Resting-state Spontaneous Fluctuations in Brain Activity: A New Paradigm for Presurgical Planning Using fMRI

Shimony, Joshua S.; Zhang, Dongyang; Johnston, James M.; Fox, Michael D.; Roy, Abhik; Leuthardt, Eric C.

doi:10.1016/j.acra.2009.02.001

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Volume 16, Issue 5 , Pages 578-583, May 2009

Resting-state Spontaneous Fluctuations in Brain Activity:

A New Paradigm for Presurgical Planning Using fMRI

Mallinckrodt Institute of Radiology (J.S.S., D.Z., M.D.F., A.R.) and the Department of Neurosurgery (J.M.J., E.C.L.), Washington University School of Medicine, Campus Box 8131, 510 S Kingshighway Blvd, St Louis, MO 63110. This work was supported by Mallinckrodt Institute of Radiology startup funds, by grant K23 HD053212 (J.S.S.) from the National Institutes of Health (NIH; Bethesda, MD), and by grant F30MH083483 (D.Z.) from the National Institute of Mental Health (Bethesda, MD). This publication was made possible by grant UL1 RR024992 from the National Center for Research Resources (Bethesda, MD), a component of the NIH, and the NIH Roadmap for Medical Research

Received 6 October 2008; accepted 3 February 2009.

Rationale and Objectives

Task-evoked functional MRI (fMRI) has been used successfully in the study of brain function and clinically for presurgical localization of eloquent brain regions prior to the performance of brain surgery. This method requires patient cooperation and is not useful in young children or if the patient has cognitive dysfunction or physical impairment. An alternative method that can overcome some of these disadvantages measures the intrinsic function of the brain using resting-state fMRI. This method does not require any task performance and measures the spontaneous low-frequency (<0.1 Hz) fluctuations of the fMRI signal over time. Our objective in the present work is to provide preliminary information on the possible clinical utility of this technique for presurgical planning and on possible future applications.

Materials and Methods

Data from prior fMRI resting-state studies were reviewed for their potential use in preoperative mapping. Structural and resting-state fMRI data from normal subjects and patients with brain tumors were preprocessed and seed regions were placed in key regions of the brain; the related functional networks were identified using correlation analysis.

Results

Several key functional networks can be identified in patients with brain tumors from resting-state fMRI data.

Conclusion

Resting-state fMRI data can provide valuable presurgical information in many patients who cannot benefit from traditional task-based fMRI. Adoption of this method has the potential to improve individualized patient-centered care.

Key Words: Functional MRI, brain mapping, CNS tumors, neurosurgery, neuroradiology