Disrupted interhemispheric functional connectivity in primary angle-closure glaucoma: a functional MRI study:...

The purpose of the study is to use the voxel-mirrored homotopic connectivity (VMHC) technique to explore the pattern of the interhemispheric functional connectivity in patients with primary angle-closure glaucoma (PACG). The interhemispheric functional connectivity was compared between 31 individuals with PACG and 31 healthy controls closely matched with sex, age, and educational level using the VMHC technique. Significant differences in VMHC between two groups were selected to be classification features for classifying individuals with PACG from healthy controls using the support vector machine algorithm of the machine learning. We used the permutation test analysis to assess the classification performance. In addition, the Pearson analysis was applied to explore the relationship between changed VMHC and clinical varieties in patients with PACG. Compared with healthy controls, individuals with PACG exhibited significantly lower VMHC signal values in the right calcarine, right cuneus, right superior occipital gyrus, and right postcentral gyrus [voxel level: P < 0.001, Gaussian random field correction, cluster level: P < 0.05]. Moreover, the results displayed that the total accuracy, sensitivity, and specificity of the machine learning classification were 0.758, 0.710, and 0.807, respectively (P < 0.001, nonparametric permutation test). The findings demonstrated that there is disturbed interhemispheric resting-state functional connectivity in the vision-related brain areas of individuals with PACG; and the VMHC variability can classify individuals with PACG from healthy controls with high accuracy, which provided novel evidence for understanding the neuropathological mechanism of PACG.