Evolutionary Strategies Enable Systematic and Reliable Uncertainty Quantification: A Proof-of-Concept Pilot Study on Resting-State Functional MRI Language Lateralization.

Reliable and trustworthy artificial intelligence (AI), particularly in high-stake medical diagnoses, necessitates effective uncertainty quantification (UQ). Existing UQ methods using model ensembles often introduce invalid variability or computational complexity, rendering them impractical and ineffective in clinical workflow. We propose a UQ approach based on deep neuroevolution (DNE), a data-efficient optimization strategy. Our goal is to replicate trends observed in expert-based UQ. We focused on language lateralization maps from resting-state functional MRI (rs-fMRI). Fifty rs-fMRI maps were divided into training/testing (30:20) sets, representing two labels: "left-dominant" and "co-dominant." DNE facilitated acquiring an ensemble of 100 models with high training and testing set accuracy. Model uncertainty was derived from distribution entropies over the 100 model predictions. Expert reviewers provided user-based uncertainties for comparison. Model (epistemic) and user-based (aleatoric) uncertainties were consistent in the independently and identically distributed (IID) testing set, mainly indicating low uncertainty. In a mostly out-of-distribution (OOD) holdout set, both model and user-based entropies correlated but displayed a bimodal distribution, with one peak representing low and another high uncertainty. We also found a statistically significant positive correlation between epistemic and aleatoric uncertainties. DNE-based UQ effectively mirrored user-based uncertainties, particularly highlighting increased uncertainty in OOD images. We conclude that DNE-based UQ correlates with expert assessments, making it reliable for our use case and potentially for other radiology applications.

Tumors Affect the Metabolic Connectivity of the Human Brain Measured by 18F-FDG PET.

PURPOSE: 18F-FDG PET captures the relationship between glucose metabolism and synaptic activity, allowing for modeling brain function through metabolic connectivity. We investigated tumor-induced modifications of brain metabolic connectivity. PATIENTS AND METHODS: Forty-three patients with left hemispheric tumors and 18F-FDG PET/MRI were retrospectively recruited. We included 37 healthy controls (HCs) from the database CERMEP-IDB-MRXFDG. We analyzed the whole brain and right versus left hemispheres connectivity in patients and HC, frontal versus temporal tumors, active tumors versus radiation necrosis, and patients with high Karnofsky performance score (KPS = 100) versus low KPS (KPS < 70). Results were compared with 2-sided t test (P < 0.05). RESULTS: Twenty high-grade glioma, 4 low-grade glioma, and 19 metastases were included. The patients' whole-brain network displayed lower connectivity metrics compared with HC (P < 0.001), except assortativity and betweenness centrality (P = 0.001). The patients' left hemispheres showed decreased similarity, and lower connectivity metrics compared with the right (P < 0.01), with the exception of betweenness centrality (P = 0.002). HC did not show significant hemispheric differences. Frontal tumors showed higher connectivity metrics (P < 0.001) than temporal tumors, but lower betweenness centrality (P = 4.5-7). Patients with high KPS showed higher distance local efficiency (P = 0.01), rich club coefficient (P = 0.0048), clustering coefficient (P = 0.00032), betweenness centrality (P = 0.008), and similarity (P = 0.0027) compared with low KPS. Patients with active tumor(s) (14/43) demonstrated significantly lower connectivity metrics compared with necroses. CONCLUSIONS: Tumors cause reorganization of metabolic brain networks, characterized by formation of new connections and decreased centrality. Patients with frontal tumors retained a more efficient, centralized, and segregated network than patients with temporal tumors. Stronger metabolic connectivity was associated with higher KPS.

Functional MRI in Neuro-Oncology: State of the Art and Future Directions.

