الفهرس | Only 14 pages are availabe for public view |
Abstract Preoperative assessment of brain tumors is essential for surgical planning and can predict post-operative outcome. Resting state functional MRI is a functional imaging method that allows the localization of functional brain areas without the need for patient cooperation. In this study, we performed Resting state functional MRI on 22 patients with supratentorial tumors and analyzed the results using both independent component analysis and Seed based analysis. Our results show the ability of both methods to detect sensorimotor networks as well as the ability of independent component analysis to detect other networks to variable degrees. We reported the correlation between the extracted functional connectivity maps and post-operative clinical outcome, Finally, changes in brain connectomics between the pre and post-operative periods are reported. Our results demonstrate the applicability of Resting state functional MRI for localizing different functional brain areas in preoperative assessment, representing a step in further integration of computational radiology research in a clinical setting |