983 resultados para Tensor-based morphometry


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Context Diffusion tensor imaging (DTI) studies in adults with bipolar disorder (BD) indicate altered white matter (WM) in the orbitomedial prefrontal cortex (OMPFC), potentially underlying abnormal prefrontal corticolimbic connectivity and mood dysregulatioin in BD. Objective: To use tract-based spatial statistics (TBSS) to examine VVM skeleton (ie, the most compact whole-brain WM) in subjects with BD vs healthy control subjects. Design: Cross-sectional, case-control, whole-brain DTI using TBSS. Setting: University research institute. Participants: Fifty-six individuals, 31 having a DSM-IV diagnosis of BD type 1 (mean age, 35.9 years [age range, 24-52 years]) and 25 controls (mean age, 29.5 years [age range, 19-52 years]). Main Outcome Measures: Fractional anisotropy (FA) longitudinal and radial diffusivities in subjects with BD vs controls (covarying for age) and their relationships with clinical and demographic variables. Results: Subjects with BD vs controls had significantly greater FA (t > 3.0, P <=.05 corrected) in the left uncinate fasciculus (reduced radial diffusivity distally and increased longitudinal diffusivity centrally), left optic radiation (increased longitudinal diffusivity), and right anterothalamic radiation (no significant diffusivity change). Subjects with BD vs controls had significantly reduced FA (t > 3.0, P <=.05 corrected) in the right uncinate fasciculus (greater radial diffusivity). Among subjects with BD, significant negative correlations (P <.01) were found between age and FA in bilateral uncinate fasciculi and in the right anterothalamic radiation, as well as between medication load and FA in the left optic radiation. Decreased FA (P <.01) was observed in the left optic radiation and in the right anterothalamic radiation among subjects with BD taking vs those not taking mood stabilizers, as well as in the left optic radiation among depressed vs remitted subjects with BD. Subjects having BD with vs without lifetime alcohol or other drug abuse had significantly decreased FA in the left uncinate fasciculus. Conclusions: To our knowledge, this is the first study to use TBSS to examine WM in subjects with BD. Subjects with BD vs controls showed greater WM FA in the left OMPFC that diminished with age and with alcohol or other drug abuse, as well as reduced WM FA in the right OMPFC. Mood stabilizers and depressed episode reduced WM FA in left-sided sensory visual processing regions among subjects with BD. Abnormal right vs left asymmetry in FA in OMPFC WM among subjects with BD, likely reflecting increased proportions of left-sided longitudinally aligned and right-sided obliquely aligned myelinated fibers, may represent a biologic mechanism for mood dysregulation in BD.

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In social anxiety disorder (SAD), impairments in limbic/paralimbic structures are associated with emotional dysregulation and inhibition of the medial prefrontal cortex (MPFq. Little is known, however, about alterations in limbic and frontal regions associated with the integrated morphometric, functional, and structural architecture of SAD. Whether altered gray matter volume is associated with altered functional and structural connectivity in SAD. Three techniques were used with 18 SAD patients and 18 healthy controls: voxel-based morphometry; resting-state functional connectivity analysis; and diffusion tensor imaging tractography. SAD patients exhibited significantly decreased gray matter volumes in the right posterior inferior temporal gyrus (ITG) and right parahippocampal/hippocampal gyrus (PHG/HIP). Gray matter volumes in these two regions negatively correlated with the fear factor of the Liebowitz Social Anxiety Scale. In addition, we found increased functional connectivity in SAD patients between the right posterior ITG and the left inferior occipital gyrus, and between the right PHF/HIP and left middle temporal gyms. SAD patients had increased right MPFC volume, along with enhanced structural connectivity in the genu of the corpus callosum. Reduced limbic/paralimbic volume, together with increased resting-state functional connectivity, suggests the existence of a compensatory mechanism in SAD. Increased MPFC volume, consonant with enhanced structural connectivity, suggests a long-time overgeneralization of structural connectivity and a role of this area in the mediation of clinical severity. Overall, our results may provide a valuable basis for future studies combining morphometric, functional and anatomical data in the search for a comprehensive understanding of the neural circuitry underlying SAD. (C) 2011 Elsevier B.V. All rights reserved.

