Accelerated brain age in Moyamoya disease patients: a deep learning approach and correlation with disease severity
The DenseNet based model effectively predicts brain age, revealing that MMD patients experience accelerated brain aging correlated with disease severity. These findings highlight the potential of brain age prediction as a biomarker for MMD, aiding in personalized treatment strategies and early intervention. Future research should explore multi-center datasets and longitudinal data to validate and extend these findings.
Authors
- Qihang Zhang (ORCID: https://orcid.org/0000-0003-3217-7903)
- Xiaolin Ji
- Xin Chen (ORCID: https://orcid.org/0000-0003-3561-2691)
- H. J. Yang (ORCID: https://orcid.org/0009-0004-8274-9863)
- Wenjie Li (ORCID: https://orcid.org/0000-0003-3811-4970)
- Tao Wang (ORCID: https://orcid.org/0000-0002-5798-160X)
- Yan Zhang (ORCID: https://orcid.org/0000-0002-7017-5186)
- Huan Zhu
- Suhua Chen (ORCID: https://orcid.org/0000-0002-6114-9779)
- Chenyu Zhu
Institutions
- Capital Medical University (CN)
- Peking University (CN)
- Beijing Tian Tan Hospital (CN)
- Peking University Third Hospital (CN)
Publication Details
- Journal
- Frontiers in Neuroscience
- Published
- 2025-09-25
- DOI
- https://doi.org/10.3389/fnins.2025.1668993
- Primary Topic
- Moyamoya disease diagnosis and treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00