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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