NIMG-63. PRE-SURGICAL RADIO-PATHOMIC MAPS OF TUMOR CELLULARITY PREDICT EARLY RECURRENCE IN GLIOBLASTOMA PATIENTS. (14th November 2022)

• Record Type: Journal Article
• Authors: Winiarz, Aleksandra; Bobholz, Samuel; Lowman, Allison; Duenweg, Savannah; Kyereme, Fitzgerald; Coss, Dylan; Cochran, Elizabeth; Connelly, Jennifer; LaViolette, Peter
• Is Part Of: Neuro-oncology. Volume 24(2022)Supplement 7
• Page Start: vii178
• Page End: vii178
• Publication Date: 2022-11-14
• Subjects: Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noac209.681
• Languages: English
• ISSNs: 1522-8517

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.