NIMG-49. RADIO-PATHOMIC MAPS OF DE-NOVO GLIOBLASTOMA IDENTIFY PHENOTYPES OF TUMOR INVASION ASSOCIATED WITH PROGNOSIS

Abstract

Abstract PURPOSE Although tumor is known to exist beyond the contrast-enhancing margin, a lack of access to pathological information beyond enhancement has hindered the study of non-angiogenic tumor characteristics and their effects on patient prognosis. This study tested the hypothesis that radio-pathomic maps of tumor characteristics developed using autopsy tissue samples can identify phenotypes relevant to patient survival and treatment outcomes. METHODS A dataset of autopsy tissue samples aligned to the MRI as ground truth from 65 glioma patients (training set n=43, test set n=22) was used to train machine learning models that predict and map tumor cellularity (Cell), extracellular fluid (ECF), and cytoplasm (Cyt) density following our previously published methodology (Bobholz et al. 2022). Cell, ECF, and Cyt maps were then generated from the pre-surgical MRI scans from an independent dataset of 80 glioblastoma patients. Each patient was separated into groups based on the appearance of tumor characteristics beyond the contrast-enhancing margin. Group phenotypes included Well-Circumscribed (WC) tumors with no tumor activity beyond contrast enhancement, Necrotic Front (NF) tumors with areas of necrosis extending beyond the tumor margin, Hypercellular Front (HF) tumors with areas of increased cellularity surrounding the tumor, and Hybrid Front (HYF) tumors with characteristics of both HF and NF tumors. A Cox regression was used to assess survival differences between phenotypes, controlling for treatment history. RESULTS Across the 80 patients, 22 were classified as WC, 14 were classified as HF, 24 were classified as NF, and 20 were classified as HYF. NF, HF, and HYF tumors each showed significant/trending reductions in survival when compared to WC tumors (HR=2.02, p=0.03; HR=2.0, p=0.06; and HR=1.75, p=0.09, respectively). CONCLUSION Radio-pathomic phenotypes identify characteristics beyond the contrast-enhancing margin that affect overall survival outcome in glioblastoma.