Power spectral analysis can determine language laterality from resting-state functional MRI data in healthy controls.

BACKGROUND AND PURPOSE: Resting-state functional magnetic resonance imaging (rsfMRI) has been proposed as an alternative to task-based fMRI including clinical situations such as preoperative brain tumor planning, due to advantages including ease of performance and time savings. However, one of its drawbacks is the limited ability to accurately lateralize language function. METHODS: Using the rsfMRI data of healthy controls, we carried out a power spectra analysis on three regions of interest (ROIs): Broca's area (BA) in the frontal cortex for language, hand motor (HM) area in the primary motor cortex, and the primary visual cortex (V1). Spike removal, motion correction, linear trend removal, and spatial smoothing were applied. Spontaneous low-frequency fluctuations (0.01-0.1 Hz) were filtered to enable functional integration. RESULTS: BA showed greater power on the left hemisphere relative to the right (p = .0055), while HM (p = .1563) and V1 (p = .4681) were not statistically significant. A novel index, termed the power laterality index (PLI), computed to estimate the degree of power lateralization for each brain region, revealed a statistically significant difference between BA and V1 (p < .00001), where V1 was used as a control since the primary visual cortex does not lateralize. Validation studies used to compare PLI to a laterality index computed using phonemic fluency, a task-based, language fMRI paradigm, demonstrated good correlation. CONCLUSIONS: The power spectra for BA revealed left language lateralization, which was not replicated in HM or V1. This work demonstrates the feasibility and validity of an ROI-based power spectra analysis on rsfMRI data for language lateralization.

Resting-state functional MRI language network connectivity differences in patients with brain tumors: exploration of the cerebellum and contralesional hemisphere.

Brain tumors can have far-reaching impacts on functional networks. Language processing is typically lateralized to the left hemisphere, but also involves the right hemisphere and cerebellum. This resting-state functional MRI study investigated the proximal and distal effects of left-hemispheric brain tumors on language network connectivity in the ipsilesional and contralesional hemispheres. Separate language resting-state networks were generated from seeding in ipsilesional (left) and contralesional (right) Broca's Area for 29 patients with left-hemispheric brain tumors and 13 controls. Inclusion criteria for all subjects included language left-dominance based on task-based functional MRI. Functional connectivity was analyzed in each network to the respective Wernicke's Area and contralateral cerebellum. Patients were assessed for language deficits prior to scanning. Compared to controls, patients exhibited decreased connectivity in the ipsilesional and contralesional hemispheres between the Broca's Area and Wernicke's Area homologs (mean connectivity for patients/controls: left 0.51/0.59, p < 0.002; right 0.52/0.59, p < 0.0002). No differences in mean connectivity to the contralateral cerebellum were observed between groups (p > 0.09). Crossed cerebro-cerebellar connectivity was correlated in controls (rho = 0.59, p < 0.05), patients without language deficits (rho = 0.74, p < 0.0002), and patients with high-grade gliomas (rho = 0.78, p < 0.0002), but not in patients with language deficits or low-grade gliomas (p > 0.l). These findings demonstrate that brain tumors impact the language network in the contralesional hemisphere and cerebellum, which may reflect neurological deficits and lesion-induced cortical reorganization.

Patient Preparation and Paradigm Design in fMRI.

Functional magnetic resonance imaging (fMRI) is useful for localizing eloquent cortex in the brain prior to neurosurgery. Language and motor paradigms offer a wide range of tasks to test brain regions within the language and motor networks. With the help of fMRI, hemispheric language dominance can be determined. It also is possible to localize specific motor and sensory areas within the motor and sensory gyri. These findings are critical for presurgical planning. The most important factor in presurgical fMRI is patient performance. Patient interview and instruction time are crucial to ensure that patients understand and comply with the fMRI paradigm.

Multiband diffusion tensor imaging for presurgical mapping of motor and language pathways in patients with brain tumors.

