Magnetic Resonance Imaging in Cerebral Small Vessel Disease-Related Depression: From Visual Scoring to Artificial Intelligence

IF 6.6 1区医学 Q1 NEUROSCIENCES

CNS Neuroscience & Therapeutics Pub Date : 2026-09-30 DOI:10.1002/cns.71188

Chaofang Lei, Jiaxu Chen, Yilong Wang

{"title":"Magnetic Resonance Imaging in Cerebral Small Vessel Disease-Related Depression: From Visual Scoring to Artificial Intelligence","authors":"Chaofang Lei, Jiaxu Chen, Yilong Wang","doi":"10.1002/cns.71188","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Cerebral small vessel disease (CSVD) is the key pathological basis of vascular depression. The precise identification of its neuroimaging markers is of core value for early diagnosis, elucidation of its pathological mechanism, and individualized treatment. Recent advances in magnetic resonance imaging (MRI) and artificial intelligence (AI) have enabled automated, high-throughput characterization of CSVD-related brain lesions. However, the translation of these technical advances into clinical tools for depression-specific prediction and classification remains at an early stage.</p>\n </section>\n \n <section>\n \n <h3> Results and Conclusion</h3>\n \n <p>This manuscript aims to summarize the application of traditional visual scoring systems in assessing the burden of CSVD and its association with depressive symptoms. Review the current status of imaging and AI research on CSVD-related depression. To provide a direction for the development of more precise and efficient imaging diagnostic tools for the future, and ultimately promote the practical application and utilization of precision medicine in the field of CSVD-related depression.</p>\n </section>\n </div>","PeriodicalId":154,"journal":{"name":"CNS Neuroscience & Therapeutics","volume":"32 10","pages":""},"PeriodicalIF":6.6000,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13627875/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"CNS Neuroscience & Therapeutics","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cns.71188","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}

引用次数: 0

Abstract

Background

Cerebral small vessel disease (CSVD) is the key pathological basis of vascular depression. The precise identification of its neuroimaging markers is of core value for early diagnosis, elucidation of its pathological mechanism, and individualized treatment. Recent advances in magnetic resonance imaging (MRI) and artificial intelligence (AI) have enabled automated, high-throughput characterization of CSVD-related brain lesions. However, the translation of these technical advances into clinical tools for depression-specific prediction and classification remains at an early stage.

Results and Conclusion

This manuscript aims to summarize the application of traditional visual scoring systems in assessing the burden of CSVD and its association with depressive symptoms. Review the current status of imaging and AI research on CSVD-related depression. To provide a direction for the development of more precise and efficient imaging diagnostic tools for the future, and ultimately promote the practical application and utilization of precision medicine in the field of CSVD-related depression.

查看原文本刊更多论文

磁共振成像在脑血管病相关抑郁中的应用：从视觉评分到人工智能。

背景：脑血管病（CSVD）是血管抑制的重要病理基础。准确识别其神经影像学标志物对早期诊断、阐明其病理机制和个体化治疗具有核心价值。磁共振成像（MRI）和人工智能（AI）的最新进展使csvd相关脑病变的自动化、高通量表征成为可能。然而，将这些技术进步转化为抑郁症特异性预测和分类的临床工具仍处于早期阶段。结果与结论：本文旨在总结传统视觉评分系统在评估心血管疾病负担及其与抑郁症状的关系中的应用。综述csvd相关抑郁的影像学和人工智能研究现状。为未来开发更精确、高效的影像诊断工具提供方向，最终促进精准医学在csvd相关抑郁症领域的实际应用和利用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

CNS Neuroscience & Therapeutics 医学-神经科学

CiteScore

7.30

自引率

12.70%

发文量

240

审稿时长

2 months

期刊介绍： CNS Neuroscience & Therapeutics provides a medium for rapid publication of original clinical, experimental, and translational research papers, timely reviews and reports of novel findings of therapeutic relevance to the central nervous system, as well as papers related to clinical pharmacology, drug development and novel methodologies for drug evaluation. The journal focuses on neurological and psychiatric diseases such as stroke, Parkinson’s disease, Alzheimer’s disease, depression, schizophrenia, epilepsy, and drug abuse.