title: Defining language networks from resting-state fMRI for surgical planning--a feasibility study.
abstract: Presurgical language mapping for patients with lesions close to language areas is critical to neurosurgical decision-making for preservation of language function. As a clinical noninvasive imaging technique, functional MRI (fMRI) is used to identify language areas by measuring blood-oxygen-level dependent (BOLD) signal change while patients perform carefully timed language vs. control tasks. This task-based fMRI critically depends on task performance, excluding many patients who have difficulty performing language tasks due to neurologic deficits. On the basis of recent discovery of resting-state fMRI (rs-fMRI), we propose a "task-free" paradigm acquiring fMRI data when patients simply are at rest. This paradigm is less demanding for patients to perform and easier for technologists to administer. We investigated the feasibility of this approach in right-handed healthy control subjects. First, group independent component analysis (ICA) was applied on the training group (14 subjects) to identify group level language components based on expert rating results. Then, four empirically and structurally defined language network templates were assessed for their ability to identify language components from individuals' ICA output of the testing group (18 subjects) based on spatial similarity analysis. Results suggest that it is feasible to extract language activations from rs-fMRI at the individual subject level, and two empirically defined templates (that focuses on frontal language areas and that incorporates both frontal and temporal language areas) demonstrated the best performance. We propose a semi-automated language component identification procedure and discuss the practical concerns and suggestions for this approach to be used in clinical fMRI language mapping.
authors.affiliation: Harvard Medical School, Boston, Massachusetts, USA; Department of Neurosurgery, Brigham and Women's Hospital, Boston, Massachusetts, USA.
authors.forename: Yanmei
authors.initials: Y
authors.lastname: Tie
authors.forename: Laura
authors.initials: L
authors.lastname: Rigolo
authors.forename: Isaiah H
authors.initials: IH
authors.lastname: Norton
authors.forename: Raymond Y
authors.initials: RY
authors.lastname: Huang
authors.forename: Wentao
authors.initials: W
authors.lastname: Wu
authors.forename: Daniel
authors.initials: D
authors.lastname: Orringer
authors.forename: Srinivasan
authors.initials: S
authors.lastname: Mukundan
authors.forename: Alexandra J
authors.initials: AJ
authors.lastname: Golby
mesh_terms: D000328:Adult; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000295:instrumentation / Q000379:methods*; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D007802:Language; D008279:Magnetic Resonance Imaging; D008297:Male; D009415:Nerve Net / Q000502:physiology*; D011300:Preoperative Care / Q000379:methods* / Q000592:standards; D012146:Rest / Q000502:physiology; D055815:Young Adult
keywords: functional connectivity; independent component analysis (ICA); language mapping; resting-state networks (RSNs); task-based fMRI; “task-free” paradigm