Diffusion Tensor Imaging Biomarkers Research Articles

Diffusion tensor imaging biomarkers and clinical assessments in amyotrophic lateral sclerosis (ALS) patients: an exploratory study.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by progressive loss of upper and lower motor neurons. Biomarkers are needed to improve diagnosis, gauge progression, and evaluate treatment. Diffusion tensor imaging (DTI) is a promising biomarker for detecting microstructural alterations in the white matter tracts. This study aimed to assess DTI metrics as biomarkers and to examine their relationship with clinical assessments in patients with ALS. Eleven patients with ALS and 21 healthy controls (HCs) underwent 3T MRI with DTI. DTI metrics, including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD), were compared between key motor and extra-motor tract groups. Group comparisons and correlations between DTI metrics also correlated with clinical scores of disability (ALSFRS-R), muscle strength (dynamometry), and motor unit loss (MUNIX). Widespread differences were found between patients with ALS and HCs in DTI metrics, including decreased FA and increased diffusivity metrics. However, MD and RD are more sensitive metrics for detecting white matter changes in patients with ALS. Significant interhemispheric correlations between the tract DTI metrics were also observed. DTI metrics showed symmetry between the hemispheres and correlated with the clinical assessments. MD, RD, and AD increases significantly correlated with lower ALSFRS-R and MUNIX scores and weaker dynamometry results. DTI reveals microstructural damage along the motor and extra-motor regions in ALS patients. DTI metrics can serve as quantitative neuroimaging biomarkers for diagnosis, prognosis, monitoring of progression, and treatment. Combined analysis of imaging, electrodiagnostic, and functional biomarkers shows potential for characterizing disease pathophysiology and progression.

Brain diffusion MRI biomarkers after oncology treatments.

In addition to providing a measurement of the tumor's size and dimensions, magnetic resonance imaging (MRI) provides excellent noninvasive radiographic detection of tumor location. The MRI technique is an important modality that has been shown to be useful in the prognosis, diagnosis, treatment planning, and evaluation of response and recurrence in solid cancers. Diffusion-weighted imaging (DWI) is an imaging technique that quantifies water mobility. This imaging approach is good for identifying sub-voxel microstructure of tissues, correlates with tumor cellularity, and has been proven to be valuable in the early assessment of cytotoxic treatment for a variety of malignancies. Diffusion tensor imaging (DTI) is an MRI method that assesses the preferred amount of water transport inside tissues. This enables precise measurements of water diffusion, which changes according to the direction of white matter fibers, their density, and myelination. This measurement corresponds to some related variables: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD), and others. DTI biomarkers can detect subtle changes in white matter microstructure and integrity following radiation therapy (RT) or chemoradiotherapy, which may have implications for cognitive function and quality of life. In our study, these indices were evaluated after brain chemoradiotherapy.

Diffusion Tensor Imaging in Amyotrophic Lateral Sclerosis: Machine Learning for Biomarker Development.

Diffusion tensor imaging (DTI) allows the in vivo imaging of pathological white matter alterations, either with unbiased voxel-wise or hypothesis-guided tract-based analysis. Alterations of diffusion metrics are indicative of the cerebral status of patients with amyotrophic lateral sclerosis (ALS) at the individual level. Using machine learning (ML) models to analyze complex and high-dimensional neuroimaging data sets, new opportunities for DTI-based biomarkers in ALS arise. This review aims to summarize how different ML models based on DTI parameters can be used for supervised diagnostic classifications and to provide individualized patient stratification with unsupervised approaches in ALS. To capture the whole spectrum of neuropathological signatures, DTI might be combined with additional modalities, such as structural T1w 3-D MRI in ML models. To further improve the power of ML in ALS and enable the application of deep learning models, standardized DTI protocols and multi-center collaborations are needed to validate multimodal DTI biomarkers. The application of ML models to multiparametric MRI/multimodal DTI-based data sets will enable a detailed assessment of neuropathological signatures in patients with ALS and the development of novel neuroimaging biomarkers that could be used in the clinical workup.

Correlations between DTI-derived metrics and MRS metabolites in tumour regions of glioblastoma: a pilot study.

