Predicting the molecular subtypes of 2021 WHO grade 4 glioma by a multiparametric MRI-based machine learning model
The multiparametric MRI ML model effectively distinguished astrocytoma, CNS WHO grade 4 from GBM, IDH-wt (WHO 2021) and differentiated astrocytoma, IDH-mut from astrocytoma, IDH-wt, CNS WHO grade 4. Additionally, the model provided reliable survival stratification for glioma patients across different molecular subtypes.
Authors
- Yan Qin Tan (ORCID: https://orcid.org/0000-0002-7529-9807)
- P. Shen (ORCID: https://orcid.org/0009-0005-8680-2577)
- Wenji Xu (ORCID: https://orcid.org/0000-0002-3057-8589)
- Guoqiang Yang (ORCID: https://orcid.org/0000-0001-8824-244X)
- Hui Zhang (ORCID: https://orcid.org/0000-0003-4206-4339)
- Jie Zhang
- Xiaochun Wang (ORCID: https://orcid.org/0000-0003-3148-4581)
- Jiangfeng Du (ORCID: https://orcid.org/0000-0002-8533-5509)
- Yangyang Li (ORCID: https://orcid.org/0009-0006-0058-6015)
- Zhiyi Zhang (ORCID: https://orcid.org/0000-0001-8345-6588)
Institutions
- Shanxi Medical University (CN)
- First Hospital of Shanxi Medical University (CN)
Publication Details
- Journal
- BMC Cancer
- Published
- 2025-07-14
- DOI
- https://doi.org/10.1186/s12885-025-14529-7
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 4.08
Funders
- National Natural Science Foundation of China
- Shanxi Scholarship Council of China