964 resultados para diffusion tensor imaging
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PURPOSE: To determine how the ADC value of parotid glands is influenced by the choice of b-values. MATERIALS AND METHODS: In eight healthy volunteers, diffusion-weighted echo-planar imaging (DW-EPI) was performed on a 1.5 T system, with b-values (in seconds/mm2) of 0, 50, 100, 150, 200, 250, 300, 500, 750, and 1000. ADC values were calculated by two alternative methods (exponential vs. logarithmic fit) from five different sets of b-values: (A) all b-values; (B) b=0, 50, and 100; (C) b=0 and 750; (D) b=0, 500, and 1000; and (E) b=500, 750, and 1000. RESULTS: The mean ADC values for the different settings were (in 10(-3) mm2/second, exponential fit): (A) 0.732+/-0.019, (B) 2.074+/-0.084, (C) 0.947+/-0.020, (D) 0.890+/-0.023, and (E) 0.581+/-0.021. ADC values were significantly (P <0.001) different for all pairwise comparisons of settings (A-E) of b-values, except for A vs. D (P=0.172) and C vs. D (P=0.380). The ADC(B) was significantly higher than ADC(C) or ADC(D), which was significantly higher than ADC(E). ADC values from exponential vs. logarithmic fit (P=0.542), as well as left vs. right parotid gland (P=0.962), were indistinguishable. CONCLUSION: The ADC values calculated from low b-value settings were significantly higher than those calculated from high b-value settings. These results suggest that not only true diffusion but also perfusion and saliva flow may contribute to the ADC.
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PURPOSE To study the apparent diffusivity and its directionality for metabolites of skeletal muscle in humans in vivo by (1) H magnetic resonance spectroscopy. METHODS The diffusion tensors were determined on a 3 Tesla MR system using optimized acquisition and processing methods including an adapted STEAM sequence with orientation-dependent diffusion weighting, pulse-triggering with individually adapted delays, eddy-current correction schemes, median filtering, and simultaneous prior-knowledge fitting of all related spectra. RESULTS The average apparent diffusivities, as well as the fractional anisotropies of taurine (ADCav = 0.74 × 10(-3) s/mm(2) , FA = 0.46), creatine (ADCav = 0.41 × 10(-3) s/mm(2) , FA = 0.33), trimethylammonium compounds (ADCav = 0.48 × 10(-3) s/mm(2) , FA = 0.34), carnosine (ADCav = 0.46 × 10(-3) s/mm(2) , FA = 0.47), and water (ADCav = 1.5 × 10(-3) s/mm(2) , FA = 0.36) were estimated. The diffusivities of most metabolites and water were significantly different from each other. Diffusion was found to be anisotropic and the diffusion tensors showed tensor correlation coefficients close to 1 and were hence found to be essentially coaligned. The magnitudes of apparent metabolite diffusivities were largely ordered according to molecular weight, with taurine as the smallest molecule diffusing fastest, both along and across the fiber direction. CONCLUSION Diffusivities, directional dependence of diffusion and fractional anisotropies of (1) H MRS-visible muscle metabolites were presented. It was shown that metabolites share diffusion directionality with water and have similar fractional anisotropies, hinting at similar diffusion barriers. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.
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Spinal cord injury (SCI) is a devastating condition that affects people in the prime of their lives. A myriad of vascular events occur after SCI, each of which contributes to the evolving pathology. The primary trauma causes mechanical damage to blood vessels, resulting in hemorrhage. The blood-spinal cord barrier (BSCB), a neurovascular unit that limits passage of most agents from systemic circulation to the central nervous system, breaks down, resulting in inflammation, scar formation, and other sequelae. Protracted BSCB disruption may exacerbate cellular injury and hinder neurobehavioral recovery in SCI. In these studies, angiopoietin-1 (Ang1), an agent known to reduce vascular permeability, was hypothesized to attenuate the severity of secondary injuries of SCI. Using longitudinal magnetic resonance imaging (MRI) studies (dynamic contrast-enhanced [DCE]-MRI for quantification of BSCB permeability, highresolution anatomical MRI for calculation of lesion size, and diffusion tensor imaging for assessment of axonal integrity), the acute, subacute, and chronic effects of Ang1 administration after SCI were evaluated. Neurobehavioral assessments were also performed. These non-invasive techniques have applicability to the monitoring of therapies in patients with SCI. In the acute phase of injury, Ang1 was found to reduce BSCB permeability and improve neuromotor recovery. Dynamic contrast-enhanced MRI revealed a persistent compromise of the BSCB up to two months post-injury. In the subacute phase of injury, Ang1’s effect on reducing BSCB permeability was maintained and it was found to transiently reduce axonal integrity. The SCI lesion burden was assessed with an objective method that compared favorably with segmentations from human raters. In the chronic phase of injury, Ang1 resulted in maintained reduction in BSCB permeability, a decrease in lesion size, and improved axonal integrity. Finally, longitudinal correlations among data from the MRI modalities and neurobehavioral assays were evaluated. Locomotor recovery was negatively correlated with lesion size in the Ang1 cohort and positively correlated with diffusion measures in the vehicle cohort. In summary, the results demonstrate a possible role for Ang1 in mitigating the secondary pathologies of SCI during the acute and chronic phases of injury.