IntroductionSpecific correlations among diffusion tensor imaging (DTI)-derived metrics and magnetic resonance spectroscopy (MRS) metabolite ratios in brains with glioblastoma are still not completely understood.Patients and methodsWe made retrospective cohort study. MRS ratios (choline-to-N-acetyl aspartate [Cho/NAA], lipids and lactate to creatine [LL/Cr], and myo-inositol/creatine [mI/Cr]) were correlated with eleven DTI biomarkers: mean diffusivity (MD), fractional anisotropy (FA), pure isotropic diffusion (p), pure anisotropic diffusion (q), the total magnitude of the diffusion tensor (L), linear tensor (Cl), planar tensor (Cp), spherical tensor (Cs), relative anisotropy (RA), axial diffusivity (AD) and radial diffusivity (RD) at the same regions: enhanced rim, peritumoral oedema and normal-appearing white matter. Correlational analyses of 546 MRS and DTI measurements used Spearman coefficient.ResultsAt the enhancing rim we found four significant correlations: FA ⇔ LL/Cr, Rs = -.364, p = .034; Cp ⇔ LL/Cr, Rs = .362, p = .035; q ⇔ LL/Cr, Rs = -.349, p = .035; RA ⇔ LL/Cr, Rs = -.357, p = .038. Another ten pairs of significant correlations were found in the peritumoral edema: AD ⇔ LL/Cr, AD ⇔ mI/Cr, MD ⇔ LL/Cr, MD ⇔ mI/Cr, p ⇔ LL/Cr, p ⇔ mI/ Cr, RD ⇔ mI/Cr, RD ⇔ mI/Cr, L ⇔ LL/Cr, L ⇔ mI/Cr.ConclusionsDTI and MRS biomarkers answer different questions; peritumoral oedema represents the biggest challenge with at least ten significant correlations between DTI and MRS that need additional studies. The fact that DTI and MRS measures are not specific of one histologic type of tumour broadens their application to a wider variety of intracranial pathologies.

A prospective harmonized multicenter DTI study of cerebral white matter degeneration in ALS.

To evaluate progressive white matter (WM) degeneration in amyotrophic lateral sclerosis (ALS). Sixty-six patients with ALS and 43 healthy controls were enrolled in a prospective, longitudinal, multicenter study in the Canadian ALS Neuroimaging Consortium (CALSNIC). Participants underwent a harmonized neuroimaging protocol across 4 centers that included diffusion tensor imaging (DTI) for assessment of WM integrity. Three visits were accompanied by clinical assessments of disability (ALS Functional Rating Scale-Revised [ALSFRS-R]) and upper motor neuron (UMN) function. Voxel-wise whole-brain and quantitative tract-wise DTI assessments were done at baseline and longitudinally. Correction for site variance incorporated data from healthy controls and from healthy volunteers who underwent the DTI protocol at each center. Patients with ALS had a mean progressive decline in fractional anisotropy (FA) of the corticospinal tract (CST) and frontal lobes. Tract-wise analysis revealed reduced FA in the CST, corticopontine/corticorubral tract, and corticostriatal tract. CST FA correlated with UMN function, and frontal lobe FA correlated with the ALSFRS-R score. A progressive decline in CST FA correlated with a decline in the ALSFRS-R score and worsening UMN signs. Patients with fast vs slow progression had a greater reduction in FA of the CST and upper frontal lobe. Progressive WM degeneration in ALS is most prominent in the CST and frontal lobes and, to a lesser degree, in the corticopontine/corticorubral tracts and corticostriatal pathways. With the use of a harmonized imaging protocol and incorporation of analytic methods to address site-related variances, this study is an important milestone toward developing DTI biomarkers for cerebral degeneration in ALS. NCT02405182.

Comparing model-based cerebrovascular physiomarkers with DTI biomarkers in MCI patients.

