As an extension of the central nervous system, the retina is the only tissue in the body that allows direct in vivo observation of both neural and vascular structures, offering a unique non-invasive window for the assessment of cerebral neurovascular diseases. Recent studies have shown that multimodal imaging techniques—such as fundus photography, optical coherence tomography(OCT), and OCT angiography(OCTA)—enable quantitative analysis of retinal indicators including vascular caliber, fractal dimension, retinal nerve fiber layer thickness, and microvascular density. These metrics can, to some extent, reflect the severity and progression risk of cerebrovascular and neurodegenerative diseases such as stroke, Alzheimer's disease, and Parkinson's disease. Consequently, retinal imaging holds promise as a powerful tool for early screening, risk stratification, and treatment monitoring. This article systematically reviews the application of retinal imaging technologies in the diagnosis and management of cerebral neurovascular disorders, with a particular focus on the important role of artificial intelligence(AI)-driven image analysis in enhancing screening efficiency, improving risk assessment accuracy, and promoting multidisciplinary collaborative care, thereby providing insights for clinical translation.

陕西省重点研发计划项目(No.2024SF-GJHX-38); 西安市科技计划项目(No.2025JH-YXYJZD-0057); 西京医院医务人员培养助推计划项目(No.XJZT25CX52)