ObjectivesSeveral cholinergic nuclei, and in particular the nucleus basalis of Meynert, are localised to the substantia innominata in the basal forebrain. These nuclei provide major cholinergic innervation to the cerebral cortex and hippocampus, and have an essential role in cognitive function. The aim of this study was to investigate volumetric grey matter (GM) changes in the substantia innominata from structural T1 images in Alzheimer's disease (AD), dementia with Lewy bodies (DLB) and healthy older participants using voxel‐based morphometry.MethodsParticipants (41 DLB, 47 AD and 39 controls) underwent 3 T T1 magnetic resonance imaging and cognitive assessments. Voxel‐based morphometry analysis used SPM8 with a substantia innominata brain mask to define the subspace for voxel GM analyses. Group differences, and selected behavioural and clinical correlates, were assessed.ResultsCompared with that in controls, bilateral GM loss in the substantia innominata was apparent in both AD and DLB. Relative to controls, significant bilateral GM loss in the substantia innominata was observed in DLB and AD. In DLB, significant associations were also observed between substantia innominata GM volume loss, and the levels of cognitive impairment and severity of cognitive fluctuations.ConclusionsRelative to that controls, atrophy of the substantia innominata was apparent in DLB and AD, and is associated with specific clinical manifestations in DLB. © 2016 The Authors. International Journal of Geriatric Psychiatry Published by John Wiley & Sons Ltd.
Background: The substantia innominata (SI) forms part of the basal fore-brain that provides major cholinergic innervation to the cerebral cortex and hippocampus, and has an essential role in cognitive function. Cholin-ergic loss is a central feature of dementia with Lewy bodies (DLB) and contributes to the clinical symptom phenotype. The objective was to investigate grey matter (GM) and white matter (WM) changes in the SI from magnetic resonance (MR) images in DLB, Alzheimer's disease (AD) and healthy older subjects using voxel-based morphometry (VBM). Methods: One hundred and twenty seven subjects' (39 controls, 48 AD, 41 DLB) underwent 3T T1 MR imaging as well as clinical and cognitive assessments. VBM was undertaken using SPM8 and used a SI mask image to define the brain volume subspace for voxel analyses. Group differences in GM and WM volumes and selected behavioural correlates were assessed using the general linear model, with age and total intracranial volume as nuisance variables. Effects were identified using an uncorrected threshold of P uncorrected 0.05, followed by family-wise error (FWE) correction for multiple comparisons (P FWE 0.05) within the SI volume subspace. Results: Relative to controls, VBM analysis revealed significant bilateral GM loss in the SI in both AD and DLB (P FWE 0.05); however, these deficits were more pronounced in DLB. Compared to controls, significant WM loss (P FWE 0.05) was also observed bilaterally in AD but not in DLB. In DLB, significant correlations were found with MMSE and CAF scores on GM volume (P FWE 0.05). Conclusions: In DLB, GM loss is more pronounced in the SI than in AD and appears to be associated with dementia severity and cognitive fluctuations. GM atrophy of the SI may shed light in understanding some of the clinical manifestations of DLB, while relative preservation of WM volume could also have positive implications for cholinergic intervention. Background: The hive database system (theHiveDB) is a web-based brain imaging management framework for cross-sectional and longitudinal multi-center studies. It has been conceived with a focus on data aggregation across modalities (i.e. brain imaging, clinical and genetic data). Methods: TheHi-veDB has been designed to manage imaging projects, individuals (study participants), scalar data and associated file assets.Data files pertaining to different projects may be stored on distinct networked computers. The sys-tem's activity and resource management component is capable of distributing processing across local computing resources and both private and public clouds. Data transfers are automated using the SSH-2 protocol. The system provides a framework for effective collaborations and resource sharing. It facilitates access to data at all levels, by providing pertinent meta information about image acquisitions, allowing to extract individual series in various formats from DICOM studies and offering direct file download and transfer to workstations for source data and processed output. The system supports a rich set o...
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