ObjectiveTo compare the novel model‐based hemodynamic physiomarker of Dynamic Vasomotor Reactivity (DVR) with biomarkers based on Diffusion Tensor Imaging (DTI) and some widely used neurocognitive scores in terms of their ability to delineate patients with amnestic Mild Cognitive Impairment (MCI) from age‐matched cognitively normal controls.Materials & MethodsThe model‐based DVR and MRI‐based DTI markers were obtained from 36 patients with amnestic MCI and 16 age‐matched controls without cognitive impairment, for whom widely used neurocognitive scores were available. These markers and scores were subsequently compared in terms of statistical delineation between patients and controls.ResultsIt was found that statistically significant delineation between MCI patients and controls was comparable for DVR or DTI markers (p < 0.01). The performance of both types of markers was consistent with the scores of some (but not all) widely used neurocognitive tests.ConclusionSince DTI offers a measure of cerebral white matter integrity, the results suggest that the model‐based hemodynamic marker of DVR may correlate with cognitive impairment due to white matter lesions. This finding is consistent with the hypothesis that dysregulation of cerebral microcirculation may be an early cause of cognitive impairment, which has been recently corroborated by several studies.

Diffusion Tensor Imaging Biomarkers to Predict Motor Outcomes in Stroke: A Narrative Review.

Stroke is a leading cause of disability worldwide. Motor impairments occur in most of the patients with stroke in the acute phase and contribute substantially to disability. Diffusion tensor imaging (DTI) biomarkers such as fractional anisotropy (FA) measured at an early phase after stroke have emerged as potential predictors of motor recovery. In this narrative review, we: (1) review key concepts of diffusion MRI (dMRI); (2) present an overview of state-of-art methodological aspects of data collection, analysis and reporting; and (3) critically review challenges of DTI in stroke as well as results of studies that investigated the correlation between DTI metrics within the corticospinal tract and motor outcomes at different stages after stroke. We reviewed studies published between January, 2008 and December, 2018, that reported correlations between DTI metrics collected within the first 24 h (hyperacute), 2–7 days (acute), and >7–90 days (early subacute) after stroke. Nineteen studies were included. Our review shows that there is no consensus about gold standards for DTI data collection or processing. We found great methodological differences across studies that evaluated DTI metrics within the corticospinal tract. Despite heterogeneity in stroke lesions and analysis approaches, the majority of studies reported significant correlations between DTI biomarkers and motor impairments. It remains to be determined whether DTI results could enhance the predictive value of motor disability models based on clinical and neurophysiological variables.

Potential of a statistical approach for the standardization of multicenter diffusion tensor data: A phantom study

Diffusion tensor imaging (DTI) parameters, such as fractional anisotropy (FA), allow examining the structural integrity of the brain. However, the true value of these parameters may be confounded by variability in MR hardware, acquisition parameters, and image quality. To examine the effects of confounding factors on FA and to evaluate the feasibility of statistical methods to model and reduce multicenter variability. Longitudinal multicenter study. DTI single strand phantom (HQ imaging). 3T diffusion tensor imaging. Thirteen European imaging centers participated. DTI scans were acquired every 6 months and whenever maintenance or upgrades to the system were performed. A total of 64 scans were acquired in 2 years, obtained by three scanner vendors, using six individual head coils, and 12 software versions. The variability in FA was assessed by the coefficients of variation (CoV). Several linear mixed effects models (LMEM) were developed and compared by means of the Akaike Information Criterion (AIC). The CoV was 2.22% for mean FA and 18.40% for standard deviation of FA. The variables "site" (P = 9.26 × 10-5 ), "vendor" (P = 2.18 × 10-5 ), "head coil" (P = 9.00 × 10-4 ), "scanner drift," "bandwidth" (P = 0.033), "TE" (P = 8.20 × 10-6 ), "SNR" (P = 0.029) and "mean residuals" (P = 6.50 × 10-4 ) had a significant effect on the variability in mean FA. The variables "site" (P = 4.00 × 10-4 ), "head coil" (P = 2.00 × 10-4 ), "software" (P = 0.014), and "mean voxel outlier intensity count" (P = 1.10 × 10-4 ) had a significant effect on the variability in standard deviation of FA. The mean FA was best predicted by an LMEM that included "vendor" and the interaction term of "SNR" and "head coil" as model factors (AIC -347.98). In contrast, the standard deviation of FA was best predicted by an LMEM that included "vendor," "bandwidth," "TE," and the interaction term between "SNR" and "head coil" (AIC -399.81). Our findings suggest that perhaps statistical models seem promising to model the variability in quantitative DTI biomarkers for clinical routine and multicenter studies. 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:955-965.

A robust diffusion tensor model for clinical applications of MRI to cartilage.

