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Abstract #0987

Radiomic profiling for IDH-mutant astrocytoma stratification with distinct biologic pathway activities

Chaoli Zhang1, Jing Yan1, and Kaiyu Wang2
1MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China, 2MR Research China, GE Healthcare, Beijing 100000, PR China, Beijing, China

Synopsis

Keywords: Diagnosis/Prediction, Machine Learning/Artificial Intelligence, Astrocytoma, Magnetic resonance imaging, Prognosis, Biological Pathway

Motivation: Recent studies highlight the challenge of interpreting radiomic phenotypes biologically.

Goal(s): To develop a radiomic model for prognostic prediction in IDH-mutant astrocytoma patients and to elucidate the underlying biological mechanisms.

Approach: We used preoperative MRI-derived radiomic features to create and validate a Radscore for predicting overall survival in IDH-mutant astrocytomas. Validation included paired MRI and RNA-seq data, with Gene Set Enrichment Analysis and Weighted Gene Co-expression Network Analysis identifying key biological pathways linked to the Radscore and individual prognostic features.

Results: Radscore is an independent prognostic factor. Four categories of pathways were significantly associated with radiomic features.

Impact: Our study introduces a prognostic Radscore for non-invasive stratification of IDH-mutant astrocytomas. This score is informed by biological pathways associated with immunity, proliferation, cell function, and treatment response, thereby supporting targeted therapies and personalized management.

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