Predictive value of cerebral perfusion and guanine nucleotide-binding protein, alpha-stimulating activity polypeptide in ischemic white matter lesions: a machine learning approach
In patients with ischemic WMLs, factors such as age, sex, history of cerebral infarction, GNAS levels, and specific perfusion metrics are predictive of WML progression. Advanced imaging and ML improve detection. GNAS levels correlated with Fazekas scores, indicating their downregulation in the hypoperfused white matter.
Authors
- Zongkai Wu
- Yu Ning
- Yajing Li (ORCID: https://orcid.org/0000-0001-8211-3137)
- Zhijie Dou (ORCID: https://orcid.org/0000-0003-4014-1222)
- Shuai Ma (ORCID: https://orcid.org/0000-0001-6416-642X)
- Hebo Wang (ORCID: https://orcid.org/0000-0002-0598-5772)
- Xiaoxuan Zhang (ORCID: https://orcid.org/0000-0002-6566-7880)
- Shengxian Jiao
Institutions
- Chengde Medical University (CN)
- Hebei General Hospital (CN)
- Chengde Medical University (CN)
- Hebei University of Chinese Medicine (CN)
Publication Details
- Journal
- Frontiers in Neurology
- Published
- 2025-10-29
- DOI
- https://doi.org/10.3389/fneur.2025.1612379
- Primary Topic
- Neurological Disease Mechanisms and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Chengde Medical University