• World Neurosurg · Nov 2019

    Case Reports

    Resting-State Functional Magnetic Resonance Imaging for Brain Tumor Surgical Planning: Feasibility in Clinical Setting.

    • Gianvincenzo Sparacia, Giuseppe Parla, Roberto Cannella, Alessandro Perri, Vincenzina Lo Re, Giuseppe Mamone, Roberto Miraglia, Fabio Torregrossa, and Giovanni Grasso.
    • Radiology Service, Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, Palermo, Italy; Radiology Service, Department of Diagnostic and Therapeutic Services, Mediterranean Institute for Transplantation and Advanced Specialized Therapies, Palermo, Italy. Electronic address: gianvincenzo.sparacia@unipa.it.
    • World Neurosurg. 2019 Nov 1; 131: 356-363.

    AbstractThe aim of this study was to introduce resting-state functional magnetic resonance imaging (rest-fMRI) capability for brain tumor surgical planning. rest-fMRI is an emerging functional neuroimaging technique potentially able to provide new insights into brain physiology and to provide useful information regarding brain tumors in preoperative and postoperative settings. rest-fMRI evaluates low-frequency fluctuations in the blood oxygen level-dependent signal while the subject is at rest during magnetic resonance imaging examination. Multiple resting-state networks have been identified, including the somatosensory, language, and visual networks, which are of primary importance for surgical planning. We discuss the feasibility of rest-fMRI examination before and after surgical resection of brain tumors in routine clinical practice and the usefulness of the information obtained for surgical planning in brain tumor resection. rest-fMRI is particularly useful for patients who are unable to cooperate with the task-based paradigm, such as children or patients who are sedated, paretic, or aphasic. Although standardization and validation of rest-fMRI are still ongoing, this technique is feasible and valuable and can be implemented for routine clinical surgical planning.Copyright © 2019 Elsevier Inc. All rights reserved.

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