Eigenvalues Of Diffusion Tensor Research Articles

Cardiac Diffusion Tensor Biomarkers of Chronic Infarction Based on In Vivo Data

In vivo cardiac diffusion tensor imaging (cDTI) data were acquired in swine subjects six to ten weeks post-myocardial infarction (MI) to identify microstructural-based biomarkers of MI. Diffusion tensor invariants, diffusion tensor eigenvalues, and radial diffusivity (RD) are evaluated in the infarct, border, and remote myocardium, and compared with extracellular volume fraction (ECV) and native T1 values. Additionally, to aid the interpretation of the experimental results, the diffusion of water molecules was numerically simulated as a function of ECV. Finally, findings based on in vivo measures were confirmed using higher-resolution and higher signal-to-noise data acquired ex vivo in the same subjects. Mean diffusivity, diffusion tensor eigenvalues, and RD increased in the infarct and border regions compared to remote myocardium, while fractional anisotropy decreased. Secondary (e2) and tertiary (e3) eigenvalues increased more significantly than the primary eigenvalue in the infarct and border regions. These findings were confirmed by the diffusion simulations. Although ECV presented the largest increase in infarct and border regions, e2, e3, and RD increased the most among non-contrast-based biomarkers. RD is of special interest as it summarizes the changes occurring in the radial direction and may be more robust than e2 or e3 alone.

On co-existing diffusive and anti-diffusive tracer transport by oceanic mesoscale eddies

A common approach for parameterising eddy transport of passive tracers by mesoscale eddies in the ocean is by invoking a transport tensor. The symmetric part of this tensor, the diffusion tensor, quantifies diffusive eddy tracer transport. Recent studies have diagnosed opposite-signed eigenvalues (diffusivities) of the diffusion tensor from eddy-resolving simulations, while all current parameterisations implement only positive diffusivities. For opposite-signed eigenvalues the associated diffusive eddy tracer flux is not necessarily down-gradient and therefore may not mix the tracer by transferring variance to the small scales. In this study we explore such diffusive eddy fluxes by using an eddy-resolving simulation of passive tracers with a relaxation (source/sink) forcing. After confirming that the diffusion tensors for different tracer pairs have opposite-signed eigenvalues, we show that the corresponding diffusive eddy tracer flux drives a net down-gradient transfer of variance, as would be guaranteed when the diffusion tensor eigenvalues are both positive. Locally up-gradient fluxes are common, with their frequency strongly dependent on the relaxation profile. The effects of weakening/strengthening the relaxation on the frequency of down-gradient fluxes is different for each tracer. However, for all tracers considered the amplitude of the net down-gradient transfer weakens as the relaxation strengthens, a consequence of the homogeneous diffusion dissipating less eddy variance. Our results indicate that for oceanic tracers with sources/sinks the parameterised diffusive eddy tracer fluxes should not be globally down-gradient.

Geometric Distortion Correction of Renal Diffusion Tensor Imaging Using the Reversed Gradient Method.

Renal echo planar diffusion tensor imaging (DTI) has clinical potential but suffers from geometric distortion. We evaluated feasibility of reversed gradient distortion correction in 10 diabetic patients and 6 volunteers. Renal area, apparent diffusion coefficient, fractional anisotropy, and tensor eigenvalues were measured on uncorrected and distortion-corrected DTI. Corrected DTI correlated better than uncorrected DTI (r = 0.904 vs 0.840, P = 0.002) with reference anatomic T2-weighted imaging, with no significant difference in DTI metrics.

Diffusion biomarkers in chronic myocardial infarction.

Cardiac diffusion tensor magnetic resonance imaging (cDTI) allows estimating the aggregate cardiomyocyte architecture in healthy subjects and its remodeling as a result of cardiac disease. In this study, cDTI was used to quantify microstructural changes occurring in swine (N=7) six to ten weeks after myocardial infarction. Each heart was extracted and imaged ex vivo with 1mm isotropic spatial resolution. Microstructural changes were quantified in the border zone and infarct region by comparing diffusion tensor invariants - fractional anisotropy (FA), mode, and mean diffusivity (MD) - radial diffusivity, and diffusion tensor eigenvalues with the corresponding values in the remote myocardium. MD and radial diffusivity increased in the infarct and border regions with respect to the remote myocardium (p<0.01). In contrast, FA and mode decreased in the infarct and border regions (p<0.01). Diffusion tensor eigenvalues also increased in the infarct and border regions, with a larger increase in the secondary and tertiary eigenvalues.

