Abstract #0663

Radio-pathomic models trained with autopsy tissue samples aligned to MP-MRI predict histopathological features in brain cancer patients.

Samuel Bobholz¹, Allison Lowman², Michael Brehler², Savannah Duenweg¹, Fitzgerald Kyereme², Elizabeth Cochran³, Jennifer Connelly⁴, Wade Mueller⁵, Mohit Agarwal², Darren O'Neill², Anjishnu Banerjee⁶, and Peter LaViolette^2,7

¹Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States, ²Radiology, Medical College of Wisconsin, Milwaukee, WI, United States, ³Pathology, Medical College of Wisconsin, Milwaukee, WI, United States, ⁴Neurology, Medical College of Wisconsin, Milwaukee, WI, United States, ⁵Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States, ⁶Biostatistics, Medical College of Wisconsin, Milwaukee, WI, United States, ⁷Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI, United States

This study used autopsy tissue in order to develop radio-pathomic models for histopathological features of brain cancer. These models used T1, T1C, FLAIR, and ADC images from 45 patients as input into bagged regression ensembles for cellularity, cytoplasm, and extracellular fluid, using the aligned autopsy tissue samples as ground truth. These models were able to accurately predict these features and were able to find tumor signatures, such as hypercellularity beyond the traditional contrast-enhancing and FLAIR hyperintense regions. These radio-pathomic maps provide new insights into non-invasive signatures of tumor pathology in the post-treatment state and beyond the contrast enhancing region.

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