaging of Cerebral Blood Flow . . . . . . . . . . . . . . . . . . . 451 Ralph Buchert 22 Cardiac Perfusion MRI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 471 Amedeo Chiribiri 23 Myocardial Perfusion Assessment by 3D and 4D Computed Tomography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 487 Marc Dewey and Marc Kachelrieß Introduction: Medical Imaging 1 for the Quantitative Measurement of Biophysical Parameters Ingolf Sack and Tobias Schaeffter Abstract Medical imaging is the backbone of modern clinical diagnosis with the vast majority of images obtained by high-end tomographic modalities such as com- puted tomography (CT), magnetic resonance imaging (MRI), 3D ultrasound (US), and emission tomography (PET, SPECT). However, the current radiologi- cal practice is based on visual inspection of images and most diseases are rated in qualitative terms, which results in limited comparability and accuracy of image-based diagnostic decisions. Therefore, there is a need for quantitative imaging technologies for the assessment of biophysical tissue parameters. This book focuses on imaging approaches to obtain quantitative information of fluid transport, soft tissue mechanics, and tissue structures; and gives examples on clinical applications that benefit from quantitative imaging. Medical imaging is the backbone of modern clinical diagnosis. More than 5 billion imaging investigations are performed worldwide each year [1, 2]. The vast majority of radiological imaging procedures are based on high-end tomographic modalities such as computed tomography (CT), magnetic resonance imaging (MRI), 3D ultra- sound (US), and emission tomography (PET, SPECT) [3]. Medical imaging is a prospering market with estimated sales of $31.9 billion in 2019 alone in the United I. Sack (*) Department of Radiology, Charité - Universitätsmedizin Berlin, Berlin, Germany e-mail: [email protected] T. Schaeffter Medical Physics and Metrological Information Technology, Physikalisch-Technische Bundesanstalt, Berlin, Germany e-mail: [email protected] © Springer International Publishing AG 2018 1 I. Sack, T. Schaeffter (eds.), Quantification of Biophysical Parameters in Medical Imaging, https://doi.org/10.1007/978-3-319-65924-4_1 2 I. Sack and T. Schaeffter States.1 The growing demand for high-end imaging systems reflects advancing tech- nologies, aging demographic trends, evolving epidemiological patterns, and chang- ing patient care strategies. Notwithstanding this success, medical imaging has not yet fulfilled all expectations about its reproducibility, consistency, and accuracy. 1.1 Most Clinical Imaging Examinations Are Still Nonquantitative Medical imaging modalities today can acquire morphological information with high spatial resolution in a relatively short time. This technical progress has led to the current radiological practice to make decisions based on visual inspection of images and to rate diseases in qualitative terms like “enlarged,” “small,” or “enhanced.” Such qualitative information often suffers from the limited comparabil- ity among readers, modalities, platforms, and scan protocols. Virtually none of the currently used diagnostic information is related to the biophysical properties of the affected tissue. The lack of established quantitative and biophysics-based medical imaging markers has wide implications for clinical practice. Today, radiologists need many years of training to master the interpreta- tion of subtle morphometric variations. Although principally feasible using current imaging methods, quantitative staging of many diseases such as tumors, hepatic fibrosis, neurodegeneration, and cardiovascular pressure usually requires invasive interventional methods and/or histological examination for final validation. For example, in cardiovascular disease diagnosis and therapeutic decisions are based on vascular anatomical features, such as the diameter of stenotic vessels, rather than on the physiological relevance of the stenotic vessels for the heart or brain. The COURAGE trial [4] showed no significant outcome difference in coro- nary catheterization in comparison with standard medical therapy alone when vascular anatomical features were used. However, it was shown in a sub-study that certain patients can benefit from such expensive intervention, when the blood flow is measured in tissue (called perfusion) as a biophysical property [5]. Also in cancer new imaging parameters are required for early diagnosis and teatment of tumors. There is a strong trend to expand the current metrics, which have been based solely on size, like the World Health Organization (WHO) criteria and the Response Evaluation Criteria in Solid Tumors (RECIST) [6, 7]. Both applications also require medical imaging to asess therapy effects non-inva- sively. However, such serial imaging is often hampered by a low reproducibility due to technical variations and inter-observer variability. The same applies to multi- center studies, where different scanners and interobserver variability add to the issues. For these reasons, the demand for quantitative imaging technologies has been identified as the major new challenge for the advancement of medical imaging over the next decade [8]. 1 www.freedoniagroup.com. 1 Introduction: Medical Imaging for the Quantitative Measurement of Biophysical 3 1.2 Toward Quantitative Medical Imaging The mission to improve the value and practicality of quantitative imaging biomarkers has emerged in worldwide alliances such as QIBA (Quantitative Imaging Biomarkers Alliance2) by RSNA, the Quantitative Imaging Network (QIN3) of the National Cancer Institute in the United States, or EIBALL (European Imaging Biomarkers Alliance) by ESR [9], which are all committed to making medical imaging a more quantitative science. In parallel, graduate training programs emerge which specifi- cally focus on quantitative medical imaging. One activity is BIOQIC—Biophysical Quantitative Imaging towards Clinical diagnosis [10]—a graduate school centered in Berlin, Germany, and funded by the German Research Foundation (DFG), which addresses the investigation and clinical application of new quantitative imaging approaches. Most of the authors of this book are involved in BIOQIC activities—from defining clinical needs to current research and teaching activities. 1.3 About the Book This book has the mission of teaching medical imaging sciences to interdisciplinary scientists and PhD students with emphasis on quantitative biophysical tissue param- eters. These parameters include transport-related parameters, such as flow velocity; tracer kinetics; diffusion; perfusion; and mechanical properties, like stiffness, elastic- ity, and viscoelasticity, and structure-related properties like cell density, heterogene- ity, and anisotropy. Many of these properties also influence each other, e.g., the anisotropy of tissue microstructure strongly affects the amount and direction of dif- fusion. This book emphasizes imaging research in modality- and system-i ndependent biophysical properties. This biophysics-based view on quantitative medical imaging is complementary to the worldwide research effort in quantitative parameter map- ping of modality-related parameters such as relaxation times in MRI or CT attenua- tion coefficients. Figure 1.1 illustrates the primary parameter classes addressed by biophysical quantitative imaging, that is, fluid transport, soft tissue mechanics, and tissue structures. The close interrelation of soft tissue structures including vascular components and cellular and extracellular networks at multiple scales naturally yields an overlap in the prescribed parameter categories. For example, the cross- linking of extracellular matrix influences the macroscopic mechanical response of the tissue. Another example is the microstructures such as microvessels and intersti- tial spaces, which significantly control the fluid transport properties in the tissue. Chapter 2 outlines the theoretical foundations for the parameter categories as illus- trated in Fig. 1.1. The interrelation between fluid transport, structures, and mechani- cal properties in biological tissues is of high relevance for basic research and clinical applications in imaging sciences. 2 http://www.rsna.org/QIBA/. 3 https://imaging.cancer.gov/informatics/qin.htm.