NIMG-63. PRE-SURGICAL RADIO-PATHOMIC MAPS OF TUMOR CELLULARITY PREDICT EARLY RECURRENCE IN GLIOBLASTOMA PATIENTS

Abstract

Abstract PURPOSE Glioblastoma time to recurrence following initial surgery is difficult to predict as it differs widely between patients. This is important as those who recur early have a poorer prognosis and shorter survival time. This study aimed to test the hypothesis that cell density, as defined by a predictive radio-pathomic mapping model, would indicate a more aggressive tumor, and thus carry a lower time to progression. METHODS 18 confirmed glioblastoma patients were included in this study. All patients underwent surgery followed by chemo-radiation, consistent with standard of care. Inclusion criteria also included radiographic recurrence, and autopsy confirmation of recurrent glioblastoma. Three magnetic resonance imaging (MRI) timepoints were investigated: pre- and post-surgery, and tumor recurrence defined by a radiologist. Patients were classified into two groups, early recurrence, as defined by tumor progression in the first 6 months post-surgery MRI (n=9, average 116 days to recurrence), and late recurrence, which included everyone else (n=9, average 283 days to recurrence). Contrast enhancement and FLAIR hyperintensity regions of interest were annotated from the patients’ T1+C and FLAIR scans. Radio-pathomic maps of predicted tumor cellularity were generated from a previously published machine learning model trained to identify tumor pathology using aligned autopsy tissue samples as ground truth to clinical MRI scans. The T1, T1+C, FLAIR, and apparent diffusion coefficient (ADC) images were used as input. Tumor cellularity values were then averaged across the T1+C and FLAIR ROIs. RESULTS Both pre- and post-surgical cell density within contrast enhancement was significantly greater in patients with early recurrence compared to those who recurred later (p ≤0.05). CONCLUSIONS Our results suggest that radio-pathomic maps of cell density can identify early-recurrence in patients prior to treatment. This may help with treatment planning for radiologists, surgeons, and neuro-oncologists which may include more aggressive surgery and more frequent monitoring.