Abstract INTRODUCTION Hypermutation is the excessive accumulation of DNA mutation in cancer cells. This specific hypermutated genotype has been reported in low and high grade gliomas, specifically post-temozolomide treatment and is associated with treatment-resistance. Herein, we sought to identify an imaging-based signature for hypermutated gliomas using a radiomics-based approach. MATERIALS AND METHODS In this IRB-approved retrospective study, we analyzed a total of 101 patients with primary gliomas from the University of Texas MD Anderson Cancer Center. Next generation sequencing (NGS) platforms (T200 and Foundation 1) were used to determine the Mutation burden status in post-biopsy (stereotactic/excisional). Patients were dichotomized based on their mutation burden; 77 hypomutated (<30 mutations) and 24 hypermutated (>=30 mutations or <30 with MMR gene or POLE/POLD gene mutations). Radiomic analysis was performed on the conventional MR images (FLAIR and T1 post-contrast) obtained prior to tumor tissue surgical sampling; and a total of 2480 rotation-invariant radiomic features were extracted using: (i) the first-order histogram and (ii) grey level co-occurrence matrix. The Maximum Relevance Minimum Redundancy technique was used to select the most relevant radiomic features. ROC analysis and leave-one-out cross-validation (LOOCV) were used to assess the performance of the Support Vector Machine (SVM) classifier as and AUC, Sensitivity, Specificity, and p-value were obtained. RESULTS We found 100 radiomic features that can discriminate between hypermutated versus hypomutated gliomas, AUC 96.3% (CI: 90.2%-98.9%), Sensitivity 100%, Specificity 95%, p-value=3.769e-6. CONCLUSION Hypermutated gliomas has a unique radiomic quantitative signature that can be used to predict mutation burden regardless of tumor grade or histopathology. Citation Format: Islam Hassan, Aikaterini Kotrotsou, Carlos Kamiya Matsuoka, Kristin D. Alfaro-Munoz, Nabil Elshafeey, Nancy El Shafei, Pascal O. Zinn, John F. de Groot, Rivka R. Colen. A radiomic-based MRI phenotype is uniquely associated with hypermutated genotype in gliomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2955.