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

Abstract

Graph theory provides a framework for analyzing brainnetworks. This review explores the role of graph networkanalysis in predicting cognitive function and overallsurvival (OS) in glioma patients, focussing on studies thatapplied graph theory metrics to evaluate cognitive andsurvival outcomes in glioma patients.Various studies showed that graph network alterations inglioma patients were associated with cognitive declineand worse OS. Small-world network properties weredisrupted, with reductions in global efficiency andclustering coefficients correlating with neurocognitivedeficits. Network hubs, which are critical for brainintegration, were significantly affected, furthercontributing to functional impairments. These findingshave implications for personalized neurosurgicalplanning and patient prognosis.