Aberrant white matter function and structure in Rhegmatogenous retinal detachment: A study utilizing functional network clustering and TractSeg methods

Abstract

Rhegmatogenous retinal detachment (RRD) has been linked to abnormal functional changes in visual pathways and gray matter regions; however, alterations in white matter (WM) function and structure remain poorly understood. Using functional clustering networks and TractSeg methodologies, we investigated WM alterations in RRD patients and employed Support Vector Machine (SVM) algorithms for classification. RRD patients demonstrated reduced functional covariance connectivity (FCC) between the Superior Temporal Network and the Cerebellar Network, along with increased WM amplitude in the Anterior Corpus Callosum Network. Distinct differences in WM fiber bundles associated with visual and cognitive functions were observed, with visual acuity negatively correlating with amplitudes in the Occipital Networks. The SVM model based on WM7_amplitude achieved the highest AUC, highlighting its potential as a neurobiological marker for distinguishing RRD patients from healthy controls (HCs). These findings reveal critical disruptions in WM functional and structural integrity linked to cognitive and visual deficits in RRD, offering novel insights into the neural mechanisms underlying these impairments.