Assistant Professor in Biomedical Engineering at Carnegie Mellon University
BioE PhD Dissertation: “Anthropomorphic Phantom Developments for the Characterization and Evaluations of MRI RF Coils”
Over the past few decades, Magnetic Resonance Imaging (MRI/MR) has proven to be one of the most resourceful diagnostic tools to non-invasively exam various parts of the human body. As MRI technology improved, research scanners were developed at greater field strengths to offer greater resolution and improved tissue contrast in comparison to clinical MR machines. In late 2017, the FDA approved the first clinical 7 Tesla (T) MR scanner, Siemens MAGNETOM Terra. The FDA’s approval met the scientific demand for 7T MR imaging and ultra-high field (UHF) (≥ 7 Tesla) imaging’s growing capability to detect human disease and tissue damage within the human body. While these machines offer promise, there are several issues experienced at higher field strengths that hinder its clinical feasibility. UHF MRI is presented with challenges such as 1) magnetic field (B1+) homogeneity, 2) increased global/local specific absorption rate (SAR) in biological tissue, and (3) addressing concerns regarding the unclear radiofrequency (RF) safety assurance due to temperature rise at UHF.
To address these challenges, the work of this dissertation develops tools to characterize RF coil designs for RF engineers. These tools are realized through hardware and software developments including a realistic anthropomorphic heterogeneous human head phantom and other software methodologies for the evaluation of RF coil designs.
The results and the broad conclusion will support our long-term goal of achieving homogeneity and minimized RF power absorption at 7T in-vivo and further the UHF MRI community’s understanding of 7T imaging. Thus, progress in this proposed work strengthens 7T’s potential clinical feasibility and its ability to detect human disease and premature symptoms of brain damage.
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Below you will find video footage of the anatomically detailed human head phantom project that I designed. The footage shows the model being taken from an acquired 3T MRI dataset, segmented and later prototyped with CAD software.