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

Background: Previous studies have documented abnormal functional changes in the visual pathways and gray matter regions related to vision in Rhegmatogenous retinal detachment (RRD) patients. However, the extent of alterations in the functional and structural characteristics of white matter (WM) in these patients remains insufficiently understood.

Methods: In this study, we employed functional clustering networks and TractSeg methodologies to investigate the alterations in WM function and structure among patients with RRD. Subsequently, we applied a Support Vector Machine (SVM) algorithm to classify RRD patients and healthy controls (HCs).

Results: Compared to HCs, patients with RRD exhibited a marked reduction in Functional Covariance Connectivity (FCC) between the Superior Temporal Network and the Cerebellar Network. Concurrently, there was an elevation in WM amplitude within the Anterior Corpus Callosum Network among RRD patients. Moreover, significant differences were identified in WM fiber bundles linked to visual and cognitive functions. Notably, the visual acuity of RRD patients displayed a significant positive correlation with the amplitudes of the Brainstem Network and the Cerebellar Network. The SVM classification based on WM7_amplitude achieved the highest AUC value of 0.6694.

Conclusion: This study highlights abnormal changes in both the functional and structural integrity of WM in patients with RRD, which are likely directly linked to their cognitive and visual deficits. Furthermore, variations in the WM7_amplitude parameter may serve as a neurobiological marker for differentiating RRD patients from HCs. These findings offer profound insights into the underlying neural mechanisms contributing to the cognitive and visual impairments experienced by RRD patients.