MRI quantified enlarged perivascular space volumes as imaging biomarkers correlating with severity of anxiety depression in young adults with long-time mobile phone use

Datos Bibliográficos

ID15523864
AutoresLi Li (0000-0001-9700-9682), Yalan Wu (0000-0002-1092-7542, Stomatology Hospital, autor de correspondencia), Jiaojiao Wu (0000-0001-8962-1679, United Imaging Healthcare (China)), Bin Li (0000-0002-9633-0033, United Imaging Healthcare (China)), Rui Hua (0000-0003-2686-7991, United Imaging Healthcare (China)), Feng Shi (0000-0002-4433-6185, Sichuan University), Lizhou Chen (0000-0002-8181-270X, Sichuan University, autor de correspondencia), Yeke Wu (0000-0003-2318-3199, Stomatology Hospital)
Año2025
Volumen16
Páginas1532256-1532256
Fecha de publicación2025-02-20
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaFrontiers in Psychiatry (JOURNAL)
Identificadores de la revistaISSN: 1664-0640 • E-ISSN: 1664-0640
EditorialFrontiers Media (PUBLISHER • CH)
DOI10.3389/fpsyt.2025.1532256
PMID40051766
OpenAlexW4407798227
IdiomaEN
Referencias citadas8

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

Anxiety · Depression (economics · Magnetic resonance imaging · Psychiatry · Radiology · Advanced Neuroimaging Techniques and Applications · Cerebrospinal fluid and hydrocephalus · Clinical Psychology · Functional Brain Connectivity Studies · Medicine · Psychology