An ALE Meta-Analysis of Specific Functional MRI Studies on Subcortical Vascular Cognitive Impairment - Xu, Wenwen; Song, Yu; Chen, Shanshan; Xue, Chen; Hu, Guanjie; Qi, Wenzhang; Ma, Wenying; Lin, Xingjian; Chen, Jiu (Frontiers in Neurology, 2021)
Background: Subcortical vascular cognitive impairment(sVCI), caused by cerebral small vessel diseases accounts for the majority of vascular cognitive impairment, is characterized by insidious onset and impaired memory and executive function. If not recognized early, it inevitably develops into vascular dementia. Currently, few quantitative studies on the consistent results of brain regions in sVCI patients can be used to predict dementia conversion. The purpose of the study was to explore the exact abnormalities within the brain in sVCI patients by combing the coordinates of previous articles. Methods: PubMed, Embase and Web of Science were thoroughly searched to obtain neuroimaging articles about the amplitude of low frequency fluctuation, regional homogeneity, and functional connectivity in sVCI patients. According to the activation likelihood estimation (ALE) algorithm, the meta-analysis based on coordinate and functional connectivity modelling were made. Results: The quantitative meta-analysis included 20 functional imaging studies with sVCI patients. Alterations in specific brain regions mainly concentrated on the frontal lobes including middle frontal gyrus, superior frontal gyrus, medial frontal gyrus and precentral gyrus, parietal lobes including precuneus, angular gyrus, postcentral gyrus and inferior parietal lobule, occipital lobes including lingual gyrus and cuneus, temporal lobes including fusiform gyrus and middle temporal gyrus and the limbic system including cingulate gyrus. These specific markers belonged to the important networks known such as default mode network, executive control network and visual network . Conclusions: The present study determined specific abnormal brain regions in sVCI patients and explored the important brain funtional networks. These findings objectively represent the exact abnormalities within the brain, which help further understand the pathogenesis of sVCI and find the potential imaging as a biomarker. What’s more, it may provide basis for new approaches to treatment.