A study of bipolar disorder using magnetization transfer imaging and voxel-based morphometry
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Abstract:
Bipolar disorder (BP) traditionally has been considered as a recurrent illness with full recovery between episodes, and the absence of neuropathological abnormalities has usually been taken for granted. In recent times, the realization that, for many BP carries a poor prognosis, that cognitive deficits are often persistent and that structural brain abnormalities are detectable with modern imaging techniques has spurred the search for its neuropathological substrate. The shortcomings of post-mortem studies make the use of imaging techniques sensitive to neuropathological changes compelling. We report here the first study of BP patients using two such techniques in conjunction: magnetization transfer imaging (MTI) and voxel-based morphometry (VBM). Thirty-nine patients with BP (13 males and 26 females; 28 with BPI and 11 with BPII) and 35 healthy controls were investigated. Both high-resolution volumetric T1-weighted images and MT images were acquired from all subjects. Images were processed using a voxel-by-voxel analysis in statistical parametric mapping 2 (SPM2). The magnetization transfer ratio MTR, an index indicative of loss of macromolecular density, was reduced in the right subgenual anterior cingulate and adjacent white matter in bipolar patients compared with controls. VBM did not reveal significant volumetric differences between BP patients and controls in grey and white matter, but white matter density was significantly reduced bilaterally in prefrontal areas encompassing fronto-striatal connections. Our findings suggest that subtle abnormalities are present in the anterior cingulate and subgyral white matter in patients with BP in the absence of significant volumetric changes. These findings are in keeping with those of previously reported neuropathological studies and illustrate important similarities (involvement of the anterior cingulate) and differences (lack of widespread cortical abnormalities in BP) with our previous studies in schizophrenic patients using the same methodology.Keywords:
Magnetization transfer
Statistical parametric mapping
Voxel-based morphometry
Grey matter
Objective To study the grey matter volume of brain magnetic resonance image in patients with Alzheimer’s disease (AD). Methods Three-dimensional brain magnetic resonance images were pretreated with DARTEL method in 11 AD patients and 11 healthy controls, and the difference of grey matter volume of the whole brain was assessed using voxel-based morphometry between both groups. Results The volume of bilateral hippocampus, parahippocampal gyrus, amygdala, superior and middle temporal gyri, caudate and lenticular nuclei, insula, and cerebellar peduncle was significantly lower in AD than that in controls (FDR corrected, P0.05, voxels ?Y50). Conclusion Voxel-based morphometry can reveal the grey matter atrophy, which is helpful in early diagnosis and surveillance in AD patients.
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Parahippocampal gyrus
Middle temporal gyrus
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Reduced awareness of cognitive deficits in mild cognitive impairment (MCI) is associated with poorer outcomes although little is known about the anatomical correlates of this. We examined the association of insight and grey matter volume using a voxe
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Anosognosia
Cognitive Decline
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Voxel-based morphometry
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Putamen
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Background
In Multiple Sclerosis (MS), demyelination and neuronal loss occur in the brain grey matter (GM) and are associated with a progressive disease course. Using MRI measures of atrophy and GM magnetization transfer ratio (MTR), we investigated the regional localisation of consistent volume loss (reflecting neuronal loss) and intrinsic tissue abnormalities (particularly demyelination) in MS clinical subgroups.Objective
To map regions of consistent GM atrophy and MTR reduction in relapsing–remitting (RR), secondary progressive (SP) and primary progressive (PP) MS.Methods
102 patients (51 RRMS, 30 SPMS, 21 PPMS) and 32 controls had T1–weighted volumetric and magnetisation transfer scans, both acquired at 1x1x1mm3. MTR maps were calculated using MT on and off sequences. MTR in grey matter was extracted by segmenting grey matter on T1–weighted images and binarising the resulting tissue maps with a conservative threshold of 90%. Using SPM8, T1 scans were non–linearly registered to create a DARTEL template, registered to MNI space using affine transformation, and smoothed with an 8 mm full–width half maximum Gaussian kernel. Voxel–based morphometry (VBM) was used to compare regional differences in GM atrophy and a VBM–type analysis was carried out on the grey matter MTR of MS patient subgroups versus controls, adjusting for age and gender, using family wise error (FWE) correction at p<0.05.Results
Compared with controls, PPMS and SPMS groups exhibited more areas of MTR reduction than atrophy while RRMS subjects showed more areas of atrophy than reduced MTR. Co–localisation of atrophy and reduced MTR was most evident in the thalamus in all MS subtypes. There were more areas of cortical MTR reduction and atrophy than where both were co–localised. Compared to controls, there were more areas of cortical MTR reduction in SPMS and PPMS than in RRMS.Conclusions