Since its discovery in the early 1990s, functional MRI (fMRI) has been used to study human brain function. One well-established application of fMRI in the clinical setting is the neurosurgical planning of patients with brain tumors near eloquent cortical areas. Clinical fMRI aims to preoperatively identify eloquent cortices that serve essential functions in daily life, such as hand movement and language. The primary goal of neurosurgery is to maximize tumor resection while sparing eloquent cortices adjacent to the tumor. When a lesion presents in the vicinity of an eloquent cortex, surgeons may use fMRI to plan their best surgical approach by determining the proximity of the lesion to regions of activation, providing guidance for awake brain surgery and intraoperative brain mapping. The acquisition of fMRI requires patient preparation prior to imaging, determination of functional paradigms, monitoring of patient performance, and both processing and analysis of images. Interpretation of fMRI maps requires a strong understanding of functional neuroanatomy and familiarity with the technical limitations frequently present in brain tumor imaging, including neurovascular uncoupling, patient compliance, and data analysis. This review discusses clinical fMRI in neuro-oncology, relevant ongoing research topics, and prospective future developments in this exciting discipline.

Association of Lack of Speech Arrest During Cortical Stimulation With Interhemispheric Reorganization of the Functional Language Network in Patients With Brain Tumors.

BACKGROUND. Brain tumors induce language reorganization, which may influence the extent of resection in surgical planning. Direct cortical stimulation (DCS) allows definitive language mapping during awake surgery by locating areas of speech arrest (SA) surrounding the tumor. Although functional MRI (fMRI) combined with graph theory analysis can illustrate whole-brain network reorganization, few studies have corroborated these findings with DCS intraoperative mapping and clinical language performance. OBJECTIVE. We evaluated whether patients with low-grade gliomas (LGGs) without SA during DCS show increased right-hemispheric connections and better speech performance compared with patients with SA. METHODS. We retrospectively recruited 44 consecutive patients with left perisylvian LGG, preoperative language task-based fMRI, speech performance evaluation, and awake surgery with DCS. We generated language networks from ROIs corresponding to known language areas (i.e., language core) on fMRI using optimal percolation. Language core connectivity in the left and right hemispheres was quantified as fMRI laterality index (LI) and connectivity LI on the basis of fMRI activation maps and connectivity matrices. We compared fMRI LI and connectivity LI between patients with SA and without SA and used multivariable logistic regression (p < .05) to assess associations between DCS and connectivity LI, fMRI LI, tumor location, Broca area and Wernicke area involvement, prior treatments, age, handedness, sex, tumor size, and speech deficit before surgery, within 1 week after surgery, and 3-6 months after surgery. RESULTS. Patients with SA showed left-dominant connectivity; patients without SA lateralized more to the right hemisphere (p < .001). Between patients with SA and those without, fMRI LI was not significantly different. Patients without SA showed right-greater-than-left connectivity of Broca area and premotor area compared with patients with SA. Regression analysis showed significant association between no SA and right-lateralized connectivity LI (p < .001) and fewer speech deficits before (p < .001) and 1 week after (p = .02) surgery. CONCLUSION. Patients without SA had increased right-hemispheric connections and right translocation of the language core, suggesting language reorganization. Lack of interoperative SA was associated with fewer speech deficits both before and immediately after surgery. CLINICAL IMPACT. These findings support tumor-induced language plasticity as a compensatory mechanism, which may lead to fewer postsurgical deficits and allow extended resection.

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.

Effect of tumor genetics, pathology, and location on fMRI of language reorganization in brain tumor patients.

OBJECTIVES: Language reorganization may follow tumor invasion of the dominant hemisphere. Tumor location, grade, and genetics influence the communication between eloquent areas and tumor growth dynamics, which are drivers of language plasticity. We evaluated tumor-induced language reorganization studying the relationship of fMRI language laterality to tumor-related variables (grade, genetics, location), and patient-related variables (age, sex, handedness). METHODS: The study was retrospective cross-sectional. We included patients with left-hemispheric tumors (study group) and right-hemispheric tumors (controls). We calculated five fMRI laterality indexes (LI): hemispheric, temporal lobe, frontal lobe, Broca's area (BA), Wernicke's area (WA). We defined LI ≥ 0.2 as left-lateralized (LL) and LI < 0.2 as atypical lateralized (AL). Chi-square test (p < 0.05) was employed to identify the relationship between LI and tumor/patient variables in the study group. For those variables having significant results, confounding factors were evaluated in a multinomial logistic regression model. RESULTS: We included 405 patients (235 M, mean age: 51 years old) and 49 controls (36 M, mean age: 51 years old). Contralateral language reorganization was more common in patients than controls. The statistical analysis demonstrated significant association between BA LI and patient sex (p = 0.005); frontal LI, BA LI, and tumor location in BA (p < 0.001); hemispheric LI and fibroblast growth factor receptor (FGFR) mutation (p = 0.019); WA LI and O6-methylguanine-DNA methyltransferase promoter (MGMT) methylation in high-grade gliomas (p = 0.016). CONCLUSIONS: Tumor genetics, pathology, and location influence language laterality, possibly due to cortical plasticity. Increased fMRI activation in the right hemisphere was seen in patients with tumors in the frontal lobe, BA and WA, FGFR mutation, and MGMT promoter methylation. KEY POINTS: • Patients harboring left-hemispheric tumors present with contralateral translocation of language function. Influential variables for this phenomenon included frontal tumor location, BA location, WA location, sex, MGMT promoter methylation, and FGFR mutation. • Tumor location, grade, and genetics may influence language plasticity, thereby affecting both communication between eloquent areas and tumor growth dynamics. • In this retrospective cross-sectional study, we evaluated language reorganization in 405 brain tumor patients by studying the relationship of fMRI language laterality to tumor-related variables (grade, genetics, location), and patient-related variables (age, sex, handedness).

