Retrospective analysis of hemispheric structural network change as a function of location and size of glioma Shawn D’Souza, 1,2 Lisa Hirt, 2,3,4 David R. Ormond 2 and John A. Thompson 2,3,4 Gliomas are neoplasms that arise from glial cell origin and represent the largest fraction of primary malignant brain tumours (77%). These highly infiltrative malignant cell clusters modify brain structure and function through expansion, invasion and intra- tumoral modification. Depending on the growth rate of the tumour, location and degree of expansion, functional reorganization may not lead to overt changes in behaviour despite significant cerebral adaptation. Studies in simulated lesion models and in patients with stroke reveal both local and distal functional disturbances, using measures of anatomical brain networks. Investigations over the last two decades have sought to use diffusion tensor imaging tractography data in the context of intracranial tumours to improve surgical planning, intraoperative functional localization, and post-operative interpretation of functional change. In this study, we used diffusion tensor imaging tractography to assess the impact of tumour location on the white matter structural network. To better understand how various lobe localized gliomas impact the topology underlying efficiency of information transfer between brain regions, we identified the major alterations in brain network connectivity patterns between the ipsilesional versus contralesional hemispheres in patients with gliomas localized to the frontal, parietal or temporal lobe. Results were indicative of altered network efficiency and the role of specific brain regions unique to different lobe localized gliomas. This work draws attention to connections and brain regions which have shared structural susceptibility in frontal, parietal and temporal lobe glioma cases. This study also provides a preliminary anatomical basis for understanding which affected white matter pathways may contribute to preoperative patient symptomology. 1 MD Program, Virginia Commonwealth University, School of Medicine, Richmond, VA, USA 2 Department of Neurosurgery, University of Colorado School of Medicine, Aurora, CO, USA 3 Department of Neurosurgery, University of Colorado School of Medicine, Aurora, CO, USA 4 Masters of Science in Modern Human Anatomy Program, University of Colorado School of Medicine, Aurora, CO, USA Correspondence to: John A. Thompson University of Colorado School of Medicine, Department of Neurosurgery, RC2 5119 12800 E. 19th Ave. Aurora, CO 80045, USA E-mail: john.a.thompson@cuanschutz.edu Keywords: DTI, graph network, glioma, structural connectivity Abbreviations: AAL2 ¼ automated anatomic labelling atlas 2; BC ¼ betweenness centrality; CC ¼ cluster coefficient; DTI ¼ diffu- sion tensor imaging; EC ¼ eigenvector centrality; FA ¼ fractional anisotropy; GBM ¼ glioblastoma; LE ¼ local efficiency; MD ¼ mean diffusivity; MNI ¼ Montreal Neurological Institute Received June 6, 2020. Revised September 23, 2020. Accepted October 9, 2020. Advance Access publication December 17, 2020 V C The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. B BR AIN COMMUNICATIONS AIN COMMUNICATIONS doi:10.1093/braincomms/fcaa216 BRAIN COMMUNICATIONS 2020: Page 1 of 17 | 1 Downloaded from https://academic.oup.com/braincomms/article/3/1/fcaa216/6040732 by guest on 01 December 2022