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Abstract #3040

Spatio-temporally constrained reconstruction for hyperpolarized carbon-13 MRI using kinetic models

John Maidens1, Jeremy W Gordon2, Murat Arcak1, Hsin-Yu Chen2, Ilwoo Park2, Mark Van Criekinge2, Eugene Milshteyn2, Robert Bok2, Rahul Aggarwal3, Marcus Ferrone4, James B Slater2, John Kurhanewicz2, Daniel B Vigneron2, and Peder EZ Larson2

1Electrical Engineering & Computer Sciences, University of California, Berkeley, Berkeley, CA, United States, 2Radiology & Biomedical Imaging, UCSF, San Francisco, CA, United States, 3Medicine, UCSF, San Francisco, CA, United States, 4Clinical Pharmacy, UCSF, San Francisco, CA, United States

We present a method of generating metabolism maps from dynamic hyperpolarized carbon-13 MRI images. By incorporating prior information into our model-based reconstruction via spatial regularization of the parameter maps, we achieve two qualitative benefits: elimination of non-identifiability in unperfused background regions, and denoising. This method is illustrated on a simulated dataset and a clinical prostate cancer dataset.

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