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Classical regression methods take vectors as covariates and estimate the corresponding vectors of regression parameters. When addressing regression problems on covariates of more complex form such as multi-dimensional arrays (i.e. tensors), traditional computational models can be severely compromised by ultrahigh dimensionality as well as complex structure. By exploiting the special structure of tensor covariates, the tensor regression model provides a promising solution to reduce the model’s dimensionality to a manageable level, thus leading to efficient estimation. Most of the existing tensor-based methods independently estimate each individual regression problem based on tensor decomposition which allows the simultaneous projections of an input tensor to more than one direction along each mode. As a matter of fact, multi-dimensional data are collected under the same or very similar conditions, so that data share some common latent components but can also have their own independent parameters for each regression task. Therefore, it is beneficial to analyse regression parameters among all the regressions in a linked way. In this paper, we propose a tensor regression model based on Tucker Decomposition, which identifies not only the common components of parameters across all the regression tasks, but also independent factors contributing to each particular regression task simultaneously. Under this paradigm, the number of independent parameters along each mode is constrained by a sparsity-preserving regulariser. Linked multiway parameter analysis and sparsity modeling further reduce the total number of parameters, with lower memory cost than their tensor-based counterparts. The effectiveness of the new method is demonstrated on real data sets.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Studies in cocaine-dependent human subjects have shown differences in white matter on diffusion tensor imaging (DTI) compared with non-drug-using controls. It is not known whether the differences in fractional anisotropy (FA) seen on DTI in white matter regions of cocaine-dependent humans result from a pre-existing predilection for drug use or purely from cocaine abuse. To study the effect of cocaine on brain white matter, DTI was performed on 24 rats after continuous infusion of cocaine or saline for 4 weeks, followed by brain histology. Voxel-based morphometry analysis showed an 18% FA decrease in the splenium of the corpus callosum (CC) in cocaine-treated animals relative to saline controls. On histology, significant increase in neurofilament expression (125%) and decrease in myelin basic protein (40%) were observed in the same region in cocaine-treated animals. This study supports the hypothesis that chronic cocaine use alters white matter integrity in human CC. Unlike humans, where the FA in the genu differed between cocaine users and non-users, the splenium was affected in rats. These differences between rodent and human findings could be due to several factors that include differences in the brain structure and function between species and/or the dose, timing, and duration of cocaine administration.

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Objectives: Many morphometric magnetic resonance imaging (MRI) studies that have investigated the presence of gray matter (GM) volume abnormalities associated with the diagnosis of bipolar disorder (BD) have reported conflicting findings. None of these studies has compared patients with recent-onset psychotic BD with asymptomatic controls selected from exactly the same environment using epidemiological methods, or has directly contrasted BD patients against subjects with first-onset psychotic major depressive disorder (MDD). We examined structural brain differences between (i) BD (type I) subjects and MDD subjects with psychotic features in their first contact with the healthcare system in Brazil, and (ii) these two mood disorder groups relative to a sample of geographically matched asymptomatic controls. Methods: A total of 26 BD subjects, 20 subjects with MDD, and 94 healthy controls were examined using either of two identical MRI scanners and acquisition protocols. Diagnoses were based on DSM-IV criteria and confirmed one year after brain scanning. Image processing was conducted using voxel-based morphometry. Results: The BD group showed increased volume of the right dorsal anterior cingulate cortex relative to controls, while the MDD subjects exhibited bilateral foci GM deficits in the dorsolateral prefrontal cortex (p < 0.05, corrected for multiple comparisons). Direct comparison between BD and MDD patients showed a focus of GM reduction in the right-sided dorsolateral prefrontal cortex (p < 0.05, corrected for multiple comparisons) and a trend (p < 0.10, corrected) toward left-sided GM deficits in the dorsolateral prefrontal cortex of MDD patients. When analyses were repeated with scanner site as a confounding covariate the finding of increased right anterior cingulate volumes in BD patients relative to controls remained statistically significant (p = 0.01, corrected for multiple comparisons). Conclusions: These findings reinforce the view that there are important pathophysiological distinctions between BD and MDD, and indicate that subtle dorsal anterior cingulate abnormalities may be relevant to the pathophysiology of BD.