Probing cardiomyocyte mobility with multi-phase cardiac diffusion tensor MRI.

Cardiomyocyte organization and performance underlie cardiac function, but the in vivo mobility of these cells during contraction and filling remains difficult to probe. Herein, a novel trigger delay (TD) scout sequence was used to acquire high in-plane resolution (1.6 mm) Spin-Echo (SE) cardiac diffusion tensor imaging (cDTI) at three distinct cardiac phases. The objective was to characterize cardiomyocyte organization and mobility throughout the cardiac cycle in healthy volunteers. Nine healthy volunteers were imaged with cDTI at three distinct cardiac phases (early systole, late systole, and diastasis). The sequence used a free-breathing Spin-Echo (SE) cDTI protocol (b-values = 350s/mm2, twelve diffusion encoding directions, eight repetitions) to acquire high-resolution images (1.6x1.6x8mm3) at 3T in ~7 minutes/cardiac phase. Helix Angle (HA), Helix Angle Range (HAR), E2 angle (E2A), Transverse Angle (TA), Mean Diffusivity (MD), diffusion tensor eigenvalues (λ1-2-3), and Fractional Anisotropy (FA) in the left ventricle (LV) were characterized. Images from the patient-specific TD scout sequence demonstrated that SE cDTI acquisition was possible at early systole, late systole, and diastasis in 78%, 100% and 67% of the cases, respectively. At the mid-ventricular level, mobility (reported as median [IQR]) was observed in HAR between early systole and late systole (76.9 [72.6, 80.5]° vs 96.6 [85.9, 100.3]°, p<0.001). E2A also changed significantly between early systole, late systole, and diastasis (27.7 [20.8, 35.1]° vs 45.2 [42.1, 49]° vs 20.7 [16.6, 26.4]°, p<0.001). We demonstrate that it is possible to probe cardiomyocyte mobility using multi-phase and high resolution cDTI. In healthy volunteers, aggregate cardiomyocytes re-orient themselves more longitudinally during contraction, while cardiomyocyte sheetlets tilt radially during wall thickening. These observations provide new insights into the three-dimensional mobility of myocardial microstructure during systolic contraction.

Mixed Noise Removal Algorithm Combining Adaptive Directional Weighted Mean Filter and Improved Adaptive Anisotropic Diffusion Model

A mixed noise removal algorithm combining adaptive directional weighted mean filter and improved adaptive anisotropic diffusion model is proposed. Firstly, a noise classification method is introduced to divide all pixels into two types as the pixels corrupted by impulse noise and the pixels corrupted by Gaussian noise. Then an adaptive directional weighted mean filter is developed to remove impulse noise, which can adaptively select the optimal direction template from twelve direction templates and replace the gray level of each impulse noise corrupted pixel by the weighted mean gray level of pixels on the optimal direction template. Finally, an improved adaptive anisotropic diffusion model is developed to remove Gaussian noise in the initial denoised image, which can finely classify image features as smooth regions, edges, corners, and isolated noises by characteristic parameters and variance parameter and conduct adaptive diffusion for different image features by designing reasonable eigenvalues of diffusion tensor. A large number of experimental results show that the proposed algorithm outperforms many existing main mixed noise removal methods in terms of image denoising and detail preservation.

A review of anisotropic conductivity models of brain white matter based on diffusion tensor imaging.

The conductivity of brain tissues is not only essential for electromagnetic source estimation (ESI), but also a key reflector of the brain functional changes. Different from the other brain tissues, the conductivity of whiter matter (WM) is highly anisotropic and a tensor is needed to describe it. The traditional electrical property imaging methods, such as electrical impedance tomography (EIT) and magnetic resonance electrical impedance tomography (MREIT), usually fail to image the anisotropic conductivity tensor of WM with high spatial resolution. The diffusion tensor imaging (DTI) is a newly developed technique that can fulfill this purpose. This paper reviews the existing anisotropic conductivity models of WM based on the DTI and discusses their advantages and disadvantages, as well as identifies opportunities for future research on this subject. It is crucial to obtain the linear conversion coefficient between the eigenvalues of anisotropic conductivity tensor and diffusion tensor, since they share the same eigenvectors. We conclude that the electrochemical model is suitable for ESI analysis because the conversion coefficient can be directly obtained from the concentration of ions in extracellular liquid and that the volume fraction model is appropriate to study the influence of WM structural changes on electrical conductivity. Graphical abstract ᅟ.

