Abstract #1959

A Subregion-based RadioFusionOmics Model Discriminates between Grade 4 Astrocytoma and Glioblastoma on Multisequence MRI

Ruili Wei¹, Xinrui Pang¹, Ye Wang¹, Fangrong Liang¹, Yongzhou Xu², and Ruimeng Yang¹

¹Department of Radiology, Guangzhou First People's Hospital, Guangzhou, China, ²Philips Healthcare, Guangzhou, China

Synopsis

Keywords: Tumors, Radiomics

The 2021 update of WHO CNS5 underlines the importance of IDH genotype prediction in the setting of adult-type grade 4 glioma. We developed a RFO model to discriminate between grade 4 astrocytoma and glioblastoma using subregional radiomics signatures from conventional MRI sequences. The fusion models from multiparametric MR images outperformed that from single sequence. The comparison between two different subregion manners revealed that voxel-wise habitats defined by clustering procedure yielded a higher discriminative capability. Our results also implied that tumor edema may contain underlying heterogeneous metrics between grade 4 astrocytoma and GBM.

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