Diffusion tensor imaging (DTI) of articular cartilage is a promising technique for the early diagnosis of osteoarthritis (OA). However, in vivo diffusion tensor (DT) measurements suffer from low signal-to-noise ratio (SNR) that can result in bias when estimating the six parameters of the full DT, thus reducing sensitivity. This study seeks to validate a simplified four-parameter DT model (zeppelin) for obtaining more robust and sensitive in vivo DTI biomarkers of cartilage. We use simulations in a substrate to mimic changes during OA; and analytic simulations of the DT drawn from a range of fractional anisotropies (FA) measured with high-quality DT data from ex vivo human cartilage. We also use in vivo data from the knees of a healthy subject and two OA patients with Kellgren-Lawrence (KL) grades 1 and 2. For simulated in vivo cartilage SNR (∼25) and anisotropy levels, the estimated mean values of MD from the DT and zeppelin models were identical to the ground truth values. However, zeppelin's FA is more accurate in measuring water restriction. More specifically, the FA estimations of the DT model were additionally biased by between +2% and +48% with respect to zeppelin values. Additionally, both mean diffusivity (MD) and FA of the zeppelin had lower parameter variance compared to the full DT (F-test, P < 0.05). We observe the same trends from in vivo values of patient data. The zeppelin is more robust than the full DT for cartilage diffusion anisotropy and SNR at levels typically encountered in clinical applications of articular cartilage. Magn Reson Med 79:1157-1164, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

The impact of signal-to-noise ratio, diffusion-weighted directions and image resolution in cardiac diffusion tensor imaging \u2013 insights from the ex-vivo rat heart

BackgroundCardiac diffusion tensor imaging (DTI) is limited by scan time and signal-to-noise (SNR) restrictions. This invariably leads to a trade-off between the number of averages, diffusion-weighted directions (ND), and image resolution. Systematic evaluation of these parameters is therefore important for adoption of cardiac DTI in clinical routine where time is a key constraint.MethodsHigh quality reference DTI data were acquired in five ex-vivo rat hearts. We then retrospectively set 2 ≤ SNR ≤ 97, 7 ≤ ND ≤ 61, varied the voxel volume by up to 192-fold and investigated the impact on the accuracy and precision of commonly derived parameters.ResultsFor maximal scan efficiency, the accuracy and precision of the mean diffusivity is optimised when SNR is maximised at the expense of ND. With typical parameter settings used clinically, we estimate that fractional anisotropy may be overestimated by up to 13% with an uncertainty of ±30%, while the precision of the sheetlet angles may be as poor as ±31°. Although the helix angle has better precision of ±14°, the transmural range of helix angles may be under-estimated by up to 30° in apical and basal slices, due to partial volume and tapering myocardial geometry.ConclusionsThese findings inform a baseline of understanding upon which further issues inherent to in-vivo cardiac DTI, such as motion, strain and perfusion, can be considered. Furthermore, the reported bias and reproducibility provides a context in which to assess cardiac DTI biomarkers.

Structural and diffusion imaging versus clinical assessment to monitor amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis is a progressive neurodegenerative disease that affects upper and lower motor neurons. Observational and intervention studies can be tracked using clinical measures such as the revised Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R) but for a complete understanding of disease progression, objective in vivo biomarkers of both central and peripheral motor pathway pathology are highly desirable. The aim of this study was to determine the utility of structural and diffusion imaging as central nervous system biomarkers compared to the standard clinical measure, ALSFRS-R, to track longitudinal evolution using three time-point measurements. N = 34 patients with ALS were scanned and clinically assessed three times at a mean of three month time intervals. The MRI biomarkers were structural T1-weighted volumes for cortical thickness measurement as well as deep grey matter volumetry, voxel-based morphometry and diffusion tensor imaging (DTI). Cortical thickness focused specifically on the precentral gyrus while quantitative DTI biomarkers focused on the corticospinal tracts. The evolution of imaging biomarkers and ALSFRS-R scores over time were analysed using a mixed effects model that accounted for the scanning interval as a fixed effect variable, and, the initial measurements and time from onset as random variables. The mixed effects model showed a significant decrease in the ALSFRS-R score, (p < 0.0001, and an annual rate of change (AROC) of − 7.3 points). Similarly, fractional anisotropy of the corticospinal tract showed a significant decrease (p = 0.009, AROC = − 0.0066) that, in turn, was driven by a significant increase in radial diffusivity combined with a trend to decrease in axial diffusivity. No significant change in cortical thickness of the precentral gyrus was found (p > 0.5). In addition, deep grey matter volumetry and voxel-based morphometry also identified no significant changes. Furthermore, the availability of three time points was able to indicate that there was a linear progression in both clinical and fractional anisotropy measures adding to the validity of these results. The results indicate that DTI is clearly a superior imaging marker compared to atrophy for tracking the evolution of the disease and can act as a central nervous biomarker in longitudinal studies. It remains, however, less sensitive than the ALSFRS-R score for monitoring decline over time.

