MRI-based habitat imaging predicts high-risk molecular subtypes and early risk assessment of lower-grade gliomas
The MRI-based habitat model simultaneously achieves the objectives of non-invasive prediction of high-risk molecular subtypes of LrGGs and assessment of survival prognosis. This has incremental value for early non-invasive warning of malignant transformation in LrGGs and risk-stratified management.
Authors
- Guoqiang Yang (ORCID: https://orcid.org/0000-0001-8824-244X)
- Kai Wu (ORCID: https://orcid.org/0000-0002-4437-9468)
- Xiangli Yang (ORCID: https://orcid.org/0009-0008-3009-0218)
- Hui Zhang (ORCID: https://orcid.org/0000-0002-0565-0411)
- Wenju Niu
Institutions
- Shanxi Medical University (CN)
- First Hospital of Shanxi Medical University (CN)
- Shanxi Academy of Medical Sciences (CN)
Publication Details
- Journal
- Cancer Imaging
- Published
- 2025-03-28
- DOI
- https://doi.org/10.1186/s40644-025-00838-4
- Citations
- 4
- Primary Topic
- Glioma Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 6.50
Funders
- National Natural Science Foundation of China