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

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
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article

Survival Risk Stratification of 2021 WHO IDH-wt GBM by Multiparametric MRI Radiomics Model and Exploration of Biological Foundation

Yan Qin Tan, Yangyang Li
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
Radiomics and Machine Learning in Medical Imaging
article

Survival Risk Stratification of 2021 WHO IDH-wt GBM by Multiparametric MRI Radiomics Model and Exploration of Biological Foundation

Yan Qin Tan, Yangyang Li
article en

Abstract

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.

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
Openalex Percentile: Top 64%
Radiomics and Machine Learning in Medical Imaging
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