Functional MRI during tongue strength tasks before and after partial glossectomy: Insights into the cortical activation of tongue motor function.

AIM: Because the tongue is a midline structure, studies on the neural correlates of lateralized tongue function are challenging and remain limited. Patients with tongue cancer who undergo unilateral partial glossectomy may be a unique cohort to study tongue-associated cortical activation, particularly regarding brain hemispheric lateralization. This longitudinal functional magnetic resonance imaging (fMRI) study investigated cortical activation changes for three tongue tasks before and after left-sided partial glossectomy in patients with squamous cell carcinoma of the tongue. METHODS: Seven patients with squamous cell carcinoma involving the left tongue who underwent fMRI before and 6 months after unilateral partial glossectomy were studied. Post-surgical changes in laterality index (LI) values for tongue-associated precentral and postcentral gyri fMRI activation were calculated for the dry swallow, tongue press, and saliva sucking tasks. Group analysis fMRI activation maps were generated for each of the three tasks. RESULTS: There were significant differences in changes in LI values post-surgery between the tongue press (p < 0.005; median: +0.24), saliva sucking (-0.10), and dry swallow tasks (-0.16). Decreased contralateral activation (change in LI ≥+0.20) was observed post-surgery during tongue press in six of seven patients, but only in two patients during saliva sucking and one patient during dry swallow (p < 0.05). There was also increased activation in the supplementary motor area following surgery. CONCLUSION: Post-surgical fMRI changes following left-sided partial glossectomy may suggest task-specific sensitivities to cortical activation changes following unilateral tongue deficits that may reflect the impacts of surgery and adaptive responses to tongue impairment.

Longitudinal Evaluation of Brain Plasticity in Low-Grade Gliomas: fMRI and Graph-Theory Provide Insights on Language Reorganization.

Language reorganization may represent an adaptive phenomenon to compensate tumor invasion of the dominant hemisphere. However, the functional changes over time underlying language plasticity remain unknown. We evaluated language function in patients with low-grade glioma (LGG), using task-based functional MRI (tb-fMRI), graph-theory and standardized language assessment. We hypothesized that functional networks obtained from tb-fMRI would show connectivity changes over time, with increased right-hemispheric participation. We recruited five right-handed patients (4M, mean age 47.6Y) with left-hemispheric LGG. Tb-fMRI and language assessment were conducted pre-operatively (pre-op), and post-operatively: post-op1 (4-8 months), post-op2 (10-14 months) and post-op3 (16-23 months). We computed the individual functional networks applying optimal percolation thresholding. Language dominance and hemispheric connectivity were quantified by laterality indices (LI) on fMRI maps and connectivity matrices. A fixed linear mixed model was used to assess the intra-patient correlation trend of LI values over time and their correlation with language performance. Individual networks showed increased inter-hemispheric and right-sided connectivity involving language areas homologues. Two patterns of language reorganization emerged: Three/five patients demonstrated a left-to-codominant shift from pre-op to post-op3 (type 1). Two/five patients started as atypical dominant at pre-op, and remained unchanged at post-op3 (type 2). LI obtained from tb-fMRI showed a significant left-to-right trend in all patients across timepoints. There were no significant changes in language performance over time. Type 1 language reorganization may be related to the treatment, while type 2 may be tumor-induced, since it was already present at pre-op. Increased inter-hemispheric and right-side connectivity may represent the initial step to develop functional plasticity.