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Background: Neuropsychological deficits have been reported in association with first-episode psychosis (FEP). Reductions in grey matter (GM) volumes have been documented in FEP subjects compared to healthy controls. However, the possible inter-relationship between the findings of those two lines of research has been scarcely investigated. Objective: To investigate the relationship between neuropsychological deficits and GM volume abnormalities in a population-based sample of FEP patients compared to healthy controls from the same geographical area. Methods: FEP patients (n = 88) and control subjects (n = 86) were evaluated by neuropsychological assessment (Controlled Oral Word Association Test, forward and backward digit span tests) and magnetic resonance imaging using voxel-based morphometry. Results: Single-group analyses showed that prefrontal and temporo-parietal GM volumes correlated significantly (p < 0.05, corrected) with cognitive performance in FEP patients. A similar pattern of direct correlations between neocortical GM volumes and cognitive impairment was seen in the schizophrenia subgroup (n = 48). In the control group, cognitive performance was directly correlated with GM volume in the right dorsal anterior cingulate cortex and inversely correlated with parahippocampal gyral volumes bilaterally. Interaction analyses with ""group status"" as a predictor variable showed significantly greater positive correlation within the left inferior prefrontal cortex (BA46) in the FEP group relative to controls, and significantly greater negative correlation within the left parahippocampal gyrus in the control group relative to FEP patients. Conclusion: Our results indicate that cognitive deficits are directly related to brain volume abnormalities in frontal and temporo-parietal cortices in FEP subjects, most specifically in inferior portions of the dorsolateral prefrontal cortex. (C) 2009 Elsevier B.V. All rights reserved.

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Neurobiological models support an involvement of white matter tracts in the pathophysiology of obsessive-compulsive disorder (OCD), but there has been little systematic evaluation of white matter volumes in OCD using magnetic resonance imaging (MRI). We investigated potential differences in the volume of the cingulum bundle (CB) and anterior limb of internal capsule (ALIC) in OCD patients (n = 19) relative to asymptomatic control subjects (n = 15). White matter volumes were assessed using a 1.5T MRI scanner. Between-group comparisons were carried out after spatial normalization and image segmentation using optimized voxel-based morphometry. Correlations between regional white matter volumes in OCD subjects and symptom severity ratings were also investigated. We found significant global white matter reductions in OCD patients compared to control subjects. The voxel-based search for regional abnormalities (with covariance for total white matter volumes) showed no specific white matter volume deficits in brain portions predicted a priori to be affected in OCD (CB and ALIC). However, large clusters of significant positive correlation with OCD severity scores were found bilaterally on the ALIC. These findings provide evidence of OCD-related ALIC abnormalities and suggest a connectivity dysfunction within frontal-striatal-thalamic-cortical circuits. Further studies are warranted to better define the role of such white matter alterations in the pathophysiology of OCD, and may provide clues for a more effectively targeting of neurosurgical treatments for OCD. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

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Few studies have investigated in vivo changes of the cholinergic basal forebrain in Alzheimer`s disease (AD) and amnestic mild cognitive impairment (MCI), an at risk stage of AD. Even less is known about alterations of cortical projecting fiber tracts associated with basal forebrain atrophy. In this study, we determined regional atrophy within the basal forebrain in 21 patients with AD and 16 subjects with MCI compared to 20 healthy elderly subjects using deformation-based morphometry of MRI scans. We assessed effects of basal forebrain atrophy on fiber tracts derived from high-resolution diffusion tensor imaging (DTI) using tract-based spatial statistics. We localized significant effects relative to a map of cholinergic nuclei in MRI standard space as determined from a postmortem brain. Patients with AD and MCI subjects showed reduced volumes in basal forebrain areas corresponding to anterior medial and lateral, intermediate and posterior nuclei of the Nucleus basalis of Meynert (NbM) as well as in the diagonal band of Broca nuclei (P < 0.01). Effects in MCI subjects were spatially more restricted than in AD, but occurred at similar locations. The volume of the right antero-lateral NbM nucleus was correlated with intracortical projecting fiber tract integrity such as the corpus callosum, cingulate, and the superior longitudinal, inferior longitudinal, inferior fronto-occipital, and uncinate fasciculus (P < 0.05, corrected for multiple comparisons). Our findings suggest that a multimodal MRI-DTI approach is supportive to determine atrophy of cholinergic nuclei and its effect on intracortical projecting fiber tracts in AD. Hum Brain Mapp 32: 1349-1362, 2011. (C) 2010 Wiley-Liss, Inc.