An edge fusion scheme for image denoising based on anisotropic diffusion models

In this paper, we propose an enhanced anisotropic diffusion model. The improved model can classify finely image information as smooth regions, edges, corners and isolated noises by characteristic parameters and gradient variance parameter. And for different image information the eigenvalues of diffusion tensor are designed to conduct adaptive diffusion. Moreover, an edge fusion scheme is posed to preserve edges after denoising by combing different denoising and edge detection methods. Firstly, different denoising methods are applied for noisy image to obtain denoised images, and the best method among them is selected as main method. Then edge images of denoised images are obtained by edge detection methods. Finally, by fusing edge images together more integrated edges can be achieved to replace edges of denoised image obtained by main method. The experimental results show the proposed model can denoise meanwhile preserve edges and corners, and the edge fusion scheme is accurate and effective.

Whole-Body Diffusion Tensor Imaging: A Feasibility Study.

The aim of this study was to demonstrate the feasibility of whole-body diffusion tensor imaging (DTI) as a promising tool for research applications, for instance, for investigation of systemic muscle diseases. Twelve healthy volunteers (mean age, 26.6 years; range, 20-39 years) underwent whole-body magnetic resonance imaging at 3 T using an echo planar imaging sequence (b value, 400 s/mm) with 6 different spatial encoding directions. Coronal maps of DTI parameters including mean diffusivity, fractional anisotropy, and diffusion tensor eigenvalues (λ1-3) were generated using in-house MATLAB routines. Diffusion tensor imaging parameters were evaluated by region-of-interest analysis in skeletal muscle, cerebral gray and white matter, the kidneys, and the liver. The acquisition time was 79 minutes 12 seconds. The different organs could be clearly depicted on the parametrical maps. Exemplary values in skeletal muscle were mean diffusivity, 1.67 ± 0.16 × 10(-3) mm2/s; fractional anisotropy, 0.26 ± 0.03; λ1, 2.17 ± 0.20 × 10(-3) mm2/s; λ2, 1.64 ± 0.17 × 10(-3) mm2/s; and λ3, 1.22 ± 0.12 × 10(-3) mm2/s. Whole-body DTI is technically feasible. Further refinements are required to achieve a higher signal-to-noise ratio and improved spatial resolution. A possible clinical application could be the assessment of systemic myopathies.

Diffusion-tensor imaging of the growing ends of long bones: pilot demonstration of columnar structure in the physes and metaphyses of the knee.

To determine the feasibility of using in vivo diffusion-tensor imaging and tractography of the physis to examine changes related to rate of growth, location, and age. This retrospective study was institutional review board approved and HIPAA compliant and the requirement for informed consent was waived. Diffusion-tensor imaging of the knee was performed at 3.0 T in 31 subjects (nine boys and 22 girls) with a median age of 13.6 years. The mean ages of boys and girls were 14.7 years (range, 12.0-18.3 years) and 13.2 years (range, 7.0-18.6 years), respectively. Regions of interest were placed in the physis of the tibia and femur, and in the epiphyseal and articular cartilage of these bones. Tractography was performed by using a fractional anisotropic threshold of 0.15 and an angle threshold of 40°. The tractographic patterns were qualitatively evaluated and changes related to age were described. The tract-based apparent diffusion coefficient, fractional anistropy, tensor eigenvalues, and tract length were measured. Diffusion parameters were compared between the center and periphery of the physis, and between the distal femur and proximal tibia. Tractography resulted in parallel tracts in the physis and the adjacent metaphysis. Tractographic pattern changed with age, with individuals approaching physeal closure having shorter tracts in a random arrangement. Patterns of tractography varied with age in the femur (P < .001) and tibia (P < .001). Femoral tracts (median length, 6.5 mm) were longer than tibial tracts (median length, 4.3 mm) (P < .001). Tracts in the periphery of the physes were longer than those in the center (femur, P = .005; tibia, P = .004). In the physis of the femur and tibia, a significant age-related decrease was observed in apparent diffusion coefficient (P < .001 for both), axial diffusion (femur, P = .001; tibia, P < .001), and transverse diffusion [P < .001 for both]), and an age-related increase was seen in fractional anistropy (P < .001, for both). Diffusion-tensor imaging shows the columnar microstructure of the physis and adjacent metaphysis, and provides further insight into normal growth.

