Study on Lesion Assessment of Cerebello-Thalamo-Cortical Network in Wilson's Disease with Diffusion Tensor Imaging.
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ABSTRACT:
SUBMITTER: Wang A
PROVIDER: S-EPMC5525080 | biostudies-other | 2017
REPOSITORIES: biostudies-other
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Project description:The aim of this research was to test a novel in-vivo brain MRI analysis method that could be used in clinical cohorts to investigate cortical architecture changes in patients with Alzheimer's Disease (AD). Three cohorts of patients with probable AD and healthy volunteers were used to assess the results of the method. The first group was used as the "Discovery" cohort, the second as the "Test" cohort and the last "ATN" (Amyloid, Tau, Neurodegeneration) cohort was used to test the method in an ADNI 3 cohort, comparing to amyloid and Tau PET. The method can detect altered quality of cortical grey matter in AD patients, providing an additional tool to assess AD, distinguishing between these and healthy controls with an accuracy range between good and excellent. These new measurements could be used within the "ATN" framework as an index of cortical microstructure quality and a marker of Neurodegeneration. Further development may aid diagnosis, patient selection, and quantification of the "Neurodegeneration" component in response to therapies in clinical trials.
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Project description:BackgroundPreliminary work has shown that diffusion tensor MRI (DTI) may contribute to the diagnosis of Parkinson's disease (PD).ObjectivesWe conducted a large, prospective, case control study to determine: (1) if fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values on DTI in the basal ganglia and substantia nigra are different between patients with PD and healthy controls; and (2) the predictive value of these parameters and their clinical utility.MethodsDTI imaging was carried out in patients with PD and controls. FA and ADC values were obtained from various brain structures on the DTI scan using the diffusion tensor taskcard. The structures studied were: caudate, putamen, globus pallidus, thalamus and substantia nigra.Results151 subjects (73 PD patients, 41 men, 32 women; mean age 63.6 years) and 78 age and sex matched control subjects were studied. The FA value of the substantia nigra in patients with PD was lower compared with controls (0.403 vs 0.415; p = 0.001). However, no significant differences were demonstrated for FA or ADC values of other structures. Multiple regression analysis revealed that the clinical severity of PD correlated inversely with the FA value in the substantia nigra in patients with PD (regression coefficient -0.019). No single FA value had both a high positive and negative predictive power for PD.ConclusionsWe demonstrated in a large, prospective, case control study that the FA value in the substantia nigra on DTI was lower in PD compared with healthy controls, and correlated inversely with the clinical severity of PD. Further longitudinal studies would be helpful to assess the clinical utility of serial FA measurements of the substantia nigra in objective quantification of disease progression and monitoring of the therapeutic response.
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Project description:Motor skills and the acquisition of brain plasticity are important topics in current research. The development of non-invasive white matter imaging technology, such as diffusion-tensor imaging and the introduction of graph theory make it possible to study the effects of learning skills on the connection patterns of brain networks. However, few studies have characterized the brain network topological features of motor skill learning, especially open skill. Given the need to interact with environmental changes in real time, we hypothesized that the brain network of high-level open-skilled athletes had higher transmission efficiency and stronger interaction in attention, visual and sensorimotor networks. We selected 21 high-level basketball players and 25 ordinary individuals as control subjects, collected their DTI data, built a network of brain structures, and used graph theory to analyze and compare the network properties of the two groups at global and regional levels. In addition, we conducted a correlation analysis on the training years of high-level athletes and brain network nodal parameters on the regional level to assess the relationship between brain network topological characteristics and skills learning. We found that on the global-level, the brain network of high-level basketball players had a shorter path length, small-worldness, and higher global efficiency. On the regional level, the brain nodes of the high-level athletes had nodal parameters that were significantly higher than those of control groups, and were mainly distributed in the visual network, the default mode network, and the attention network. The changes in brain node parameters were significantly related to the number of training years.
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Project description:Conventional diffusion MRI yields voxel-averaged parameters that suffer from ambiguities for heterogeneous anisotropic materials such as brain tissue. Using principles from solid-state NMR spectroscopy, we have previously introduced the shape of the diffusion encoding tensor as a separate acquisition dimension that disentangles isotropic and anisotropic contributions to the observed diffusivities, thereby allowing for unconstrained data inversion into diffusion tensor distributions with "size," "shape," and orientation dimensions. Here we combine our recent non-parametric data inversion algorithm and data acquisition protocol with an imaging pulse sequence to demonstrate spatial mapping of diffusion tensor distributions using a previously developed composite phantom with multiple isotropic and anisotropic components. We propose a compact format for visualizing two-dimensional arrays of the distributions, new scalar parameters quantifying intra-voxel heterogeneity, and a binning procedure giving maps of all relevant parameters for each of the components resolved in the multidimensional distribution space.
