Resting-State Functional Connectome in Patients with Brain Tumors Before and After Surgical Resection Gianvincenzo Sparacia 1,3 , Giuseppe Parla 3 , Vincenzina Lo Re 4 , Roberto Cannella 1 , Giuseppe Mamone 3 , Vincenzo Carollo 3 , Massimo Midiri 1 , Giovanni Grasso 2 - PURPOSE: High-grade glioma surgery has evolved around the principal belief that a safe maximal tumor resection improves symptoms, quality of life, and survival. Mapping brain function has been recently improved by resting-state functional magnetic resonance imaging (rest- fMRI), a novel imaging technique that explores networks connectivity at “rest.” - METHODS: This prospective study analyzed 10 patients with high-grade glioma in whom rest-fMRI connectivity was assessed both in single-subject and in group analysis before and after surgery. Seed-based functional connec- tivity analysis was performed with CONN toolbox. Network identification focused on 8 major functional connectivity networks. A voxel-wise region of interest (ROI) to ROI correlation map to assess functional connectivity throughout the whole brain was computed from a priori seeds ROI in specific resting-state networks before and after surgical resection in each patient. - RESULTS: Reliable topography of all 8 resting-state networks was successfully identified in each participant before surgical resection. Single-subject functional con- nectivity analysis showed functional disconnection for dorsal attention and salience networks, whereas the lan- guage network demonstrated functional connection either in the case of left temporal glioblastoma. Functional connectivity in group analysis showed wide variations of functional connectivity in the default mode, salience, and sensorimotor networks. However, salience and language networks, salience and default mode networks, and salience and sensorimotor networks showed a significant correlation (P uncorrected <0.0025; P false discovery rate <0.077) in comparison before and after surgery confirming non-disconnection of these networks. - CONCLUSIONS: Resting-state fMRI can reliably detect common functional connectivity networks in patients with glioma and has the potential to anticipate network alter- ations after surgical resection. INTRODUCTION S urgical resection of focal brain tumors aims to maximize the resection while preserving brain function. Mapping brain function was recently improved by a novel imaging technique that explores distributed connectivity networks at “rest,” which requires minimal participant collaboration. Resting- state functional magnetic resonance imaging (rest-fMRI) repre- sents a novel tool to study brain functional network connectivity associated with both normal and pathologic neurologic function. This novel imaging technique is based on the quantification of Key words - Brain mapping - Brain tumors - Functional connectivity - Resting-state fMRI Abbreviations and Acronyms BOLD: Blood oxygen level dependent DMN: Default mode network EOR: Extent of resection FDR: False discovery rate fMRI: Functional magnetic resonance imaging KPS: Karnofsky performance status MR: Magnetic resonance rest-fMRI: Resting-state functional magnetic resonance imaging ROI: Region of interest RSNs: Resting-state networks From the 1 Radiology Service and 2 Neurosurgical Unit, Department of Biomedicine, Neurosciences and Advanced Diagnostics (BiND), University of Palermo, Palermo; and 3 Radiology Service, Department of Diagnostic and Therapeutic Services, and 4 Neurology Service, Mediterranean Institute for Transplantation and Advanced Specialized Therapies (IRCCS-ISMETT), Palermo, Italy To whom correspondence should be addressed: Gianvincenzo Sparacia, M.D. [E-mail: gianvincenzo.sparacia@unipa.it] Citation: World Neurosurg. (2020). https://doi.org/10.1016/j.wneu.2020.05.054 Journal homepage: www.journals.elsevier.com/world-neurosurgery Available online: www.sciencedirect.com 1878-8750/$ - see front matter ª 2020 Elsevier Inc. All rights reserved. WORLD NEUROSURGERY -: e1-e13, - 2020 www.journals.elsevier.com/world-neurosurgery e1 Original Article