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BACKGROUND: To investigate if non-rigid image-registration reduces motion artifacts in triggered and non-triggered diffusion tensor imaging (DTI) of native kidneys. A secondary aim was to determine, if improvements through registration allow for omitting respiratory-triggering. METHODS: Twenty volunteers underwent coronal DTI of the kidneys with nine b-values (10-700 s/mm2 ) at 3 Tesla. Image-registration was performed using a multimodal nonrigid registration algorithm. Data processing yielded the apparent diffusion coefficient (ADC), the contribution of perfusion (FP ), and the fractional anisotropy (FA). For comparison of the data stability, the root mean square error (RMSE) of the fitting and the standard deviations within the regions of interest (SDROI ) were evaluated. RESULTS: RMSEs decreased significantly after registration for triggered and also for non-triggered scans (P < 0.05). SDROI for ADC, FA, and FP were significantly lower after registration in both medulla and cortex of triggered scans (P < 0.01). Similarly the SDROI of FA and FP decreased significantly in non-triggered scans after registration (P < 0.05). RMSEs were significantly lower in triggered than in non-triggered scans, both with and without registration (P < 0.05). CONCLUSION: Respiratory motion correction by registration of individual echo-planar images leads to clearly reduced signal variations in renal DTI for both triggered and particularly non-triggered scans. Secondarily, the results suggest that respiratory-triggering still seems advantageous.J. Magn. Reson. Imaging 2014. (c) 2014 Wiley Periodicals, Inc.
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The brain is a complex neural network with a hierarchical organization and the mapping of its elements and connections is an important step towards the understanding of its function. Recent developments in diffusion-weighted imaging have provided the opportunity to reconstruct the whole-brain structural network in-vivo at a large scale level and to study the brain structural substrate in a framework that is close to the current understanding of brain function. However, methods to construct the connectome are still under development and they should be carefully evaluated. To this end, the first two studies included in my thesis aimed at improving the analytical tools specific to the methodology of brain structural networks. The first of these papers assessed the repeatability of the most common global and local network metrics used in literature to characterize the connectome, while in the second paper the validity of further metrics based on the concept of communicability was evaluated. Communicability is a broader measure of connectivity which accounts also for parallel and indirect connections. These additional paths may be important for reorganizational mechanisms in the presence of lesions as well as to enhance integration in the network. These studies showed good to excellent repeatability of global network metrics when the same methodological pipeline was applied, but more variability was detected when considering local network metrics or when using different thresholding strategies. In addition, communicability metrics have been found to add some insight into the integration properties of the network by detecting subsets of nodes that were highly interconnected or vulnerable to lesions. The other two studies used methods based on diffusion-weighted imaging to obtain knowledge concerning the relationship between functional and structural connectivity and about the etiology of schizophrenia. The third study integrated functional oscillations measured using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) as well as diffusion-weighted imaging data. The multimodal approach that was applied revealed a positive relationship between individual fluctuations of the EEG alpha-frequency and diffusion properties of specific connections of two resting-state networks. Finally, in the fourth study diffusion-weighted imaging was used to probe for a relationship between the underlying white matter tissue structure and season of birth in schizophrenia patients. The results are in line with the neurodevelopmental hypothesis of early pathological mechanisms as the origin of schizophrenia. The different analytical approaches selected in these studies also provide arguments for discussion of the current limitations in the analysis of brain structural networks. To sum up, the first studies presented in this thesis illustrated the potential of brain structural network analysis to provide useful information on features of brain functional segregation and integration using reliable network metrics. In the other two studies alternative approaches were presented. The common discussion of the four studies enabled us to highlight the benefits and possibilities for the analysis of the connectome as well as some current limitations.
