• Gianvincenzo Sparacia, Giuseppe Parla, Vincenzina Lo Re, Roberto Cannella, Giuseppe Mamone, Vincenzo Carollo, Massimo Midiri, and Giovanni Grasso.
• Radiology Service, Department of Biomedicine, Neurosciences and Advanced Diagnostics (BiND), University of Palermo, Palermo, Italy; Radiology Service, Department of Diagnostic and Therapeutic Services, Mediterranean Institute for Transplantation and Advanced Specialized Therapies (IRCCS-ISMETT), Palermo, Italy. Electronic address: gianvincenzo.sparacia@unipa.it.
• World Neurosurg. 2020 Sep 1; 141: e182-e194.

PurposeHigh-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."MethodsThis 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 connectivity 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.ResultsReliable topography of all 8 resting-state networks was successfully identified in each participant before surgical resection. Single-subject functional connectivity analysis showed functional disconnection for dorsal attention and salience networks, whereas the language 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.ConclusionsResting-state fMRI can reliably detect common functional connectivity networks in patients with glioma and has the potential to anticipate network alterations after surgical resection.Copyright © 2020 Elsevier Inc. All rights reserved.

28 keywords...

hide…