Quantitative evaluation of the axonal degeneration of central motor neurons in chronic cerebral stroke with diffusion tensor imaging

Conventional magnetic resonance imaging (MRI) can only show the degeneration-induced morphological changes but fail to quantitatively reveal the degree and extent of the axonal damage of nerve fibers. Diffusion tensor imaging (DTI) has the ability to detect the diffusion of water molecules and thus suitable to the study of axonal degeneration of central motor neurons. To illustrate and quantitatively evaluate the axonal degeneration of central motor neurons in patients with chronic cerebral stroke. DTI and conventional MRI were carried out with 10 normal control subjects and 25 patients who suffered from chronic cerebral stroke in the region supplied by middle cerebral artery and had varying degrees of limb movement disorders (the mean time of onset was 2.5 months), to measure the fractional anisotropy (FA), volume ratio (VR), apparent diffusion coefficient (ADC), tensor eigenvalues (λ1, λ2, and λ3), and signal intensity (SI) on T2-weighted images, of the central motor fibers (pyramidal tract) in the plane of cerebral peduncle. Results from the ipsilateral side were compared with those from the contralateral side in the same patient and with those from normal control. The axonal degeneration of central motor neurons manifests in DTI as the decline of FA of the pyramidal tract and the reduction and distortion of the high signal area. While all the FA, VR, ADC, and λ1 in the ipsilateral side reduce on DTI, λ3 increases; the T2-weighted signals exhibit no significant differences among groups. The changes and diffusions of water molecule associated with the axonal degeneration of central motor neurons after chronic cerebral stroke can be detected by DTI, which can directly quantitatively reflect the degree and extent of axonal degeneration of central motor neurons and can compensate the shortcomings of conventional MRI and diffusion-weighted imaging (DWI).

Quantitative effects of inclusion of fat on muscle diffusion tensor MRI measurements

To determine the minimum water percentage in a muscle region of interest that would allow diffusion tensor (DT-) MRI data to reflect the diffusion properties of pure muscle accurately. Proton density-weighted images with and without fat saturation were obtained at the mid-thigh in four subjects. Co-registered DT-MR images were used to calculate the diffusion tensor's eigenvalues and fractional anisotropy. The eigenvalues transitioned monotonically as a function of water signal percentage from values near to those expected for pure fat to those for pure muscle. Also, the fractional anisotropy transitioned monotonically from 0.50 (fat) to 0.20 (muscle). For water signal percentages >55%, none of the diffusion indices differed significantly from those for regions of >90% muscle. Accounting for the T1 and T2 values of muscle and fat and the pulse sequence properties, it is concluded that, as a conservative estimate, regions must contain at least 76% muscle tissue to reflect the diffusion properties of pure muscle accurately.

An exploration into diffusion tensor imaging in the bovine ocular lens

We describe our development of the diffusion tensor imaging modality for the bovine ocular lens. Diffusion gradients were added to a spin-echo pulse sequence and the relevant parameters of the sequence were refined to achieve good diffusion weighting in the lens tissue, which demonstrated heterogeneous regions of diffusive signal attenuation. Decay curves for b-value (loosely summarizes the strength of diffusion weighting) and TE (determines the amount of magnetic resonance imaging-obtained signal) were used to estimate apparent diffusion coefficients (ADC) and T2 in different lens regions. The ADCs varied by over an order of magnitude and revealed diffusive anisotropy in the lens. Up to 30 diffusion gradient directions, and 8 signal acquisition averages, were applied to lenses in culture in order to improve maps of diffusion tensor eigenvalues, equivalent to ADC, across the lens. From these maps, fractional anisotropy maps were calculated and compared to known spatial distributions of anisotropic molecular fluxes in the lens. This comparison suggested new hypotheses and experiments to quantitatively assess models of circulation in the avascular lens.

