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A Novel Data-Driven Approach to Preoperative Mapping of Functional Cortex Using Resting-State Functional Magnetic Resonance Imaging

Mitchell, Timothy J. PhD*,‡; Hacker, Carl D. BS§; Breshears, Jonathan D. MD*; Szrama, Nick P. BS§; Sharma, Mohit BS§; Bundy, David T. BS§; Pahwa, Mrinal BS§; Corbetta, Maurizio MD; Snyder, Abraham Z. PhD, MD; Shimony, Joshua S. MD, PhD; Leuthardt, Eric C. MD*,§,¶,#

doi: 10.1227/NEU.0000000000000141
Research-Human-Clinical Studies

BACKGROUND: Recent findings associated with resting-state cortical networks have provided insight into the brain's organizational structure. In addition to their neuroscientific implications, the networks identified by resting-state functional magnetic resonance imaging (rs-fMRI) may prove useful for clinical brain mapping.

OBJECTIVE: To demonstrate that a data-driven approach to analyze resting-state networks (RSNs) is useful in identifying regions classically understood to be eloquent cortex as well as other functional networks.

METHODS: This study included 6 patients undergoing surgical treatment for intractable epilepsy and 7 patients undergoing tumor resection. rs-fMRI data were obtained before surgery and 7 canonical RSNs were identified by an artificial neural network algorithm. Of these 7, the motor and language networks were then compared with electrocortical stimulation (ECS) as the gold standard in the epilepsy patients. The sensitivity and specificity for identifying these eloquent sites were calculated at varying thresholds, which yielded receiver-operating characteristic (ROC) curves and their associated area under the curve (AUC). RSNs were plotted in the tumor patients to observe RSN distortions in altered anatomy.

RESULTS: The algorithm robustly identified all networks in all patients, including those with distorted anatomy. When all ECS-positive sites were considered for motor and language, rs-fMRI had AUCs of 0.80 and 0.64, respectively. When the ECS-positive sites were analyzed pairwise, rs-fMRI had AUCs of 0.89 and 0.76 for motor and language, respectively.

CONCLUSION: A data-driven approach to rs-fMRI may be a new and efficient method for preoperative localization of numerous functional brain regions.

ABBREVIATIONS: AUC, area under the curve

BA, Brodmann area

BOLD, blood oxygen level dependent

ECS, electrocortical stimulation

fMRI, functional magnetic resonance imaging

ICA, independent component analysis

MLP, multilayer perceptron

MP-RAGE, magnetization-prepared rapid gradient echo

ROC, receiver-operating characteristic

rs-fMRI, resting-state functional magnetic resonance imaging

RSN, resting-state network

Departments of *Neurological Surgery,

Neurology,

§Biomedical Engineering, and

Mechanical Engineering and Material Sciences,

Mallinckrodt Institute of Radiology,

#Center for Innovation in Neuroscience and Technology, Washington University School of Medicine, St. Louis, Missouri

Correspondence: Eric C. Leuthardt, MD, Department of Neurosurgery, Washington University in St. Louis, School of Medicine, Campus Box 8057, 660 South Euclid, St. Louis, MO 63130. E-mail: leuthardte@wudosis.wustl.edu

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Web site (www.neurosurgery-online.com).

Received November 27, 2012

Accepted August 13, 2013

Copyright © by the Congress of Neurological Surgeons