MRI-based machine learning analysis of perivascular spaces and their link to sleep disturbances, dementia, and mental distress in young adults with long-time mobile phone use
Computational EPVSs metrics offer insights into the EPVSs pathophysiology and its links to mood disorders, sleep disturbances, and cognitive impairment in LTMPU patients. These findings also highlight potential connections between EPVSs, excessive daytime sleepiness, and anxiety, contributing to a comprehensive understanding of these multifaceted conditions.
Authors
- Jiaojiao Wu (ORCID: https://orcid.org/0000-0003-2402-7825)
- Feng Shi (ORCID: https://orcid.org/0000-0002-2407-1239)
- Yalan Wu (ORCID: https://orcid.org/0000-0002-1092-7542)
- Rui Hua (ORCID: https://orcid.org/0000-0003-3586-7862)
- Lizhou Chen
- Li M. Li (ORCID: https://orcid.org/0000-0001-6062-4649)
- Bin Li (ORCID: https://orcid.org/0000-0002-7123-6286)
- Yeke Wu (ORCID: https://orcid.org/0000-0003-2318-3199)
Institutions
- Sichuan University (CN)
- West China Hospital of Sichuan University (CN)
- Stomatology Hospital (CN)
- United Imaging Healthcare (China) (CN)
- Chengdu University of Traditional Chinese Medicine (CN)
Publication Details
- Journal
- Frontiers in Neuroscience
- Published
- 2025-04-28
- DOI
- https://doi.org/10.3389/fnins.2025.1555054
- Citations
- 1
- Primary Topic
- Cerebrospinal fluid and hydrocephalus
- Type
- article
- Field-Weighted Citation Impact
- 0.91
Funders
- National Natural Science Foundation of China