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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