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Abstract #0393

Synthesizing rCBV maps from DCE-MRI of brain tumors using conditional adversarial networks

Jeremiah Sanders1, Henry Szu-Meng Chen1, Jason M Johnson2, Donald F Schomer2, Jingfei Ma1, and Ho-Ling Liu1

1Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, TX, United States, 2Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, United States

In this work we investigate conditional adversarial networks for synthesizing relative cerebral blood volume (rCBV) maps from dynamic contrast enhanced (DCE)-MRI. A network based on the pix2pix framework is trained to map DCE-MRI to rCBV maps using rCBV maps generated from dynamic susceptibility contrast (DSC)-MRI in the same patient cohort. The results demonstrate the feasibility of synthesizing realistic rCBV maps from DCE images, potentially improving MR perfusion imaging of the brain using a single contrast injection.

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Abstract