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BACKGROUND AND PURPOSE Lesion volume on diffusion-weighted magnetic resonance imaging (DWI) before acute stroke therapy is a predictor of outcome. Therefore, patients with large volumes are often excluded from therapy. The aim of this study was to analyze the impact of endovascular treatment in patients with large DWI lesion volumes (>70 mL). METHODS Three hundred seventy-two patients with middle cerebral or internal carotid artery occlusions examined with magnetic resonance imaging before treatment since 2004 were included. Baseline data and 3 months outcome were recorded prospectively. DWI lesion volumes were measured semiautomatically. RESULTS One hundred five patients had lesions >70 mL. Overall, the volume of DWI lesions was an independent predictor of unfavorable outcome, survival, and symptomatic intracerebral hemorrhage (P<0.001 each). In patients with DWI lesions >70 mL, 11 of 31 (35.5%) reached favorable outcome (modified Rankin scale score, 0-2) after thrombolysis in cerebral infarction 2b-3 reperfusion in contrast to 3 of 35 (8.6%) after thrombolysis in cerebral infarction 0-2a reperfusion (P=0.014). Reperfusion success, patient age, and DWI lesion volume were independent predictors of outcome in patients with DWI lesions >70 mL. Thirteen of 66 (19.7%) patients with lesions >70 mL had symptomatic intracerebral hemorrhage with a trend for reduced risk with avoidance of thrombolytic agents. CONCLUSIONS There was a growing risk for poor outcome and symptomatic intracerebral hemorrhage with increasing pretreatment DWI lesion volumes. Nevertheless, favorable outcome was achieved in every third patient with DWI lesions >70 mL after successful endovascular reperfusion, whereas after poor or failed reperfusion, outcome was favorable in only every 12th patient. Therefore, endovascular treatment might be considered in patients with large DWI lesions, especially in younger patients.
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Diffusion-weighted imaging (DWI) is an established diagnostic tool with regards to the central nervous system (CNS) and research into its application in the musculoskeletal system has been growing. It has been shown that DWI has utility in differentiating vertebral compression fractures from malignant ones, assessing partial and complete tears of the anterior cruciate ligament (ACL), monitoring tumor response to therapy, and characterization of soft-tissue and bone tumors. DWI is however less useful in differentiating malignant vs. infectious processes. As of yet, no definitive qualitative or quantitative properties have been established due to reasons ranging from variability in acquisition protocols to overlapping imaging characteristics. Even with these limitations, DWI can still provide clinically useful information, increasing diagnostic accuracy and improving patient management when magnetic resonance imaging (MRI) findings are inconclusive. The purpose of this article is to summarize recent research into DWI applications in the musculoskeletal system.
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Multiple nonmorphologic magnetic resonance sequences are available in musculoskeletal imaging that can provide additional information to better characterize and diagnose musculoskeletal disorders and diseases. These sequences include blood-oxygen-level-dependent (BOLD), arterial spin labeling (ASL), diffusion-weighted imaging (DWI), and diffusion-tensor imaging (DTI). BOLD and ASL provide different methods to evaluate skeletal muscle microperfusion. The BOLD signal reflects the ratio between oxyhemoglobin and deoxyhemoglobin. ASL uses selective tagging of inflowing blood spins in a specific region for calculating local perfusion. DWI and DTI provide information about the structural integrity of soft tissue including muscles and fibers as well as pathologies.
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OBJECTIVES Readout-segmented echo planar imaging (rs-EPI) significantly reduces susceptibility artifacts in diffusion-weighted imaging (DWI) of the breast compared to single-shot EPI but is limited by longer scan times. To compensate for this, we tested a new simultaneous multi-slice (SMS) acquisition for accelerated rs-EPI. MATERIALS AND METHODS After approval by the local ethics committee, eight healthy female volunteers (age, 38.9±13.1 years) underwent breast MRI at 3T. Conventional as well as two-fold (2× SMS) and three-fold (3× SMS) slice-accelerated rs-EPI sequences were acquired at b-values of 50 and 800s/mm(2). Two independent readers analyzed the apparent diffusion coefficient (ADC) in fibroglandular breast parenchyma. The signal-to-noise ratio (SNR) was estimated based on the subtraction method. ADC and SNR were compared between sequences by using the Friedman test. RESULTS The acquisition time was 4:21min for conventional rs-EPI, 2:35min for 2× SMS rs-EPI and 1:44min for 3× SMS rs-EPI. ADC values were similar in all sequences (mean values 1.62×10(-3)mm(2)/s, p=0.99). Mean SNR was 27.7-29.6, and no significant differences were found among the sequences (p=0.83). CONCLUSION SMS rs-EPI yields similar ADC values and SNR compared to conventional rs-EPI at markedly reduced scan time. Thus, SMS excitation increases the clinical applicability of rs-EPI for DWI of the breast.
