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Abstract #4851

The Influence of Heterogenous Subregions on Predicting MGMT Methylation Status of Glioblastomas: A Radiomics Analysis on Multimodal MRI

Qiang Tian1, Xi Zhang2, Lin-feng Yan1, Yu-chuan Hu1, Yu Han1, Ying-zhi Sun1, Wen Wang1, and Guang-bin Cui1

1Radiology, Tangdu Hospital, the Fourth Military Medical University, Xi'an, China, 2Biomedical Engineering, the Fourth Military Medical University, Xi'an, China

MGMT promoter methylation is associated with longer survival and better treatment response of GBM patients. Intratumor heterogeneity is partly responsible for inaccurate detection of MGMT status. Therefore, assessing the effect of different heterogenous subregion of GBM on MGMT status would be critical. In this study, a radiomics approach integrated optimal features of heterogenous subregions in multimodal MRI and machine learning model was proposed for effectively predicting MGMT methylation, and meanwhile assessing the prediction efficiency of subregions or subregion combinations. The proposed approach achieved a promising MGMT methylation detection performance and indicated that rNEC may play a role in this issue.

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