Use of longitudinal functional MRI to demonstrate translocation of language function in patients with brain tumors.

OBJECTIVE: The ability of functional MRI (fMRI) to localize patient-specific eloquent areas has proved worthwhile in efforts to maximize resection while minimizing risk of iatrogenic damage in patients with brain tumors. Although cortical reorganization has been described, the frequency of its occurrence and the factors that influence incidence are not well understood. The authors investigated changes in language laterality between 2 fMRI studies in patients with brain tumors to elucidate factors contributing to cortical reorganization. METHODS: The authors analyzed 33 patients with brain tumors involving eloquent language areas who underwent 2 separate presurgical, language task-based fMRI examinations (fMRI1 and fMRI2). Pathology consisted of low-grade glioma (LGG) in 15, and high-grade glioma (HGG) in 18. The mean time interval between scans was 35 ± 38 months (mean ± SD). Regions of interest were drawn for Broca's area (BA) and the contralateral BA homolog. The laterality index (LI) was calculated and categorized as follows: > 0.2, left dominance; 0.2 to -0.2, codominance; and < -0.2, right dominance. Translocation of language function was defined as a shift across one of these thresholds between the 2 scans. Comparisons between the 2 groups, translocation of language function (reorganized group) versus no translocation (constant group), were performed using the Mann-Whitney U-test. RESULTS: Nine (27%) of 33 patients demonstrated translocation of language function. Eight of 9 patients with translocation had tumor involvement of BA, compared to 5/24 patients without translocation (p < 0.0001). There was no difference in LI between the 2 groups at fMRI1. However, the reorganized group showed a decreased LI at fMRI2 compared to the constant group (-0.1 vs 0.53, p < 0.01). The reorganized cohort showed a significant difference between LI1 and LI2 (0.50 vs -0.1, p < 0.0001) whereas the constant cohort did not. A longer time interval was found in the reorganized group between fMRI1 and fMRI2 for patients with LGG (34 vs 107 months, p < 0.002). Additionally, the reorganized cohort had a greater proportion of local tumor invasion into eloquent areas at fMRI2 than the constant group. Aphasia was present following fMRI2 in 13/24 (54%) patients who did not exhibit translocation, compared to 2/9 (22%) patients who showed translocation. CONCLUSIONS: Translocation of language function in patients with brain tumor is associated with tumor involvement of BA, longer time intervals between scans, and is seen in both LGG and HGG. The reduced incidence of aphasia in the reorganized group raises the possibility that reorganization supports the conservation of language function. Therefore, longitudinal fMRI is useful because it may point to reorganization and could affect therapeutic planning for patients.

Language reorganization in patients with left-hemispheric gliomas is associated with increased cortical volume in language-related areas and in the default mode network.

BACKGROUND: Language function may reorganize to overcome focal impairment; however, the relation between functional and structural changes in patients with brain tumors remains unclear. We investigated the cortical volume of atypical language dominant (AD) patients with left frontal-insular high-grade (HGG) and low-grade glioma (LGG). We hypothesized atypical language being associated with areas of increased cortical volume in the right hemisphere, including language areas homologues. METHODS: Patient were recruited following the criteria: left frontal-insular glioma; functional MRI and 3DT1-weighted images; no artifacts. We calculated an hemispheric language laterality index (LI), defined as: AD if LI < .2; left-dominant (LD) if LI ≥ .2. We measured cortical volume in three voxel-based morphometry (VBM) analyses: total AD vs. LD patients; AD vs. LD in HGG; AD vs. LD in LGG. We repeated the analysis in AD vs. LD healthy controls (HC). A minimum threshold of t > 2 and corrected p < .025 (Bonferroni) was employed. RESULTS: We recruited 119 patients (44LGG, 75HGG). Hemispheric LI demonstrated 64/119AD and 55/119LD patients. The first VBM analysis demonstrated significantly increased cortical volume in AD patients in the right inferior frontal gyrus (IFG), right superior temporal gyrus (STG), right insula, right fusiform gyrus (FG), right precentral gyrus, right temporal-parietal junction, right posterior cingulate cortex (PCC), right hippocampus, right- and left cerebellum. AD patients with HGG showed the same areas of significantly increased cortical volume. AD patients with LGG displayed significantly increased cortical volume in right IFG, right STG, right insula, right FG, right anterior cingulate cortex, right PCC, right dorsal-lateral prefrontal cortex. HC showed no significant results. CONCLUSION: Right-sided (atypical) language activations in patients with left-hemispheric gliomas are associated with areas of increased cortical volume. Additionally, default mode network nodes showed greater cortical volume in AD patients regardless of the tumor grade, supporting the idea of these cortices participating in the development of language plasticity.