Assuming that reduced GM MTR implies demyelination and atrophy reflects neuronal loss, the results suggest that: (i) in progressive (SP and PP) MS there is overall more extensive GM demyelination than neuronal loss; (ii) in RRMS there is overall more extensive GM neuronal loss with less noticeable demyelination, (iii) cortical demyelination occurs in more regions in SPMS and PPMS than RRMS; (iv) demyelination and neuronal loss often occur in different locations in the cortex, and (v) co–existent demyelination and neuronal loss is most evident in the thalamus. The variation in regional abnormalities argue against a single common mechanism for demyelination and neuronal loss in MS GM.Grey matter
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Voxel-based morphometry (VBM) is commonly used to study systematic differences in brain morphology from patients with various disorders, usually by comparisons with control subjects. It has often been suggested, however, that VBM is also sensitive to variations in composition in grey matter. The nature of the grey matter changes identified with VBM is still poorly understood. The aim of the current study was to determine whether grey matter histopathological measurements of neuronal tissue or gliosis influenced grey matter probability values that are used for VBM analyses. Grey matter probability values (obtained using both SPM5 and FSL-FAST) were correlated with neuronal density, and field fraction of NeuN and GFAP immunopositivity in a grey matter region of interest in the middle temporal gyrus, in 19 patients undergoing temporal lobe resection for refractory epilepsy. There were no significant correlations between any quantitative neuropathological measure and grey matter probability values in normal-appearing grey matter using either segmentation program. The lack of correlation between grey matter probability values and the cortical neuropathological measures in normal-appearing grey matter suggests that intrinsic cortical changes of the type we have measured do not influence grey matter probability maps used for VBM analyses.
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The aim of this study was to make a comparison of brain structure between a group of opioid-dependent subjects and healthy controls. We report the results of an ;optimized' voxel-based morphometry study on a sample of nine opioid-dependent subjects with no comorbid substance misuse disorders versus 21 healthy controls. We found a significant reduction in grey matter volume of the thalamus after controlling for age and total grey matter volume. Regression analysis of substance use variables in the opioid-dependent sample shows that only level of alcohol use negatively predicts grey matter volume for this region of difference. We suggest that level of nondependent alcohol use could influence reduced thalamic grey matter volume in opioid-dependent subjects.
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Abstract Background In order to understand the changes that occur in the brain over the course of neurodegenerative disorders, it is imperative to establish how the brain changes over time under healthy conditions (Mattson & Arumugam, 2018). Older adulthood is associated with normal age‐related declines in cognitive functioning (Klimova et al., 2017). However, there are inconsistencies in the literature regarding associated changes in grey matter, with some reporting atrophy across the whole brain and others reporting focal atrophy, localized in the frontal and temporal regions (Pergher et al., 2019; Squarzoni et al., 2018). The current study took a longitudinal approach to investigate changes in grey matter over four years in healthy aging. Methods 3T T1 anatomical magnetic resonance images (MRI) were obtained from 16 healthy older adults (7 male, 9 female; mean age 74.38 ± 4.52 years at baseline) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database at two time points, four years apart. Voxel‐based morphometry (VBM) analyses were carried out using FMRIB’s Software Library to examine within‐subject changes in grey matter over time. Results Figure 1 depicts regions where there was significant atrophy (p<0.05, corrected for multiple comparisons) in grey matter at four‐year follow‐up compared to baseline. Specifically, VBM results indicated atrophy in distributed areas including bilateral frontal and temporal regions as well as in the hippocampi, bilaterally. However, there were no significant changes in cognitive performance over these four years. Conclusions The current findings reveal atrophy in multiple regions, including the temporal lobes despite normal cognitive performance over the course of four years in healthy aging. Similar regions are known to be affected in Alzheimer’s disease and associated with cognitive decline (Minkova et al., 2017). Follow up work will aim to replicate the current findings in a larger sample and to examine the relationship between cognitive performance and grey matter volume. Developing an understanding of changes in brain structure and function that occur over time in healthy aging will allow for improved interpretation of changes in neurodegenerative conditions, such as Alzheimer’s disease.
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Grey Literature
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