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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