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High Angular Resolution Diffusion Imaging (HARDI) techniques, including Diffusion Spectrum Imaging (DSI), have been proposed to resolve crossing and other complex fiber architecture in the human brain white matter. In these methods, directional information of diffusion is inferred from the peaks in the orientation distribution function (ODF). Extensive studies using histology on macaque brain, cat cerebellum, rat hippocampus and optic tracts, and bovine tongue are qualitatively in agreement with the DSI-derived ODFs and tractography. However, there are only two studies in the literature which validated the DSI results using physical phantoms and both these studies were not performed on a clinical MRI scanner. Also, the limited studies which optimized DSI in a clinical setting, did not involve a comparison against physical phantoms. Finally, there is lack of consensus on the necessary pre- and post-processing steps in DSI; and ground truth diffusion fiber phantoms are not yet standardized. Therefore, the aims of this dissertation were to design and construct novel diffusion phantoms, employ post-processing techniques in order to systematically validate and optimize (DSI)-derived fiber ODFs in the crossing regions on a clinical 3T MR scanner, and develop user-friendly software for DSI data reconstruction and analysis. Phantoms with a fixed crossing fiber configuration of two crossing fibers at 90° and 45° respectively along with a phantom with three crossing fibers at 60°, using novel hollow plastic capillaries and novel placeholders, were constructed. T2-weighted MRI results on these phantoms demonstrated high SNR, homogeneous signal, and absence of air bubbles. Also, a technique to deconvolve the response function of an individual peak from the overall ODF was implemented, in addition to other DSI post-processing steps. This technique greatly improved the angular resolution of the otherwise unresolvable peaks in a crossing fiber ODF. The effects of DSI acquisition parameters and SNR on the resultant angular accuracy of DSI on the clinical scanner were studied and quantified using the developed phantoms. With a high angular direction sampling and reasonable levels of SNR, quantification of a crossing region in the 90°, 45° and 60° phantoms resulted in a successful detection of angular information with mean ± SD of 86.93°±2.65°, 44.61°±1.6° and 60.03°±2.21° respectively, while simultaneously enhancing the ODFs in regions containing single fibers. For the applicability of these validated methodologies in DSI, improvement in ODFs and fiber tracking from known crossing fiber regions in normal human subjects were demonstrated; and an in-house software package in MATLAB which streamlines the data reconstruction and post-processing for DSI, with easy to use graphical user interface was developed. In conclusion, the phantoms developed in this dissertation offer a means of providing ground truth for validation of reconstruction and tractography algorithms of various diffusion models (including DSI). Also, the deconvolution methodology (when applied as an additional DSI post-processing step) significantly improved the angular accuracy of the ODFs obtained from DSI, and should be applicable to ODFs obtained from the other high angular resolution diffusion imaging techniques.
Evidence of altered prefrontal-thalamic circuitry in schizophrenia: An optimised diffusion MRI study
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MRI diffusion tensor imaging (DTI), optimized for measuring the trace of the diffusion tensor, was used to investigate microstructural changes in the brains of 12 individuals with schizophrenia compared with 12 matched control subjects. To control for the effects of anatomic variation between subject groups, all participants' diffusion images were non-linearly registered to standard anatomical space. Significant statistical differences in mean diffusivity (MD) measures between the two groups were determined on a pixel-by-pixel basis, using Gaussian random field theory. We found significantly elevated MD measures within temporal, parietal and prefrontal cortical regions in the schizophrenia group (P > 0.001), especially within the medial frontal gyrus and anterior cingulate. The dorsal medial and anterior nucleus of the thalamus, including the caudate, also exhibited significantly increased MD in the schizophrenia group (P > 0.001). This study has shown for the first time that MD measures offer an alternative strategy for investigating altered prefrontal-thalamic circuitry in schizophrenia. (c) 2006 Elsevier Inc. All rights reserved.
