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Abstract #1879

The Utility of Virtual Biopsies for Dataset Augmentation as Applied to AI-Based Detection of Tumor Infiltration in Non-Enhancing Brain Lesion

Robert Wujek1, Melissa Prah2, Mona Al-Gizawiy2, and Kathleen Schmainda2
1Graduate School, Medical College of Wisconsin, Wauwatosa, WI, United States, 2Biophysics, Medical College of Wisconsin, Wauwatosa, WI, United States


Delineation of invasive tumor from peritumoral edematous tissue remains a major obstacle to glioma treatment. To address this problem, a neural network was trained to distinguish between these regions using biopsies paired with colocalized MRI inputs. In addition to histologically confirmed biopsies, virtual biopsies sampled from non-contrast enhancing, FLAIR enhancing regions of non-invasive tumors (meningioma, metastasis) were used with an assumed classification of “non-tumor”. The current work is a preliminary assessment of this assumption and it's impact on model performance.

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