Brain Functional Connectivity in Low- and High-Grade Gliomas: Differences in Network Dynamics Associated with Tumor Grade and Location.

Brain tumors lead to modifications of brain networks. Graph theory plays an important role in clarifying the principles of brain connectivity. Our objective was to investigate network modifications related to tumor grade and location using resting-state functional magnetic resonance imaging (fMRI) and graph theory. We retrospectively studied 30 low-grade (LGG), 30 high-grade (HGG) left-hemispheric glioma patients and 20 healthy controls (HC) with rs-fMRI. Tumor location was labeled as: frontal, temporal, parietal, insular or occipital. We collected patients' clinical data from records. We analyzed whole-brain and hemispheric networks in all patients and HC. Subsequently, we studied lobar networks in subgroups of patients divided by tumor location. Seven graph-theoretical metrics were calculated (FDR p < 0.05). Connectograms were computed for significant nodes. The two-tailed Student t-test or Mann−Whitney U-test (p < 0.05) were used to compare graph metrics and clinical data. The hemispheric network analysis showed increased ipsilateral connectivity for LGG (global efficiency p = 0.03) and decreased contralateral connectivity for HGG (degree/cost p = 0.028). Frontal and temporal tumors showed bilateral modifications; parietal and insular tumors showed only local effects. Temporal tumors led to a bilateral decrease in all graph metrics. Tumor grade and location influence the pattern of network reorganization. LGG may show more favorable network changes than HGG, reflecting fewer clinical deficits.

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.

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.

Decreased Hand Motor Resting-State Functional Connectivity in Patients with Glioma: Analysis of Factors including Neurovascular Uncoupling.

Background Resting-state functional MRI holds substantial potential for clinical application, but limitations exist in current understanding of how tumors exert local effects on resting-state functional MRI readings. Purpose To investigate the association between tumors, tumor characteristics, and changes in resting-state connectivity, to explore neurovascular uncoupling as a mechanism underlying these changes, and to evaluate seeding methodologies as a clinical tool. Materials and Methods Institutional review board approval was obtained for this HIPAA-compliant observational retrospective study of patients with glioma who underwent MRI and resting-state functional MRI between January 2016 and July 2017. Interhemispheric symmetry of connectivity was assessed in the hand motor region, incorporating tumor position, perfusion, grade, and connectivity generated from seed-based correlation. Statistical analysis was performed by using one-tailed t tests, Wilcoxon rank sum tests, one-way analysis of variance, Pearson correlation, and Spearman rank correlation, with significance at P < .05. Results Data in a total of 45 patients with glioma (mean age, 51.3 years ± 14.3 [standard deviation]) were compared with those in 10 healthy control subjects (mean age, 50.3 years ± 17.2). Patients showed loss of symmetry in measures of hand motor resting-state connectivity compared with control subjects (P < .05). Tumor distance from the ipsilateral hand motor (IHM) region correlated with the degree (R = 0.38, P = .01) and strength (R = 0.33, P = .03) of resting-state connectivity. In patients with World Health Organization grade IV glioblastomas 40 mm or less from the IHM region, loss of symmetry in strength of resting-state connectivity was correlated with tumor perfusion (R = 0.74, P < .01). In patients with gliomas 40 mm or less from the IHM region, seeding the nontumor hemisphere yielded less asymmetric hand motor resting-state connectivity than seeding the tumor hemisphere (connectivity seeded:contralateral = 1.34 nontumor vs 1.38 tumor hemisphere seeded; P = .03, false discovery rate threshold = 0.01). Conclusion Hand motor resting-state connectivity was less symmetrical in a tumor distance-dependent manner in patients with glioma. Differences in resting-state connectivity may be false-negative results driven by a neurovascular uncoupling mechanism. Seeding from the nontumor hemisphere may attenuate asymmetry in patients with tumors near ipsilateral hand motor cortices. © RSNA, 2020 Online supplemental material is available for this article.

