Dataset Information

Speech network regional involvement in bulbar ALS: a multimodal structural MRI study.

ABSTRACT: Objective: To examine gray (GM) and white matter (WM) structural changes in regions of the speech network (SpN) in ALS patients with varying degree of bulbar disease. Methods: T1 and DTI images were obtained for 19 ALS participants and 13 neurologically-intact controls. Surface-based, volumetric, and DTI metrics were obtained for 6 regions-of-interest (ROIs) including the primary motor cortex (PMC), pars triangularis (parsT), pars opercularis (ParsO), posterior superior temporal gyrus (pSTG), and transverse temporal (TT). Disease-effects and brain-behavioral correlates between neuroanatomy and clinical measures of bulbar, limb, and overall disability were examined using linear models. Results: Structural changes were observed in the right oral and limb PMC and left ParsT, TT, and pSTG in ALS. Bulbar motor dysfunction was associated with WM abnormalities in the right oral PMC and left pSTG, and GM changes in bilateral TT. In contrast, symptom progression rate predicted GM and WM changes in bilateral pars opercularis (part of Broca's area). Grip strength and disease duration models were non-significant. Conclusions: The findings suggested that regions of the left-dominant SpN may be implicated in ALS and degeneration of these areas are related to bulbar disease severity. Involvement of regions that overlap across multiple connectomes such as Broca's area, however, may be dependent on the rate of disease progression. The work contributes to our understanding of bulbar ALS subtype, which is crucial for predicting disease progression, delivering targeted clinical care, and appropriate recruitment into clinical trials.

SUBMITTER: Shellikeri S

PROVIDER: S-EPMC6648678 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Speech network regional involvement in bulbar ALS: a multimodal structural MRI study.

Shellikeri Sanjana S Myers Matthew M Black Sandra E SE Abrahao Agessandro A Zinman Lorne L Yunusova Yana Y

Amyotrophic lateral sclerosis & frontotemporal degeneration 20190514 5-6

<i>Objective:</i> To examine gray (GM) and white matter (WM) structural changes in regions of the speech network (SpN) in ALS patients with varying degree of bulbar disease. <i>Methods:</i> T1 and DTI images were obtained for 19 ALS participants and 13 neurologically-intact controls. Surface-based, volumetric, and DTI metrics were obtained for 6 regions-of-interest (ROIs) including the primary motor cortex (PMC), pars triangularis (parsT), pars opercularis (ParsO), posterior superior temporal gy ...[more]

PMID: 31088163

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Project description:Introduction: Corticobasal syndrome (CBS) is a progressive neurological disorder related to multiple underlying pathologies, including four-repeat tauopathies, such as corticobasal degeneration and progressive supranuclear palsy, and Alzheimer's disease (AD). Speech and language are commonly impaired, encompassing a broad spectrum of deficits. We aimed to investigate CBS speech and language impairment patterns in light of a multimodal imaging approach. Materials and Methods: Thirty-one patients with probable CBS were prospectively evaluated concerning their speech-language, cognitive, and motor profiles. They underwent positron emission tomography with [18F]fluorodeoxyglucose (FDG-PET) and [11C]Pittsburgh Compound-B (PIB-PET) on a hybrid PET-MRI machine to assess their amyloid status. PIB-PET images were classified based on visual and semi-quantitative analyses. Quantitative group analyses were performed on FDG-PET data, and atrophy patterns on MRI were investigated using voxel-based morphometry (VBM). Thirty healthy participants were recruited as imaging controls. Results: Aphasia was the second most prominent cognitive impairment, presented in 67.7% of the cases, following apraxia (96.8%). We identified a wide linguistic profile, ranging from nonfluent variant-primary progressive aphasia to lexical-semantic deficits, mostly with impaired verbal fluency. PIB-PET was classified as negative (CBS-A- group) in 18/31 (58%) and positive (CBS-A+ group) in 13/31 (42%) patients. The frequency of dysarthria was significantly higher in the CBS-A- group than in the CBS-A+ group (55.6 vs. 7.7%, p = 0.008). CBS patients with dysarthria had a left-sided hypometabolism at frontal regions, with a major cluster at the left inferior frontal gyrus and premotor cortex. They showed brain atrophy mainly at the opercular frontal gyrus and putamen. There was a positive correlation between [18F]FDG uptake and semantic verbal fluency at the left inferior (p = 0.006, R 2 = 0.2326), middle (0.0054, R 2 = 0.2376), and superior temporal gyri (p = 0.0066, R 2 = 0.2276). Relative to the phonemic verbal fluency, we found a positive correlation at the left frontal opercular gyrus (p = 0.0003, R 2 = 0.3685), the inferior (p = 0.0004, R 2 = 0.3537), and the middle temporal gyri (p = 0.0001, R 2 = 0.3993). Discussion: In the spectrum of language impairment profile, dysarthria might be helpful to distinguish CBS patients not related to AD. Metabolic and structural signatures depicted from this feature provide further insights into the motor speech production network and are also helpful to differentiate CBS variants.

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Project description:Autism Spectrum Disorder (ASD) and Childhood Apraxia of Speech (CAS) are developmental disorders with distinct diagnostic criteria and different epidemiology. However, a common genetic background as well as overlapping clinical features between ASD and CAS have been recently reported. To date, brain structural language-related abnormalities have been detected in both the conditions, but no study directly compared young children with ASD, CAS and typical development (TD). In the current work, we aim: (i) to test the hypothesis that ASD and CAS display neurostructural differences in comparison with TD through morphometric Magnetic Resonance Imaging (MRI)-based measures (ASD vs. TD and CAS vs. TD); (ii) to investigate early possible disease-specific brain structural patterns in the two clinical groups (ASD vs. CAS); (iii) to evaluate predictive power of machine-learning (ML) techniques in differentiating the three samples (ASD, CAS, TD). We retrospectively analyzed the T1-weighted brain MRI scans of 68 children (age range: 34-74 months) grouped into three cohorts: (1) 26 children with ASD (mean age ± standard deviation: 56 ± 11 months); (2) 24 children with CAS (57 ± 10 months); (3) 18 children with TD (55 ± 13 months). Furthermore, a ML analysis based on a linear-kernel Support Vector Machine (SVM) was performed. All but one brain structures displayed significant higher volumes in both ASD and CAS children than TD peers. Specifically, ASD alterations involved fronto-temporal regions together with basal ganglia and cerebellum, while CAS alterations are more focused and shifted to frontal regions, suggesting a possible speech-related anomalies distribution. Caudate, superior temporal and hippocampus volumes directly distinguished the two conditions in terms of greater values in ASD compared to CAS. The ML analysis identified significant differences in brain features between ASD and TD children, whereas only some trends in the ML classification capability were detected in CAS as compared to TD peers. Similarly, the MRI structural underpinnings of two clinical groups were not significantly different when evaluated with linear-kernel SVM. Our results may represent the first step towards understanding shared and specific neural substrate in ASD and CAS conditions, which subsequently may contribute to early differential diagnosis and tailoring specific early intervention.

Dataset Information

Speech network regional involvement in bulbar ALS: a multimodal structural MRI study.

Publications

Speech network regional involvement in bulbar ALS: a multimodal structural MRI study.

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