Srinidhi Bharadwaj, Paloma Casteleiro Costa, Caroline Serafini, Brienna Heinsz, Alice Hsu, Nischita Kaza, Zhe Guang, Zhenmin Li, Jeffrey J. Olson, Kimberly Hoang, Stewart Neill, Francisco E. Robles
Accurate intraoperative diagnosis of brain tumors is critical for improving patient outcomes, yet current histopathology is time-consuming and performed outside the operating room. We investigate the use of quantitative oblique back-illumination microscopy (qOBM) for the identification and classification of tumors in brain tumor core samples ex vivo . We studied samples from 28 patients across four tumor types and identified diagnostic features in qOBM images corroborated by H&E. Using samples from 19 glioma patients, a leave-one-out classifier distinguishes high- from low-grade glioma cases with 86.6% accuracy (95% CI: 85.9-87.4%), demonstrating qOBM’s potential for real-time intraoperative diagnosis in future studies.