Cerebral small vessel disease (CSVD) is a group of cerebrovascular system disease syndromes that involve perforating arteries, capillaries, and small veins. Because of the high incidence of CSVD in the elderly and its great harm, it is particularly important to identify and diagnose the diseases as early as possible. With the development of artificial intelligence technology, intelligent algorithms such as machine learning, deep learning, and computer neural networks are increasingly being applied in the medical field. This article reviews the application of artificial intelligence technology in the evaluation of CSVD imaging markers and blood biomarkers in recent years.

Vascular cognitive impairment (VCI) refers to a cognitive impairment syndrome caused by cerebrovascular disease and its risk factors, and encompasses a spectrum from mild cognitive impairment to vascular dementia. It is the second leading cause of dementia after Alzheimer's disease (AD). The clinical manifestations of VCI often overlap with neurological diseases such as AD, and its neuropathological changes are heterogeneous, lacking specificity in clinical diagnosis and treatment, thus delaying the optimal timing of treatment. In recent years, with the continuous development of brain structure-function coupling analysis methods based on multimodal MRI, the correlation between brain structure and function has been comprehensively revealed, which is helpful for exploring the pathological and physiological mechanisms of VCI. This article reviews the research progress on the application of multimodal MRI in VCI in recent years, including the study of brain structure function-coupling based on multimodal MRI.