BACKGROUND AND PURPOSE: Assessment of the essential white matter fibers of arcuate fasciculus and corticospinal tract (CST), required for preoperative planning in brain tumor patients, relies on the reliability of diffusion tensor imaging (DTI). The recent development of multiband DTI (mb-DTI) based on simultaneous multislice excitation could maintain the overall quality of tractography while not exceeding standard clinical care time. To address this potential, we performed quantitative analyses to evaluate tractography results of arcuate fasciculus and CST acquired by mb-DTI in brain tumor patients. METHODS: We retrospectively analyzed 44 patients with brain lesions who underwent presurgical single-shot DTI (s-DTI) and mb-DTI. We measured DTI parameters: fractional anisotropy (FA) and mean diffusivity (MD [mm2 s-1 ]) in whole brain and tumor regions; and the tractography parameters: fiber FA, MD (mm2 s-1 ), volume (mm3 ), and length (mm) in the whole brain, arcuate fasciculus, and CST. Additionally, three neuroradiologists performed a blinded visual assessment comparing s-DTI with mb-DTI. RESULTS: The mb-DTI showed higher mean FA and lower MD (r > .95, p < .002) in whole brain and tumor regions of interest; slightly higher fiber FA, volume, and length; and slightly lower fiber MD in whole brain, arcuate fasciculus, and CST than in s-DTI. These differences were significant for fiber FA in all tracts; length (mm) in arcuate fasciculus; and fiber MD (mm2 s-1 ) and volume (mm3 ) in all patients with tumor involved in the arcuate fasciculus, CST, and whole brain tracts (p = .001). Visual assessment demonstrated that both techniques produced visually similar tracts. CONCLUSIONS: This study demonstrated the clinical potential and significant advantages of preoperative mb-DTI in brain tumor patients.

Monolingual and bilingual language networks in healthy subjects using functional MRI and graph theory.

Bilingualism requires control of multiple language systems, and may lead to architectural differences in language networks obtained from clinical fMRI tasks. Emerging connectivity metrics such as k-core may capture these differences, highlighting crucial network components based on resiliency. We investigated the influence of bilingualism on clinical fMRI language tasks and characterized bilingual networks using connectivity metrics to provide a patient care benchmark. Sixteen right-handed subjects (mean age 42-years; nine males) without neurological history were included: eight native English-speaking monolinguals and eight native Spanish-speaking (L1) bilinguals with acquired English (L2). All subjects underwent fMRI with gold-standard clinical language tasks. Starting from active clusters on fMRI, we inferred the persistent functional network across subjects and ran centrality measures to characterize differences. Our results demonstrated a persistent network "core" consisting of Broca's area, the pre-supplementary motor area, and the premotor area. K-core analysis showed that Wernicke's area was engaged by the "core" with weaker connection in L2 than L1.

Resting State Functional Connectivity of the Supplementary Motor Area to Motor and Language Networks in Patients with Brain Tumors.

BACKGROUND AND PURPOSE: We examined the resting-state functional connectivity (RSFC) of the supplementary motor area (SMA) in brain tumor patients. We compared the SMA subdivisions (pre-SMA, SMA proper, central SMA) in terms of RSFC projected from each region to the motor gyrus and language areas. METHODS: We retrospectively identified 14 brain tumor patients who underwent task-based and resting-state fMRI, and who completed motor and language paradigms that activated the SMA proper and pre-SMA, respectively. Regions of interest (ROIs) obtained from task-based fMRI were generated in both areas and the central SMA to produce RSFC maps. Degree of RSFC was measured from each subdivision to the motor gyrus and Broca's area (BA). RESULTS: All patients showed RSFC between the pre-SMA and language centers and between the SMA proper and motor gyrus. Thirteen of 14 patients showed RSFC from the central SMA to both motor and language areas. There was no significant difference between subdivisions in degree of RSFC to BA (pre-SMA, r = .801; central SMA, r = .803; SMA proper; r = .760). The pre-SMA showed significantly less RSFC to the motor gyrus (r = .732) compared to the central SMA (r = .842) and SMA proper (r = .883) (P = .016, P = .001, respectively). CONCLUSIONS: The region between the pre-SMA and SMA proper produces reliable RSFC to the motor gyrus and language areas in brain tumor patients. This study is the first to examine RSFC of the central SMA in this population. Consequently, our results provide further validation to previous studies, supporting the existence of a central SMA with connectivity to both motor and language networks.