MIMRTL is pleased to announce that James Wang successfully completed his preliminary examination on April 21, 2025. The examination marks a significant milestone in his Ph.D. journey, advancing him to candidacy. James’s research, under the guidance of his co-advisors, MIMRTL PI Dr. Alan McMillan, and Dr. Ali Pirasteh, focuses on Optimizing MRI Acquisition for Systemic Issues in Quantitative Analysis. His preliminary examination committee included Dr. Diego Hernando (chair), Dr. Kevin Johnson, and Dr. Jim Pipe.
Whole-body Magnetic Resonance Imaging (WB MRI) holds immense potential as a comprehensive, radiation-free tool for diagnosing and monitoring a range of systemic conditions, including oncologic staging, metabolic disorders, and musculoskeletal diseases. However, its widespread clinical adoption is currently hindered by technical and practical challenges related to scan efficiency, patient comfort, motion robustness, and quantitative accuracy.
James’s research directly addresses these critical limitations. His work outlined in the preliminary examination focuses on several key areas aimed at improving WB MRI. One significant area addresses cumbersome coil setups; conventional WB MRI often requires complex and uncomfortable coil configurations. James’s first aim, to develop and validate Comfortable Open-Coil MRI for Whole-body Imaging (COMFI) as an accurate diagnostic tool for WB MRI, hypothesizes that a coil setup without anterior array coils can provide comparable image quality and diagnostic capability while improving workflow and patient experience. His approach involves developing optimized image processing strategies for these COMFI acquisitions.
Another major focus is on improving motion robustness through free-breathing techniques, as the reliance on breath-hold acquisitions in current WB MRI protocols limits scan duration and can lead to motion artifacts. James’s second aim is to develop, optimize, and implement a Gradient Impulse Response Function (GIRF)-based correction for free-breathing radial imaging sequences. He hypothesizes that free-breathing radial MRI, enhanced by GIRF modeling to correct for gradient imperfections, will yield improved image quality and quantitative accuracy with fewer motion artifacts compared to traditional breath-held methods. His approach involves investigating WB radial MRI with chemical shift-encoding (CSE) reconstruction using GIRF-informed reconstructions in phantoms and human patients.
Furthermore, James’s research aims to enhance quantitative accuracy in CSE MRI, a technique widely used for quantitative fat fraction and R2* measurements that is susceptible to system imperfections. His third aim is to extend the implementation of GIRF-based reconstruction to CSE MRI sequences. He proposes that GIRF corrections can improve the accuracy of CSE techniques and enable more efficient acquisitions, such as those utilizing bipolar readouts. His approach involves enhancing CSE image reconstruction by using GIRF to achieve faster and more accurate imaging.
Please join us in congratulating James on this significant academic achievement!