MRI quantified enlarged perivascular space volumes as imaging biomarkers correlating with severity of anxiety depression in young adults with long-time mobile phone use
The utilization of MRI-quantified EPVS metrics combined with machine-learning algorithms presents a promising method for evaluating severity of anxiety and depression symptoms in patients with LTMPU, which might introduce a non-invasive, objective, and quantitative approach to enhance diagnostic efficiency and guide personalized treatment strategies.
Authors
- Jiaojiao Wu (ORCID: https://orcid.org/0000-0003-2402-7825)
- Yalan Wu (ORCID: https://orcid.org/0000-0002-1092-7542)
- Feng Shi (ORCID: https://orcid.org/0000-0003-1522-9943)
- Bin Li (ORCID: https://orcid.org/0000-0001-8870-8393)
- Lizhou Chen
- Li Li (ORCID: https://orcid.org/0000-0001-8832-0575)
- Rui Hua (ORCID: https://orcid.org/0000-0001-7507-6155)
- 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 Psychiatry
- Published
- 2025-02-20
- DOI
- https://doi.org/10.3389/fpsyt.2025.1532256
- Primary Topic
- Advanced Neuroimaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Sichuan Province
- Key Research and Development Program of Sichuan Province