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.

Resting-State Functional Magnetic Resonance Imaging and Probabilistic Diffusion Tensor Imaging Demonstrate That the Greatest Functional and Structural Connectivity in the Hand Motor Homunculus Occurs in the Area of the Thumb.

The primary hand motor region is classically believed to be in the "hand knob" area in the precentral gyrus (PCG). However, hand motor task-based activation is often localized outside this area. The purpose of this study is to investigate the structural and functional connectivity driven by different seed locations corresponding to the little, index, and thumb in the PCG using probabilistic diffusion tractography (PDT) and resting-state functional magnetic resonance imaging (rfMRI). Twelve healthy subjects had three regions of interest (ROIs) placed in the left PCG: lateral to the hand knob (thumb area), within the hand knob (index finger area), and medial to the hand knob (little finger area). Connectivity maps were generated using PDT and rfMRI. Individual and group level analyses were performed. Results show that the greatest hand motor connectivity between both hemispheres was obtained using the ROI positioned just lateral to the hand knob in the PCG (the thumb area). The number of connected voxels in the PCG between the two hemispheres was greatest in the lateral-most ROI (the thumb area): 279 compared with 13 for the medial-most ROI and 9 for the central hand knob ROI. Similarly, the highest white matter connectivity between the two hemispheres resulted from the ROI placed in the lateral portion of PCG (p < 0.003). The maximal functional and structural connectivity of the hand motor area between hemispheres occurs in the thumb area, located laterally at the "hand knob." Thus, this location appears maximal for rfMRI and PDT seeding of the motor area.

Diffusion Tensor Imaging Shows Corpus Callosum Differences between High-Grade Gliomas and Metastases.

BACKGROUND AND PURPOSE: The corpus callosum (CC) has an important role in regulating interhemispheric transfer and is thought to be instrumental in contralateral brain reorganization in patients with brain tumors, as suggested by a previous study reporting callosal differences between language dominance groups through diffusion tensor imaging (DTI) characteristics. The purpose of this study was to explore the structural differences in the CC between high-grade gliomas (HGGs) and metastatic tumors (METs) using the DTI characteristics of fractional anisotropy (FA), mean diffusivity (MD), and axial diffusivity (AD). METHODS: HGG (n = 30) and MET (n = 20) subjects with Magnetic Resonance Imaging (MRI) scans including DTI were retrospectively studied. The tumor and CC were segmented using the 3-dimensional T1-weighted scans to determine their volumes. The region of interest (ROI; mean volume of the ROI = 3,090 ± 464 mm3 ) of the body of the CC was overlaid onto the DTI parametric maps to obtain the averaged FA, MD, and AD values. RESULTS: There were significant differences in the distributions of FA and MD values between the two patient groups (mean FA for HGG/MET = .691/.646, P < .05; mean MD for HGG/MET = .894×10-3 mm 2/ second /.992×10-3 mm2 /second, P < .01), while there was no correlation between the DTI parameters and the anatomical volumes. CONCLUSION: These results suggest that there is more contralateral brain reorganization in HGG patients than MET patients and that neither the tumor nor callosal volume impact the degree of contralateral brain reorganization.

Comparison of compressed sensing diffusion spectrum imaging and diffusion tensor imaging in patients with intracranial masses.

