We explored the utility of radiomic analysis to identify radiomic features (computer extracted features from MRI) that distinguish long-term survival patients from their short-term survival counterparts based on the pre-treatment perfusion DSC-MRI. Initial results indicate that dynamically extracted radiomic features from enhancing tumor and infiltrative edges on perfusion scans can segregate the 2 survival groups. A non-invasive means of predicting survival based on perfusion imaging may help clinicians to determine prognosis, and inform treatment strategy.
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