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

Author

Listed:
  • 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
  • Tammie L S Benzinger

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

Suggested Citation

  • 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-Thom, 2018. "Integration of resting state functional MRI into clinical practice - A large single institution experience," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-16, June.
  • Handle: RePEc:plo:pone00:0198349
    DOI: 10.1371/journal.pone.0198349
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    1. J. L. Vincent & G. H. Patel & M. D. Fox & A. Z. Snyder & J. T. Baker & D. C. Van Essen & J. M. Zempel & L. H. Snyder & M. Corbetta & M. E. Raichle, 2007. "Intrinsic functional architecture in the anaesthetized monkey brain," Nature, Nature, vol. 447(7140), pages 83-86, May.
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