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Cerebral microangiopathy (CMA) has been associated with executive dysfunction and fronto-parietal neural network disruption. Advances in magnetic resonance imaging allow more detailed analyses of gray (e.g., voxel-based morphometry-VBM) and white matter (e.g., diffusion tensor imaging-DTI) than traditional visual rating scales. The current study investigated patients with early CMA and healthy control subjects with all three approaches. Neuropsychological assessment focused on executive functions, the cognitive domain most discussed in CMA. The DTI and age-related white matter changes rating scales revealed convergent results showing widespread white matter changes in early CMA. Correlations were found in frontal and parietal areas exclusively with speeded, but not with speed-corrected executive measures. The VBM analyses showed reduced gray matter in frontal areas. All three approaches confirmed the hypothesized fronto-parietal network disruption in early CMA. Innovative methods (DTI) converged with results from conventional methods (visual rating) while allowing greater spatial and tissue accuracy. They are thus valid additions to the analysis of neural correlates of cognitive dysfunction. We found a clear distinction between speeded and nonspeeded executive measures in relationship to imaging parameters. Cognitive slowing is related to disease severity in early CMA and therefore important for early diagnostics.

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Elderly individuals display a rapid age-related increase in intraindividual variability (IIV) of their performances. This phenomenon could reflect subtle changes in frontal lobe integrity. However, structural studies in this field are still missing. To address this issue, we computed an IIV index for a simple reaction time (RT) task and performed magnetic resonance imaging (MRI) including voxel based morphometry (VBM) and the tract based spatial statistics (TBSS) analysis of diffusion tensor imaging (DTI) in 61 adults aged from 22 to 88 years. The age-related IIV increase was associated with decreased fractional anisotropy (FA) as well as increased radial (RD) and mean (MD) diffusion in the main white matter (WM) fiber tracts. In contrast, axial diffusion (AD) and grey matter (GM) densities did not show any significant correlation with IIV. In multivariate models, only FA has an age-independent effect on IIV. These results revealed that WM but not GM changes partly mediated the age-related increase of IIV. They also revealed that the association between WM and IIV could not be only attributed to the damage of frontal lobe circuits but concerned the majority of interhemispheric and intrahemispheric corticocortical connections.

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PURPOSE: To suppress the noise, by sacrificing some of the signal homogeneity for numerical stability, in uniform T1 weighted (T1w) images obtained with the magnetization prepared 2 rapid gradient echoes sequence (MP2RAGE) and to compare the clinical utility of these robust T1w images against the uniform T1w images. MATERIALS AND METHODS: 8 healthy subjects (29.0±4.1 years; 6 Male), who provided written consent, underwent two scan sessions within a 24 hour period on a 7T head-only scanner. The uniform and robust T1w image volumes were calculated inline on the scanner. Two experienced radiologists qualitatively rated the images for: general image quality; 7T specific artefacts; and, local structure definition. Voxel-based and volume-based morphometry packages were used to compare the segmentation quality between the uniform and robust images. Statistical differences were evaluated by using a positive sided Wilcoxon rank test. RESULTS: The robust image suppresses background noise inside and outside the skull. The inhomogeneity introduced was ranked as mild. The robust image was significantly ranked higher than the uniform image for both observers (observer 1/2, p-value = 0.0006/0.0004). In particular, an improved delineation of the pituitary gland, cerebellar lobes was observed in the robust versus uniform T1w image. The reproducibility of the segmentation results between repeat scans improved (p-value = 0.0004) from an average volumetric difference across structures of ≈6.6% to ≈2.4% for the uniform image and robust T1w image respectively. CONCLUSIONS: The robust T1w image enables MP2RAGE to produce, clinically familiar T1w images, in addition to T1 maps, which can be readily used in uniform morphometry packages.

