Graph Network Analysis for Predicting Cognitive and Survival Outcomes in Glioma Patients

Abstract

Graph theory provides a framework for analyzing brain networks. This review explores the role of graph network analysis in predicting cognitive function and overall survival (OS) in glioma patients, focussing on studies that applied graph theory metrics to evaluate cognitive and survival outcomes in glioma patients. Various studies showed that graph network alterations in glioma patients were associated with cognitive decline and worse OS. Small-world network properties were disrupted, with reductions in global efficiency and clustering coefficients correlating with neurocognitive deficits. Network hubs, which are critical for brain integration, were significantly affected, further contributing to functional impairments. These findings have implications for personalized neurosurgical planning and patient prognosis.