No abstract

BACKGROUND AND PURPOSE:The default mode network normally decreases in activity during externally directed tasks. Although default mode network connectivity is disrupted in numerous brain pathologies, default mode network deactivation has not been studied in patients with brain tumors. We investigated default mode network deactivation with language task-based fMRI by measuring the anticorrelation of a critical default mode network node, the posterior cingulate cortex, in patients with gliomas and controls; furthermore, we examined default mode network functional connectivity in these patients with task-based and resting-state fMRI. MATERIALS AND METHODS:In 10 healthy controls and 30 patients with gliomas, the posterior cingulate cortex was identified on task-based fMRI and was used as an ROI to create connectivity maps from task-based and resting-state fMRI data. We compared the average correlation in each default mode network region between patients and controls for each correlation map and stratified patients by tumor location, hemisphere, and grade.RESULTS: Patients with gliomas (P ¼ .001) and, in particular, patients with tumors near the posterior default mode network (P , .001) showed less posterior cingulate cortex anticorrelation in task-based fMRI than controls. Patients with both left-and righthemisphere tumors, as well as those with grade IV tumors, showed significantly lower posterior cingulate cortex anticorrelation than controls (P = .02, .03, and ,.001, respectively). Functional connectivity in each default mode network region was not significantly different between task-based and resting-state maps.CONCLUSIONS: Task-based fMRI showed impaired deactivation of the default mode network in patients with gliomas. The functional connectivity of the default mode network in both task-based and resting-state fMRI in patients with gliomas using the posterior cingulate cortex identified in task-based fMRI as an ROI for seed-based correlation analysis has strong overlap. ABBREVIATIONS: BOLD ¼ blood oxygen level-dependent; DMN ¼ default mode network; FC ¼ functional connectivity; IPL ¼ inferior parietal lobule; LIPL ¼ left inferior parietal lobule; mPFC ¼ medial prefrontal cortex; PCC ¼ posterior cingulate cortex; RIPL ¼ right inferior parietal lobule; rs-fMRI ¼ resting-state fMRI; tb-fMRI ¼ task-based fMRI

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.

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.

No abstract

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 [mm 2 s -1 ]) in whole brain and tumor regions; and the tractography parameters: fiber FA, MD (mm 2 s -1 ), volume (mm 3 ), 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 (mm 2 s -1 ) and volume (mm 3 ) 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.

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.

Pre-surgical language mapping with functional magnetic resonance imaging (fMRI) is routinely conducted to assist the neurosurgeon in preventing damage to brain regions responsible for language. Functional differences exist between the monolingual versus the bilingual brain, whereas clinical fMRI tasks are typically conducted in a single language. The presence of secondary language processing mechanisms is a potential source of error in the inferred language map. From fMRI data of healthy bilingual and monolingual subjects we obtain language maps as functional networks. Our results show a sub-network "core" architecture consisting of the Broca's, pre-supplementary motor, and premotor areas present across all subjects. Wernicke's Area was found to connect to the "core" to a different extent across groups. The k core centrality measure shows "core" areas belong to the maximum core while WA and other fROIs vary across groups. The results may provide a benchmark to preserve equal treatment outcomes for bilingual patients.