Integration of resting state functional MRI into clinical practice - A large single institution experience

Eric C Leuthardt, Gloria Guzman, S Kathleen Bandt, Carl Hacker, Ananth K Vellimana, David Limbrick, Mikhail Milchenko, Pamela Lamontagne, Benjamin Speidel, Jarod Roland, Michelle Miller-Thomas, Abraham Z Snyder, Daniel Marcus, Joshua Shimony and Tammie L S Benzinger

PLOS ONE, 2018, vol. 13, issue 6, 1-16

Abstract: Functional magnetic resonance imaging (fMRI) is an important tool for pre-surgical evaluation of eloquent cortex. Classic task-based paradigms require patient participation and individual imaging sequence acquisitions for each functional domain that is being assessed. Resting state fMRI (rs-fMRI), however, enables functional localization without patient participation and can evaluate numerous functional domains with a single imaging session. To date, post-processing of this resting state data has been resource intensive, which limits its widespread application for routine clinical use. Through a novel automated algorithm and advanced imaging IT structure, we report the clinical application and the large-scale integration of rs-fMRI into routine neurosurgical practice. One hundred and ninety one consecutive patients underwent a 3T rs-fMRI, 83 of whom also underwent both motor and language task-based fMRI. Data were processed using a novel, automated, multi-layer perceptron algorithm and integrated into stereotactic navigation using a streamlined IT imaging pipeline. One hundred eighty-five studies were performed for intracranial neoplasm, 14 for refractory epilepsy and 33 for vascular malformations or other neurological disorders. Failure rate of rs-fMRI of 13% was significantly better than that for task-based fMRI (38.5%,) (p

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0198349

DOI: 10.1371/journal.pone.0198349

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