Use of Network Analysis to Establish Neurosurgical Parameters in Gliomas and Epilepsy

Cutting-edge neuroimaging technologies can facilitate preoperative evaluation in various neurosurgical settings. Surgery for gliomas and epilepsy requires precise localization for resection due to the need to preserve (or perhaps improve) higher cognitive functions. Accordingly, a hodological approach should be taken that considers subcortical networks as well as cortical functions within various functional domains. Resting state functional magnetic resonance imaging (fMRI) has the potential to provide new insights that are valuable for this approach. In this review, we describe recent developments in network analysis using resting state fMRI related to factors in glioma and epilepsy surgery: the identification of functionally dominant areas, evaluation of cognitive function by alteration of resting state networks (RSNs), glioma grading, and epileptic focus detection. One particular challenge that is close to realization is using fMRI for the identification of sensorimotor- and language-dominant areas during a task-free resting state. Various RSNs representative of the default mode network demonstrated at least some alterations in both patient groups, which correlated with behavioral changes including cognition, memory, and attention, and the development of psychosis. Still challenging is the detection of epileptic foci and propagation pathways when using only network analysis with resting state fMRI; however, a combined method with simultaneous electroencephalography has produced promising results. Consequently, network analysis is expected to continue to advance as neuroimaging technology improves in the next decade, and preoperative evaluation for neurosurgical parameters through these techniques should improve parallel with them.