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Project description:Our sensory systems provide complementary information about the multimodal objects and events that are the target of perception in everyday life. Professional musicians' specialization in the auditory domain is reflected in the morphology of their brains, which has distinctive characteristics, particularly in areas related to auditory and audio-motor activity. Here, we combined diffusion tensor imaging (DTI) with a behavioral measure of visually induced gain in pitch discrimination, and we used measures of cortical thickness (CT) correlations to assess how auditory specialization and musical expertise are reflected in the structural architecture of white and grey matter relevant to audiovisual processing. Across all participants (n = 45), we found a correlation (p < 0.001) between reliance on visual cues in pitch discrimination and the fractional anisotropy (FA) in the left inferior fronto-occipital fasciculus (IFOF), a structure connecting visual and auditory brain areas. Group analyses also revealed greater cortical thickness correlation between visual and auditory areas in non-musicians (n = 28) compared to musicians (n = 17), possibly reflecting musicians' auditory specialization (FDR < 10%). Our results corroborate and expand current knowledge of functional specialization with a specific focus on audition, and highlight the fact that perception is essentially multimodal while uni-sensory processing is a specialized task.
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Project description:Glucose hypometabolism and gray matter atrophy are well known consequences of Alzheimer's disease (AD). Studies using these measures have shown that the earliest clinical stages, in which memory impairment is a relatively isolated feature, are associated with degeneration in an apparently remote group of areas-mesial temporal lobe (MTL), diencephalic structures such as anterior thalamus and mammillary bodies, and posterior cingulate. These sites are thought to be strongly anatomically inter-connected via a limbic-diencephalic network. Diffusion tensor imaging or DTI-an imaging technique capable of probing white matter tissue microstructure-has recently confirmed degeneration of the white matter connections of the limbic-diencephalic network in AD by way of an unbiased analysis strategy known as tract-based spatial statistics (TBSS). The present review contextualizes the relevance of these findings, in which the fornix is likely to play a fundamental role in linking MTL and diencephalon. An interesting by-product of this work has been in showing that alterations in diffusion behavior are complex in AD-while early studies tended to focus on fractional anisotropy, recent work has highlighted that this measure is not the most sensitive to early changes. Finally, this review will discuss in detail several technical aspects of DTI both in terms of image acquisition and TBSS analysis as both of these factors have important implications to ensure reliable observations are made that inform understanding of neurodegenerative diseases.
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Project description:BACKGROUND:Few studies have examined white matter abnormalities in suicide attempters using diffusion tensor imaging (DTI). This study sought to identify white matter regions altered in individuals with a prior suicide attempt. METHODS:DTI scans were acquired in 13 suicide attempters with major depressive disorder (MDD), 39 non-attempters with MDD, and 46 healthy participants (HP). Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) were determined in the brain using two methods: region of interest (ROI) and tract-based spatial statistics (TBSS). ROIs were limited a priori to white matter adjacent to the caudal anterior cingulate cortex, rostral anterior cingulate cortex, dorsomedial prefrontal cortex, and medial orbitofrontal cortex. RESULTS:Using the ROI approach, suicide attempters had lower FA than MDD non-attempters and HP in the dorsomedial prefrontal cortex. Uncorrected TBSS results confirmed a significant cluster within the right dorsomedial prefrontal cortex indicating lower FA in suicide attempters compared to non-attempters. There were no differences in ADC when comparing suicide attempters, non-attempters and HP groups using ROI or TBSS methods. CONCLUSIONS:Low FA in the dorsomedial prefrontal cortex was associated with a suicide attempt history. Converging findings from other imaging modalities support this finding, making this region of potential interest in determining the diathesis for suicidal behavior.
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Project description:The relationship between stroke topography and functional outcome has largely been studied with binary manual lesion segmentations. However, stroke topography may be better characterized by continuous variables capable of reflecting the severity of ischemia, which may be more pertinent for long-term outcome. Diffusion Tensor Imaging (DTI) constitutes a powerful means of quantifying the degree of acute ischemia and its potential relation to functional outcome. Our aim was to investigate whether using more clinically pertinent imaging parameters with powerful machine learning techniques could improve prediction models and thus provide valuable insight on critical brain areas important for long-term outcome. Eighty-seven thrombolyzed patients underwent a DTI sequence at 24 h post-stroke. Functional outcome was evaluated at 3 months post-stroke with the modified Rankin Score and was dichotomized into good (mRS ≤ 2) and poor (mRS > 2) outcome. We used support vector machines (SVM) to classify patients into good vs. poor outcome and evaluate the accuracy of different models built with fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity asymmetry maps, and lesion segmentations in combination with lesion volume, age, recanalization status, and thrombectomy treatment. SVM classifiers built with axial diffusivity maps yielded the best accuracy of all imaging parameters (median [IQR] accuracy = 82.8 [79.3-86.2]%), compared to that of lesion segmentations (76.7 [73.3-82.8]%) when predicting 3-month functional outcome. The analysis revealed a strong contribution of clinical variables, notably - in descending order - lesion volume, thrombectomy treatment, and recanalization status, in addition to the deep white matter at the crossroads of major white matter tracts, represented by brain regions where model weights were highest. Axial diffusivity is a more appropriate imaging marker to characterize stroke topography for predicting long-term outcome than binary lesion segmentations.
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