Accelerated and Motion Corrected Magnetic Resonance Imaging using Nonlinear Gradient Fields
Magnetic resonance imaging (MRI) provides images with high soft-tissue contrast and clinically acceptable signal-to-noise ratio without exposing the patient to ionizing radiation. Therefore, MRI is one of the more commonly used clinical imaging modalities. However, scan time is not one of the stronger aspects of MRI, since individual scans may last up to a few minutes. This decreases accessibility of MRI scanners by increasing costs per patient, reduces patient comfort, and also makes MRI prone to patient motion. Even though effects of involuntary motion such as respiratory and cardiac motion can be overcome, correcting those effects generally increases total scan time further. Moreover, in certain cases including pediatric imaging, preventing motion may be inevitable without sedation.
Nonlinear gradient fields are hardware components that have attracted increased attention in MRI research in recent years due to their spatially varying encoding capabilities. This talk will characterize the differences between such fields and their clinically available counterparts, and describe how these differences can be exploited to accelerate imaging of specific tissues, to obtain patient motion data in a fraction of a millisecond for retrospective correction of motion artifacts in images, and to improve imaging fidelity and patient safety.
Bio: Emre Kopanoglu is a post-doctoral associate at the Department of Diagnostic Radiology, Yale University School of Medicine. He received his Ph.D. and B.Sc. degrees in 2012 and 2006, respectively, in electrical and electronics engineering from Bilkent University, and worked as a research and teaching assistant at Bilkent University (2006-2012) and as a researcher at the National Magnetic Resonance Research Center (UMRAM, 2009-2012). His research focuses on developing excitation and encoding strategies in magnetic resonance imaging (MRI) to reduce patient heating, track and correct patient motion, and accelerate MRI scans. During his Ph.D. studies, he demonstrated for the first time that nonlinear gradient fields can be used to reduce patient heating, which led to a U.S. patent application supported by Siemens Healthcare. In 2013, he received the ISMRM Summa Cum Laude Merit Award for his conference submission, and won first prize in Yale University Bio-Imaging Sciences Grand Rounds. He is a member of the IEEE and the ISMRM, and serves as an ad-hoc reviewer for the journal Magnetic Resonance in Medicine.