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UC San Francisco Electronic Theses and Dissertations UCSF UC San Francisco Electronic Theses and Dissertations Title MR PHASE AND SUSCEPTIBILITY-WEIGHTED IMAGING OF IRON DEPOSITION IN MULTIPLE SCLEROSIS AND RADIATION-TREATED BRAIN TUMORS Permalink https://escholarship.org/uc/item/9901m0fs Author Bian, Wei Publication Date 2014 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California MR PHASE AND SUSCEPTIBILITY-WEIGHTED IMAGING OF IRON DEPOSITION IN MULTIPLE SCLEROSIS AND RADIATION-TREATED BRAIN TUMORS by Wei Bian DISSERTATION Submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in Bioengineering in the GRADUATE DIVISION of the UNIVERSITY OF CALIFORNIA, SAN FRANCISCO AND UNIVERSITY OF CALIFORNIA, BEPdCELEY Copyright 2014 by Wei Bian ii ACKNOWLEDGEMENTS First and foremost I wish to thank my advisor Prof. Sarah Nelson. It has been a great honor to be her student and work in her lab. I would like to express my deepest gratitude to her, for her advice, guidance, funding, and encouragement, which enrich my growth as a student, a researcher, and a person. I also want to thank all my dissertation committee members Profs. Daniel Vigneron, Christopher Hess, Steven Conolly, and Nicholas Butowski, who have supported me throughout my dissertation research with their knowledge and experience. In particular, Prof. Conolly has offered much advice and insight on my dissertation while challenging me to clarify and prove my assertions. A special thanks goes to Dr. Janine Lupo, whom I worked closely throughout my Ph.D. study. She provided me in-person guidance on every aspect of my research, from experimental design to data acquisition to data analysis to manuscript composition and publication. From her I have learned how to write and express myself on scientific papers. I would like to thank Profs. Daniel Pelletier and Roland Henry, who gave me chance to work on MR imaging of multiple sclerosis, broadening my horizons beyond brain tumors in neuroimaging. I express my thankfulness to my research collaborators neurooncologist Susan Chang from the department of neurological surgery, Prof. Duan Xu and GE Healthcare research scientists Douglas Kelly and Suchandrima Banerjee, whose clinical knowledge and engineering expertise made my research work possible. iii As I have worked over the years in my graduate school, I have been blessed with a friendly and cheerful group of lab-mates, whose valuable suggestions have contributed to my research immensely. The group has been a source of collaboration, inspiration and friendships. The Bioengineering graduate program at UC Berkeley and UCSF has provided funding and the academic support I have needed to complete my graduate school education. I specially acknowledge my academic advisor Prof. John Kurhanewicz and our program administrators Rebecca Pauling, Kristin Olson, and SarahJane Taylor for their kind help regarding my academic requirements. Thanks to all the staff in the Surbeck Laboratory of Advanced Imaging, especially our research nurses Bert Jimenez and Allison Fuller, MR technologist Niles Bruce and Mary McPolin, and clinical coordinator Linda Shapiro, who helped me with all the logistics for collecting MR images from patients. Being involved in research in brain tumors, I am indebted to all patients from whom I obtained invaluable MR imaging data. Without their willingness to participate our research, my dissertation research would not have been possible. More importantly, their ability to adapt to different situations, find hope where there is little, and most of all, whole-heartedly trust in another person has inspired me to face struggles in my research and my personal life. I also want to acknowledge the founding sources I received from Graduate Education in Medical Sciences (GEMS) training program fellowship awarded by Howard Hughes Medical Institute; and UC Discovery grants LSIT-01-10107 and ITL-BIO04-10148 in conjunction with GE Healthcare. Finally, my parents and my sister deserve special mention for all their love, encouragement and endless support in all my pursuits. And this dissertation is dedicated to them. iv ABSTRACT Magnetic Resonance Imaging is a non-invasive imaging technique that is widely used in medicine. Conventionally, MRI contrasts rely on differences in longitudinal or transverse relaxation times of different tissues and the resulting images display primarily anatomical information of the tissues. With progress in MRI techniques, image contrasts that provide functional or physiological information are now available. Tissue susceptibility is one of this kind and recently has been gaining interest in MRI, especially at high MR field strengths. To generate susceptibility contrast, MR phase and susceptibility-weighted imaging (SWI) are currently two imaging modalities that are used most often. In this work, we focused on using these imaging methods to study abnormal iron accumulation in multiple sclerosis (MS) and radiation-treated brain tumors. We first report in this dissertation a serial phase imaging study of chronic MS lesions in which the phase contrast, presumed due to iron deposition in the lesions, was investigated longitudinally. The observations from the study contribute to a better knowledge of the mechanism of the phase contrast in MS lesions and their evolution. Then we present a comparison study of SWI of iron-containing cerebral microbleeds (CMBs) between 3 Tesla and 7 Tesla MR scanners for patients who had brain tumors and received radiation therapy. This study was aimed at knowing how much sensitivity gain can be achieved when choosing 7T over 3T for detection of CMBs. Followed by the study, a gradient-echo sequence with multiple echoes is introduced, which is able to acquire MR angiography and susceptibility-weighted images simultaneously. This sequence provides a way to characterize CMBs together with veins and arteries in the brain. In addition, by integrating data from several echoes, the SWI can be made more flexible and its imaging quality of CMBs can be improved compared to sing-echo SWI. Finally, an automated CMB detection algorithm is developed, which is able to identify v CMBs on images from SWI with a high sensitivity. Its high accuracy and fast speed significantly reduces radiological time burden in identifying CMBs, which will speed up the exploring of the clinical relevance of CMBs. vi CONTENTS Chapter 1 Introduction..................................................................................................................1 1.1 Background ..........................................................................................................................1 1.2 Contributions........................................................................................................................3 1.3 Organization of the dissertation ...........................................................................................4 Chapter 2 Principles of MRI .........................................................................................................6 2.1 Nuclear Magnetism ..............................................................................................................6 2.1.1 Spin and magnetic moment .........................................................................................6 2.1.2 Procession of nuclear magnetic moment ....................................................................7 2.1.3 Net macroscopic magnetic moment ............................................................................8 2.2 Detection of MR signal ......................................................................................................10 2.3 Spatial encoding .................................................................................................................12 2.4 Pulse sequence and image formation .................................................................................14 2.5 Image contrast ....................................................................................................................18 Chapter 3 MR phase and susceptibility-weighted imaging......................................................23 3.1 Magnetic susceptibility ......................................................................................................23 3.2 Susceptibility effect on MR phase images .........................................................................24 3.3 Phase image processing .....................................................................................................26 3.3.1 Phase Wrapping ........................................................................................................26 3.3.2 Phase unwrapping methods.......................................................................................27 3.3.3 Multi-coil phase image combination ........................................................................31 3.4 Susceptibility weighted imaging ........................................................................................33 3.4.1 Phase mask for SWI ..................................................................................................34 3.4.2 SWI sequence ............................................................................................................35 3.4.3 Data acquisition of SWI ............................................................................................37 Chapter 4 Longitudinal MR phase imaging of multiple sclerosis lesions ...............................39
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