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Recent genetic studies have implicated a number of candidate genes in the pathogenesis of Autism Spectrum Disorder (ASD). Polymorphisms of CNTNAP2 (contactin-associated like protein-2), a member of the neurexin family, have already been implicated as a susceptibility gene for autism by at least 3 separate studies. We investigated variation in white and grey matter morphology using structural MRI and diffusion tensor imaging. We compared volumetric differences in white and grey matter and fractional anisotropy values in control subjects characterised by genotype at rs7794745, a single nucleotide polymorphism in CNTNAP2. Homozygotes for the risk allele showed significant reductions in grey and white matter volume and fractional anisotropy in several regions that have already been implicated in ASD, including the cerebellum, fusiform gyrus, occipital and frontal cortices. Male homozygotes for the risk alleles showed greater reductions in grey matter in the right frontal pole and in FA in the right rostral fronto-occipital fasciculus compared to their female counterparts who showed greater reductions in FA of the anterior thalamic radiation. Thus a risk allele for autism results in significant cerebral morphological variation, despite the absence of overt symptoms or behavioural abnormalities. The results are consistent with accumulating evidence of CNTNAP2's function in neuronal development. The finding suggests the possibility that the heterogeneous manifestations of ASD can be aetiologically characterised into distinct subtypes through genetic-morphological analysis.

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Obesity is one of the key challenges to health care system worldwide and its prevalence is estimated to rise to pandemic proportions. Numerous adverse health effects follow with increasing body weight, including increased risk of hypertension, diabetes, hypercholesterolemia, musculoskeletal pain and cancer. Current evidence suggests that obesity is associated with altered cerebral reward circuit functioning and decreased inhibitory control over appetitive food cues. Furthermore, obesity causes adverse shifts in metabolism and loss of structural integrity within the brain. Prior cross-sectional studies do not allow delineating which of these cerebral changes are recoverable after weight loss. We compared morbidly obese subjects with healthy controls to unravel brain changes associated with obesity. Bariatric surgery was used as an intervention to study which cerebral changes are recoverable after weight loss. In Study I we employed functional magnetic resonance imaging (fMRI) to detect the brain basis of volitional appetite control and its alterations in obesity. In Studies II-III we used diffusion tensor imaging (DTI) and voxel-based morphometry (VBM) to quantify the effects of obesity and the effects of weight loss on structural integrity of the brain. In study IV we used positron emission tomography (PET) with [18F]-FDG in fasting state and during euglycemic hyperinsulinemia to quantify effects of obesity and weight loss on brain glucose uptake. The fMRI experiment revealed that a fronto-parietal network is involved in volitional appetite control. Obese subjects had lower medial frontal and dorsal striatal brain activity during cognitive appetite control and increased functional connectivity within the appetite control circuit. Obese subjects had initially lower grey matter and white matter densities than healthy controls in VBM analysis and loss of integrity in white matter tracts as measured by DTI. They also had initially elevated glucose metabolism under insulin stimulation but not in fasting state. After the weight loss following bariatric surgery, obese individuals’ brain volumes recovered and the insulin-induced increase in glucose metabolism was attenuated. In conclusion, obesity is associated with altered brain function, coupled with loss of structural integrity and elevated glucose metabolism, which are likely signs of adverse health effects to the brain. These changes are reversed by weight loss after bariatric surgery, implicating that weight loss has a causal role on these adverse cerebral changes. Altogether these findings suggest that weight loss also promotes brain health.Key words: brain, obesity, bariatric surgery, appetite control, structural magnetic resonance

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Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.