Cnsc-05. local and global functional connectome disruption in patients with gliomas

Abstract The aim of the study was to map the disruption of functional connectome in patients with gliomas using resting-state functional MRI (rs-fMRI) acquired before surgery (3T scanner). 54 patients with gliomas were included (M = 34, mean age = 50.8 y). Manual segmentation of lesions was performed on T1w and T2w MRI scans. Whole-brain measures of network centrality, modularity, integration and segregation were computed for a set of Regions of Interest (ROIs) including the Harvard Oxford anatomical atlas and tumor-related ROIs (i.e., edema, solid tumor, necrotic core). The analysis was performed on adjacency matrices obtained with a cost of 0.15, i.e. considering the 15% of the edges with the largest correlation coefficient values for each subject. A p< 0.05, two-sided, FDR corrected threshold was used for statistical analysis. In newly diagnosed patients (n = 18), we found a decrease of Integration (Degree, Global Efficiency) and Centrality (Betweenness Centrality) and an increase of Segregation (Local Efficiency) in the tumor ROIs compared to healthy brain regions. A similar integration/segregation imbalance pattern was present across the edema, solid tumor and necrotic core, with the edema being the most similar to healthy grey matter and the necrosis being the more altered, possibly reflecting tumor cells’ density and neuronal disruption. In patients at recurrence (n = 36), the same pattern was found, though with a less clear separation among tissue classes, possibly due to the altered anatomical/functional environment caused by functional plastic rearrangement and the effects the treatment(s). Finally, a significant correlation with overall survival was found for local efficiency values of the edema (p< 0.05, r 0,53=, R2 = 28%). We found significant alterations of functional connectome measures in brain regions affected by the tumor, with a decrease of network integration and an increase of network segregation measures characterizing different levels of tumor infiltration and potentially correlating with clinical outcomes.