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The NTRK1 gene (also known as TRKA) encodes a high-affinity receptor for NGF, a neurotrophin involved in nervous system development and myelination. NTRK1 has been implicated in neurological function via links between the T allele at rs6336 (NTRK1-T) and schizophrenia risk. A variant in the neurotrophin gene, BDNF, was previously associated with white matter integrity in young adults, highlighting the importantce of neurotrophins to white matter development. We hypothesized that NTRK1-T would relate to lower fractional anisotropy in healthy adults. We scanned 391 healthy adult human twins and their siblings (mean age: 23.6 ± 2.2 years; 31 NTRK1-T carriers, 360 non-carriers) using 105-gradient diffusion tensor imaging at 4 tesla. We evaluated in brain white matter how NTRK1-T and NTRK1 rs4661063 allele A (rs4661063-A, which is in moderate linkage disequilibrium with rs6336) related to voxelwise fractional anisotropy-acommondiffusion tensor imaging measure of white matter microstructure. We used mixed-model regression to control for family relatedness, age, and sex. The sample was split in half to test reproducibility of results. The false discovery rate method corrected for voxelwise multiple comparisons. NTRK1-T and rs4661063-A correlated with lower white matter fractional anisotropy, independent of age and sex (multiple-comparisons corrected: false discovery rate critical p=0.038 forNTRK1-Tand0.013 for rs4661063-A). In each half-sample, theNTRK1-T effectwasreplicated in the cingulum, corpus callosum, superior and inferior longitudinal fasciculi, inferior fronto-occipital fasciculus, superior corona radiata, and uncinate fasciculus. Our results suggest that NTRK1-T is important for developing white matter microstructure.
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There is a strong genetic risk for late-onset Alzheimer's disease (AD), but so far few gene variants have been identified that reliably contribute to that risk. A newly confirmed genetic risk allele C of the clusterin (CLU) gene variant rs11136000 is carried by ~88% of Caucasians. The C allele confers a 1.16 greater odds of developing late-onset AD than the T allele. AD patients have reductions in regional white matter integrity. We evaluated whether the CLU risk variant was similarly associated with lower white matter integrity in healthy young humans. Evidence of early brain differences would offer a target for intervention decades before symptom onset. We scanned 398 healthy young adults (mean age, 23.6 ± 2.2 years) with diffusion tensor imaging, a variation of magnetic resonance imaging sensitive to white matter integrity in the living brain. We assessed genetic associations using mixed-model regression at each point in the brain to map the profile of these associations with white matter integrity. Each C allele copy of the CLUvariant was associated with lower fractional anisotropy-a widely accepted measure of white matter integrity-in multiple brain regions, including several known to degenerate in AD. These regions included the splenium of the corpus callosum, the fornix, cingulum, and superior and inferior longitudinal fasciculi in both brain hemispheres. Young healthy carriers of the CLU gene risk variant showed a distinct profile of lower white matter integrity that may increase vulnerability to developing AD later in life.
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The NTRK3 gene (also known as TRKC) encodes a high affinity receptor for the neurotrophin 3'-nucleotidase (NT3), which is implicated in oligodendrocyte and myelin development. We previously found that white matter integrity in young adults is related to common variants in genes encoding neurotrophins and their receptors. This underscores the importance of neurotrophins for white matter development. NTRK3 variants are putative risk factors for schizophrenia, bipolar disorder, and obsessive-compulsive disorder hoarding, suggesting that some NTRK3 variants may affect the brain.To test this, we scanned 392 healthy adult twins and their siblings (mean age, 23.6. ±. 2.2. years; range: 20-29. years) with 105-gradient 4-Tesla diffusion tensor imaging (DTI). We identified 18 single nucleotide polymorphisms (SNPs) in the NTRK3 gene that have been associated with neuropsychiatric disorders. We used a multi-SNP model, adjusting for family relatedness, age, and sex, to relate these variants to voxelwise fractional anisotropy (FA) - a DTI measure of white matter integrity.FA was optimally predicted (based on the highest false discovery rate critical p), by five SNPs (rs1017412, rs2114252, rs16941261, rs3784406, and rs7176429; overall FDR critical p=. 0.028). Gene effects were widespread and included the corpus callosum genu and inferior longitudinal fasciculus - regions implicated in several neuropsychiatric disorders and previously associated with other neurotrophin-related genetic variants in an overlapping sample of subjects. NTRK3 genetic variants, and neurotrophins more generally, may influence white matter integrity in brain regions implicated in neuropsychiatric disorders.
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Genetic correlation (rg) analysis determines how much of the correlation between two measures is due to common genetic influences. In an analysis of 4 Tesla diffusion tensor images (DTI) from 531 healthy young adult twins and their siblings, we generalized the concept of genetic correlation to determine common genetic influences on white matter integrity, measured by fractional anisotropy (FA), at all points of the brain, yielding an NxN genetic correlation matrix rg(x,y) between FA values at all pairs of voxels in the brain. With hierarchical clustering, we identified brain regions with relatively homogeneous genetic determinants, to boost the power to identify causal single nucleotide polymorphisms (SNP). We applied genome-wide association (GWA) to assess associations between 529,497 SNPs and FA in clusters defined by hubs of the clustered genetic correlation matrix. We identified a network of genes, with a scale-free topology, that influences white matter integrity over multiple brain regions.