PURPOSE: To compare compressed diffusion spectrum imaging (CS-DSI) with diffusion tensor imaging (DTI) in patients with intracranial masses. We hypothesized that CS-DSI would provide superior visualization of the motor and language tracts. MATERIALS AND METHODS: We retrospectively analyzed 25 consecutive patients with intracranial masses who underwent DTI and CS-DSI for preoperative planning. Directionally-encoded anisotropy maps, and streamline hand corticospinal motor tracts and arcuate fasciculus language tracts were graded according to a 3-point scale. Tract counts, anisotropy, and lengths were also calculated. Comparisons were made using exact marginal homogeneity, McNemar's and Wilcoxon signed-rank tests. RESULTS: Readers preferred the CS-DSI over DTI anisotropy maps in 92% of the cases, and the CS-DSI over DTI tracts in 84%. The motor tracts were graded as excellent in 80% of cases for CS-DSI versus 52% for DTI; 58% of the motor tracts graded as acceptable in DTI were graded as excellent in CS-DSI (p=0.02). The language tracts were graded as excellent in 68% for CS-DSI versus none for DTI; 78% of the language tracts graded as acceptable by DTI were graded as excellent by CS-DSI (p<0.001). CS-DSI demonstrated smaller normalized mean differences than DTI for motor tract counts, anisotropy and language tract counts (p≤0.01). CONCLUSION: CS-DSI was preferred over DTI for the evaluation of motor and language white matter tracts in patients with intracranial masses. Results suggest that CS-DSI may be more useful than DTI for preoperative planning purposes.

Probabilistic fiber tracking of the language and motor white matter pathways of the supplementary motor area (SMA) in patients with brain tumors.

BACKGROUND AND PURPOSE: Accurate localization of anatomically and functionally separate SMA tracts is important to improve planning prior to neurosurgery. Using fMRI and probabilistic DTI techniques, we assessed the connectivity between the frontal language area (Broca's area) and the rostral pre-SMA (language SMA) and caudal SMA proper (motor SMA). MATERIALS AND METHODS: Twenty brain tumor patients completed motor and language fMRI paradigms and DTI. Peaks of functional activity in the language SMA, motor SMA and Broca's area were used to define seed regions for probabilistic tractography. RESULTS: fMRI and probabilistic tractography identified separate and unique pathways connecting the SMA to Broca's area - the language SMA pathway and the motor SMA pathway. For all subjects, the language SMA pathway had a larger number of voxels (P<0.0001) and higher connectivity (P<0.0001) to Broca's area than did the motor SMA pathway. In each patient, the number of voxels was greater in the language and motor SMA pathways than in background pathways (P<0.0001). No differences were found between patients with ipsilateral and those with contralateral tumors for either the language SMA pathway (degree of connectivity: P<0.36; number of voxels: 0.35) or the motor SMA pathway (degree of connectivity, P<0.28; number of voxels, P<0.74). CONCLUSION: Probabilistic tractography can identify unique white matter tracts that connect language SMA and motor SMA to Broca's area. The language SMA is more significantly connected to Broca's area than is the motor subdivision of the SMA proper.

Diffusion tensor tractography of the arcuate fasciculus in patients with brain tumors: Comparison between deterministic and probabilistic models.

PURPOSE: The purpose of this study was to compare the deterministic and probabilistic tracking methods of diffusion tensor white matter fiber tractography in patients with brain tumors. MATERIALS AND METHODS: We identified 29 patients with left brain tumors <2 cm from the arcuate fasciculus who underwent pre-operative language fMRI and DTI. The arcuate fasciculus was reconstructed using a deterministic Fiber Assignment by Continuous Tracking (FACT) algorithm and a probabilistic method based on an extended Monte Carlo Random Walk algorithm. Tracking was controlled using two ROIs corresponding to Broca's and Wernicke's areas. Tracts in tumoraffected hemispheres were examined for extension between Broca's and Wernicke's areas, anterior-posterior length and volume, and compared with the normal contralateral tracts. RESULTS: Probabilistic tracts displayed more complete anterior extension to Broca's area than did FACT tracts on the tumor-affected and normal sides (p < 0.0001). The median length ratio for tumor: normal sides was greater for probabilistic tracts than FACT tracts (p < 0.0001). The median tract volume ratio for tumor: normal sides was also greater for probabilistic tracts than FACT tracts (p = 0.01). CONCLUSION: Probabilistic tractography reconstructs the arcuate fasciculus more completely and performs better through areas of tumor and/or edema. The FACT algorithm tends to underestimate the anterior-most fibers of the arcuate fasciculus, which are crossed by primary motor fibers.