Diffusion Fractional Anisotropy-based Transformation in Skeletal Muscle Caused by Pressure

We used diffusion tensor imaging (DTI) to evaluate anisotropic changes in skeletal muscle cells under external pressure. In 6 healthy volunteers, we compared DTI of the tibialis anterior (TA) and soleus (SOL) muscles under pressure. We performed imaging using a 1.5-tesla magnetic resonance (MR) scanner and diffusion-weighted stimulated-echo echo-planar pulse sequences optimized for skeletal muscle. We calculated diffusion tensor eigenvalues (λ), apparent diffusion coefficients, and fractional anisotropy (FA) values in a series of axially acquired DTI and compared them between the pressurized and nonpressurized lower limbs. We also measured a cross-sectional area of skeletal muscle. We observed clear differences in FA and λ₃ between pressurized muscles and the nonpressurized muscles we used as controls. The mean control FAs were 0.36±0.02 (TA) and 0.30±0.02 (SOL). The mean control λ₃s were 0.74±0.02 s/mm² (TA) and 0.85±0.03 s/mm² (SOL). FA values in the pressurized (200 mmHg) limbs increased to 0.39±0.02 (TA) and 0.35±0.04 (SOL) compared with those values in the nonpressurized controls. λ₃ values in the pressurized (200 mmHg) limbs decreased to 0.68±0.05 s/mm² (TA) and 0.77±0.06 s/mm² (SOL) compared with those in controls. Moreover, the mean value of cross-sectional area of skeletal muscle (control) was 907.3±140.1 mm² (TA) and 1522±201.0 mm² (SOL). The cross-sectional area in the pressurized (200 mmHg) limbs decreased to 590.3±68.1 mm² (TA) and 1131±112.6 mm² (SOL) compared with those in controls. One-way analysis of variance (ANOVA) and post hoc Tukey-Kramer tests showed significant differences. Anisotropy changed markedly on pressurizing the lower limb based on the correlation of the cross-sectional area and λ₃ suggested marked changed in anisotropy following application of pressure to the lower limb. If compression of the cross-sectional area is assumed to represent compression of the cell, change in λ₃ reflected the change in the size of muscle cells.

FRATS: Functional Regression Analysis of DTI Tract Statistics

Diffusion tensor imaging (DTI) provides important information on the structure of white matter fiber bundles as well as detailed tissue properties along these fiber bundles in vivo. This paper presents a functional regression framework, called FRATS, for the analysis of multiple diffusion properties along fiber bundle as functions in an infinite dimensional space and their association with a set of covariates of interest, such as age, diagnostic status and gender, in real applications. The functional regression framework consists of four integrated components: the local polynomial kernel method for smoothing multiple diffusion properties along individual fiber bundles, a functional linear model for characterizing the association between fiber bundle diffusion properties and a set of covariates, a global test statistic for testing hypotheses of interest, and a resampling method for approximating the p-value of the global test statistic. The proposed methodology is applied to characterizing the development of five diffusion properties including fractional anisotropy, mean diffusivity, and the three eigenvalues of diffusion tensor along the splenium of the corpus callosum tract and the right internal capsule tract in a clinical study of neurodevelopment. Significant age and gestational age effects on the five diffusion properties were found in both tracts. The resulting analysis pipeline can be used for understanding normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles.

Using Perturbation theory to reduce noise in diffusion tensor fields

We propose the use of Perturbation theory to reduce noise in Diffusion Tensor (DT) fields. Diffusion Tensor Imaging (DTI) encodes the diffusion of water molecules along different spatial directions in a positive definite, 3 x 3 symmetric tensor. Eigenvectors and eigenvalues of DTs allow the in vivo visualization and quantitative analysis of white matter fiber bundles across the brain. The validity and reliability of these analyses are limited, however, by the low spatial resolution and low Signal-to-Noise Ratio (SNR) in DTI datasets. Our procedures can be applied to improve the validity and reliability of these quantitative analyses by reducing noise in the tensor fields. We model a tensor field as a three-dimensional Markov Random Field and then compute the likelihood and the prior terms of this model using Perturbation theory. The prior term constrains the tensor field to be smooth, whereas the likelihood term constrains the smoothed tensor field to be similar to the original field. Thus, the proposed method generates a smoothed field that is close in structure to the original tensor field. We evaluate the performance of our method both visually and quantitatively using synthetic and real-world datasets. We quantitatively assess the performance of our method by computing the SNR for eigenvalues and the coherence measures for eigenvectors of DTs across tensor fields. In addition, we quantitatively compare the performance of our procedures with the performance of one method that uses a Riemannian distance to compute the similarity between two tensors, and with another method that reduces noise in tensor fields by anisotropically filtering the diffusion weighted images that are used to estimate diffusion tensors. These experiments demonstrate that our method significantly increases the coherence of the eigenvectors and the SNR of the eigenvalues, while simultaneously preserving the fine structure and boundaries between homogeneous regions, in the smoothed tensor field.

