Abstract
Abstract BACKGROUND Although cognitive impairment is a prevalent long-term side effect in glioma survivors, predictive imaging-based markers remain inconsistent to date. Structural brain network topology could be altered by both the tumor and its’ treatment through reorganization of hubs (i.e. highly interconnected nodes). Here, we explored the role of nodal hub-related graph metrics in cognitive functioning. METHODS 48 WHO grade 2-3 adult glioma survivors ( > 1y post-therapy) and 42 matched controls, underwent a cognitive assessment. Cognitive scores were transformed into w-scores, corrected for age and education. Weighted nodal graph metrics were calculated based on diffusion weighted imaging. Hubs were calculated based on 4 nodal metrics. Significant differences in nodal graph metrics between patients and controls, and hubs versus non-hubs were tested in a repeated measures ANOVA, using Bonferroni correction for multiple testing. Significant group differences in nodal graph metrics were correlated to cognitive scores per domain. RESULTS In controls, 12/78 nodes were defined as hubs. In survivors, the left superior-parietal region and left putamen had a significantly lower likelihood of being a hub (p< .001). These areas showed assortativity to be positively correlated with attention, language and executive function (r(90) > .51,p< .001) and characteristic path length to be negatively correlated with all cognitive domains (r(90) > .51, p< .001). Nodal metrics of clustering coefficient, characteristic path length, local efficiency and assortativity were significantly different between groups in both hub and non-hub regions (p< .001). Except for betweenness centrality, all nodal metrics strongly correlated with cognitive outcomes, occurring more often in hubs (33-50%) than intermediate hubs (10-33%) or non-hubs (4-12%). CONCLUSION Reorganization of hubs is frequently observed in this cohort of glioma survivors. Hub connectivity seems to be important in cognitive functioning, more than for non-hub regions. Therefore, structural nodal hub-related graph metrics might be important in predicting cognitive outcomes.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
