Huang Huimin, Zheng Ning, Feng Lei, Shao Shuo
Radiological Medical College, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Department of Radiology, Jining No. 1 People's Hospital Affiliated to Shandong First Medical University, Jining, China.
Front Neurol. 2025 May 16;16:1581338. doi: 10.3389/fneur.2025.1581338. eCollection 2025.
Moyamoya disease (MMD), a chronic, progressive cerebrovascular disorder of unknown etiology, presents significant diagnostic and therapeutic challenges in clinical practice. Conventional diagnostic methods rely on physicians' experience and have limitations in disease prediction, risk assessment, and treatment decisions. The advancement of artificial intelligence (AI) technologies has created new opportunities for research on MMD. This review summarizes recent advances in AI applications for MMD, including diagnosis, risk factor analysis, treatment planning, outcome evaluation, and basic research. Additionally, this review critically examines the limitations of current research on MMD and explores potential future directions, aiming to offer valuable insights and guidance on MMD.
烟雾病（MMD）是一种病因不明的慢性、进行性脑血管疾病，在临床实践中面临着重大的诊断和治疗挑战。传统的诊断方法依赖于医生的经验，在疾病预测、风险评估和治疗决策方面存在局限性。人工智能（AI）技术的进步为烟雾病的研究创造了新的机会。本文综述了AI在烟雾病应用方面的最新进展，包括诊断、危险因素分析、治疗规划、疗效评估和基础研究。此外，本文还批判性地审视了当前烟雾病研究的局限性，并探索了潜在的未来方向，旨在为烟雾病提供有价值的见解和指导。
