Survival Risk Stratification of 2021 WHO IDH-wt GBM by Multiparametric MRI Radiomics Model and Exploration of Biological Foundation
Motivation: GBM is associated with low survival rates and poor prognoses. Accurately stratifying survival risk is crucial for personalized treatment strategies. Goal(s): Aimed to construct an accurate survival risk stratification model by integrating radiomics and clinical factors, and explore its biological foundations. Approach: We collected clinical and MRI data from 369 patients and constructed combined models for survival risk stratification, and explored the biological foundations. Results: The combined model achieved a C-index of 0.815 for survival risk stratification, significantly outperforming the individual radiomics and clinical models. The activation of neurotransmitter and lipid metabolism pathways may be associated with high-risk glioblastomas. Impact: The combined model improves survival risk stratification in IDH-wt GBM by integrating radiomics and clinical factors, supporting the guidance of personalized treatment strategies. The biological foundations may provide new insights for future therapies.
Authors
- Yan Qin Tan (ORCID: https://orcid.org/0000-0002-7529-9807)
- Yangyang Li (ORCID: https://orcid.org/0000-0002-1328-8889)
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2025-09-16
- DOI
- https://doi.org/10.58530/2025/1381
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00