Optimizing flip angles for metabolic rate estimation in hyperpolarized carbon-13 MRI
John Maidens1, Jeremy W. Gordon2, Murat Arcak1, and Peder E. Z. Larson2
1Electrical Engineering & Computer Sciences, University of California, Berkeley, Berkeley, CA, United States, 2Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
Hyperpolarized
carbon-13 MRI experiments typically aim to distinguish between
healthy and diseased tissues based on the rate at which they
metabolize an injected substrate. Existing approaches to determine
flip angle sequences for kinetic measurements have used metrics such
as signal variation and signal-to-noise ratio, but are not optimized
to provide the most reliable metabolic rate estimates.
Here we present a flip
angle sequence that maximizes the Fisher
information about the metabolic rate. We demonstrate through
numerical simulation that flip
angle sequences optimized using the Fisher
information lead to lower variance in metabolic rate estimates than
existing sequences. We then validate this optimized sequence in
vivo with experiments in a prostate cancer
mouse model.
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