AUTHOR=Chen Ri-Bo , Zhong Yu-Lin , Liu Hui , Huang Xin 

TITLE=Machine learning analysis reveals abnormal functional network hubs in the primary angle-closure glaucoma patients

JOURNAL=Frontiers in Human Neuroscience

VOLUME=Volume 16 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2022.935213

DOI=10.3389/fnhum.2022.935213

ISSN=1662-5161

ABSTRACT=Background: Previous neuroimaging studies demonstrated that primary angle-closure glaucoma (PACG) patients were accompanied by vision and vision-related brain regions changes. However, whether the whole-brain functional network hub changes occur in PACG patients remains unknown. 
Purpose: The purpose of the study was to investigate the brain function network hubs changes in PACG patients using the voxel-wise degree centrality(DC) method.                                                        Materials and methods: Thirty-one PACG patients (21 male and 10 female) and 31 healthy controls (21 male and 10 female) closely matched in age, sex, and education were enrolled in the study. DC method was applied to investigate the brain function network hubs changes in PACG patients. Moreover, the SVM method was applied to distinguishing PACG patient and HC patients.
Results: Compared with HC, PACG patients had significantly higher DC values in the right fusiform, left middle temporal gyrus and left Cerebelum_4_5. Meanwhile, PACG patients had significantly lower DC values in the right calcarine, right postcentral gyrus, left precuneus gyrus and left postcentral gyrus. Furthermore, The SVM classification reaches a total accuracy of 72.58% and the ROC curve of the SVM classifier with an AUC value of 0.85.(r=0.25)
Conclusion: Our results highlight that .PACG patients showed widespread brain functional network hubs dysfunction relative to visual network, auditory network, default mode network and cerebellum network, which might be shed light on the neural mechanism of optic atrophy in PACG patients.