Quantitative Magnetic Resonance Imaging

Dr. Nicole Seiberlich is an Associate Professor in the Department of Radiology at the University of Michigan in Ann Arbor, and the Director of the Michigan Institute for Imaging Technology and Translation (MIITT). She was previously the Elmer Lincoln Lindseth Associate Professor of Biomedical Engineering at Case Western Reserve University. Dr. Seiberlich received her BS in Chemistry from Yale University (New Haven, CT) and her PhD in Physics from the Universität Würzburg (Würzburg, Germany). Her research focuses on novel data acquisition and signal processing techniques for rapid and quantitative Magnetic Resonance Imaging, with applications in cardiac and abdominal imaging. Vikas Gulani is the Chair and Fred J. Hodges Professor of Radiology at the University of Michigan. As Chair, his primary goal is to build a compassionate workplace that strives towards excellence. He was previously the Joseph T. Wearn Professor in Radiology, Urology, and Biomedical Engineering and the Director of MRI at Case Western Reserve University and University Hospitals. Dr. Gulani is a physician-scientist interested in MR technology development and clinical translation. His clinical interests include prostate and liver MRI, MR angiography, and in-bore intervention. His scientific interests include relaxometry, diffusion imaging, perfusion, MR microscopy, parallel imaging, rapid acquisitions, and body MRI. His recent work has focused on development and translation of MR Fingerprinting. Dr. Adrienne Campbell-Washburn is Earl Stadtman Principal Investigator at the MRI Technology Program for the National Heart, Lung, and Blood Institute at the National Institutes of Health. She received her PhD in Medical Physics from University College London.Her research focuses on the development of MRI technology for cardiac, lung and interventional imaging applications. She works on low field MRI technology, advanced MRI acquisitions that leverage non-Cartesian sampling, and reconstruction methods using state-of-the-art computational resources in the clinical environment. Steven Sourbron holds a Chair in Medical Imaging Physics in the University of Sheffield, UK. He is a theoretical physicist by training, obtained a PhD on perfusion MRI from the Free University of Brussels (Belgium), and performed post-doctoral research in the Ludwig-Maximilian University of Munich (Germany) before taking up a lectureship in the University of Leeds (UK). His research focuses on developing and applying quantitative medical imaging techniques that provide more accurate and more biologically specific assessment of tissue perfusion, function and structure. Much of his current work involves clinical studies on non-invasive assessment of chronic kidney- and liver disease to determine if quantitative MRI can improve prognosis and prediction of treatment effects. Mariya Doneva is a senior scientist at Philips Research, Hamburg, Germany. She received her BSc and MSc degrees in Physics from the University of Oldenburg in 2006 and 2007, respectively and her PhD degree in Physics from the University of Luebeck in 2010. She was a Research Associate at Electrical Engineering and Computer Sciences department at UC Berkeley between 2015 and 2016. She is a recipient of the Junior Fellow award of the International Society for Magnetic Resonance in Medicine. Her research interests include methods for efficient data acquisition, image reconstruction and quantitative parameter mapping in the context of magnetic resonance imaging. Fernando Calamante studied Physics in Argentina, and obtained his PhD in MRI from University College London in 2000. He is Professor at the Faculty of Engineering, and Director of Sydney Imaging (the biomedical imaging Core Research Facility) at the University of Sydney. His main areas of research are Diffusion and Perfusion MRI, and their applications to neurology and neuroscience. His work on Perfusion MRI is highly cited and at the forefront of the field, and his Diffusion MRI methods for characterising structural connectivity are also widely used worldwide. Fernando will be President of the International Society for Magnetic Resonance in Medicine in 2021-2022. Houchun Harry Hu has been working in the domain of pediatric MRI over the last 15 years. He obtained his undergraduate degree in biochemical engineering at the University of Southern California, and his PhD in Medical Imaging from the Mayo Clinic. He has served as a Deputy Editor for Magnetic Resonance in Medicine, and an Associate Editor for Radiology and the Journal of Magnetic Resonance Imaging. Dr. Hu's main interests are in translational and clinical research. He has published over 100+ first-author and co-authored manuscripts.

Introduction

SECTION 1 Relaxometry 1. Biophysical and Physiological Principles of T1 and T2 2. Quantitative T1 and T1r Mapping 3. Quantitative T2 and T2* Mapping 4. Multiproperty Mapping Methods 5. Specialized Mapping Methods in the Heart 6. Advances in Signal Processing for Relaxometry 7. Relaxometry: Applications in the Brain 8. Relaxometry: Applications in Musculoskeletal Systems 9. Relaxometry: Applications in the Body 10. Relaxometry: Applications in the Heart

SECTION 2 Perfusion and Permeability 11. Physical and Physiological Principles of Perfusion and Permeability 12. Arterial Spin Labeling MRI: Basic Physics, Pulse Sequences, and Modeling 13. Dynamic Contrast-Enhanced MRI: Basic Physics, Pulse Sequences, and Modeling 14. Dynamic Susceptibility Contrast MRI: Basic Physics, Pulse Sequences, and Modeling 15. Applications of Quantitative Perfusion and Permeability in the Brain 16. Applications of Quantitative Perfusion and Permeability in the Liver 17. Applications of Quantitative Perfusion and Permeability in the Body

SECTION 3 Diffusion 18. Physical and Physiological Principles of Diffusion 19. Acquisition of Diffusion MRI Data 20. Modeling Fiber Orientations Using Diffusion MRI 21. Diffusion MRI Fiber Tractography 22. Measuring Microstructural Features Using Diffusion MRI 23. Diffusion MRI: Applications in the Brain 24. Diffusion MRI: Applications Outside the Brain

SECTION 4 Fat and Iron Quantification 25. Physical and Physiological Properties of Fat 26. Physical and Physiological Properties of Iron 27. Fat Quantification Techniques 28. Applications of Fat Mapping 29. Iron Mapping Techniques and Applications

SECTION 5 Quantification of Other MRI-Accessible Tissue Properties 30. Electrical Properties Mapping 31. Quantitative Susceptibility Mapping 32. Magnetization Transfer 33. Chemical Exchange Mapping 34. MR Thermometry 35. Motion Encoded MRI and Elastography 36. Flow Quantification with MRI 37. Hyperpolarized Magnetic Resonance Spectroscopy and Imaging