Cognitive Control and White Matter Callosal Microstructure in Methamphetamine-Dependent Subjects: A Diffusion Tensor Imaging Study

Methamphetamine (MA) abuse causes damage to structures within the human cerebrum, with particular susceptibility to white matter (WM). Abnormalities have been reported in anterior regions with less evidence of changes in posterior regions. Methamphetamine abusers have also shown deficits on attention tests that measure response conflict and cognitive control. We examined cognitive control with a computerized measure of the Stroop selective attention task and indices of WM microstructure obtained from diffusion tensor imaging (DTI) in the callosal genu and splenium of 37 currently abstinent MA abusers and 17 non-substance abusing control subjects. Measurements of fractional anisotropy (FA), apparent diffusion coefficient (ADC) of callosal fibers, and diffusion tensor eigenvalues were obtained in all subjects. The MA abusers exhibited greater Stroop reaction time interference (i.e., reduced cognitive control) (p = .04) compared with control subjects. After correcting for multiple comparisons, FA within the genu correlated significantly with measures of cognitive control in the MA abusers (p = .04, Bonferroni corrected) but not in control subjects (p = .26). Group differences in genu but not splenium FA were trend significant (p = .09). Methamphetamine abuse seems to alter anterior callosal WM microstructure with less evidence of change within posterior callosal WM microstructure. The DTI indices within the genu but not splenium correlated with measures of cognitive control in chronic MA abusers.

DESARROLLO Y PUESTA EN MARCHA DE SOFTWARE DE TRACTOGRAFIA

Abstract: Diffusion weighted MRI can measure the random motion of water molecules in biological tissue. These motions are captured using magnetic gradients that dephase the precession of water molecules that move along the direction of the gradient. Dephasings show up as small attenuations in signal intensity.This information can be used in tissues such as muscles, spine, medulla and white matter to measure the ani-sotropy and assess fiber integrity. In this work, a new software for the post-processing of diffusion weighted MRI is presented.The software can read datasets from a variety of scanners. Diffusion is modeled using ellipsoids that are represented mathematically by means of a tensor, estimated from entry dataset. Various indices such as diffusion tensor eigenvalues, fractional anisotropy, types of anisotropy, mean diffu-sivity, and principal directions are computed. Results are interactively visualized by using axial planes or a three-dimensional approach. The software includes a nerve fiber tracing module. This tool works on PC-based workstations through a graphical user interface or by using the command line.

Diffusion tensor imaging eigenvalues: Preliminary evidence for altered myelin in cocaine dependence

Reduced fractional anisotropy (FA) in Diffusion Tensor Imaging (DTI) has been reported in cocaine dependent subjects compared to non-drug using controls. There are several pathological mechanisms that could be responsible for these findings, since FA can be reduced through damage to axonal tracts and by neuronal loss. One way of obtaining more information about pathology underlying changes in FA on DTI is diffusion tensor eigenvalues, representing diffusion along the fiber tract ( λ 1) or perpendicular to the fiber tract ( λ T). Thirteen cocaine dependent subjects and 18 healthy controls underwent full brain DTI. Eigenvalues λ 1 and λ T of the corpus callosum were compared between cocaine users and controls. For λ T there was a significant interaction of group × region of corpus callosum. Exploratory analysis of the subregions showed higher λ T in the genu of the anterior corpus callosum of cocaine dependent subjects compared to control subjects. For λ 1 there was no significant interaction of group × region of corpus callosum. Based on prior studies suggesting that alteration or damage to myelin increases diffusion perpendicular to the direction of fiber tracts ( λ T) with minimal effect on λ 1 these findings are consistent with altered myelin in the corpus callosum in cocaine dependent subjects.

Mechanisms of normal appearing corpus callosum injury related to pericallosal T1 lesions in multiple sclerosis using directional diffusion tensor and 1H MRS imaging

Objectives: To investigate the extent of tissue damage in a region of normal appearing corpus callosum (NACC) for different forms of multiple sclerosis (MS) using diffusion tensor and proton magnetic...