The impact of myelination on axon sparing and locomotor function recovery in spinal cord injury assessed using diffusion tensor imaging

The dysmyelinated axons of shiverer mice exhibit impaired conduction characteristics, similar to early postnatal axons before myelination, whereas the patterns of neuronal activity and connectivity are relatively comparable with those of wild-type myelinated axons. This unique dysmyelination pattern is exploited in the present study to determine the role of compact myelin in the loss and recovery of function following traumatic spinal cord injury (SCI). We applied in vivo diffusion tensor imaging (DTI) and post-mortem immunohistochemistry analysis to examine changes in myelin and axonal integrity, and evaluated these changes in concert with the analysis of locomotor function from 1 to 4 weeks following a mid-thoracic contusion injury in homozygous shiverer and heterozygous littermate mice. The DTI biomarkers, axial and radial diffusivities, are noninvasive indicators of axon and myelin integrity in response to SCI of both myelinated and dysmyelinated spinal cord. We show that myelin is critical for normal hind limb function in open field locomotion. However, when the functional outcome is limited during chronic SCI, the extent of recovery is associated with residual axonal integrity and independent of the extent of intact myelin at the lesion epicenter.

Hippocampal-Thalamic Disruption Predicts Cognitive Function in Relapsing-Remitting Multiple Sclerosis (S51.006)

Objective: To investigate hippocampal-thalamic disruption in relapsing-remitting multiple sclerosis (RRMS) and its contribution to cognition. Background Thalamic and hippocampal atrophy have been demonstrated in RRMS patients and are associated with cognitive dysfunction and episodic memory impairment. We hypothesized that hippocampal-thalamic pathways, primarily the fornix and the cingulum bundles, play a role in the cognitive decline. Damage to the uncinate fasciculus, a temporal-frontal pathway, has also been linked to memory function in MS. We used Diffusion Tensor Imaging (DTI) to identify and evaluate the integrity of these pathways in RRMS patients and controls and assessed their contributions to cognition. Design/Methods: A neuropsychological battery was administered to 27 RRMS patients and 20 age and gender matched healthy controls. Results, to Z-scores, were averaged across three cognitive domains: attention/executive function, verbal memory, and spatial memory. Two DTI averages were acquired at 3T with 30 non-collinear diffusion directions using a B-value of 1000 s/mm2. Tractography and white matter skeletonization were used to identify the centermost voxels of 3 bilateral white matter pathways: the fornix, the cingulum and the uncinate fasciculus. Mean FA for each pathway was contrasted across groups using mixed ANOVA. For each cognitive domain, step-wise linear regression considered mean FA of each pathway, age and Beck Depression Inventory (BDI) as predictors of cognitive function. Results: Mean FA was significantly reduced in RRMS patients in each of the 3 pathways (p=.003). In the RRMS group, cingulum FA was the only independent predictor of attention/executive function (beta=3.74, adjusted R-squared=0.16, p=0.021); fornix FA was the only independent predictor of verbal memory (beta=2.74, adjR-squared=0.114, p=0.048); and both uncinate FA and BDI were independent predictors of spatial memory (beta1=17.65, beta2=-0.048, adjR-square=0.382, p=0.001). Controls showed no significant associations. Conclusions: Hippocampal-thalamic-frontal lobe disruption may underlie cognitive dysfunction in RRMS. DTI biomarkers may identify RRMS patients that would benefit from cognitive therapies. Supported by: The Consortium of Multiple Sclerosis Centers Foundation medical student scholarship (KCK) and the National Multiple Sclerosis Society RG 3914 (NLS). Disclosure: Dr. Kern has nothing to disclose. Dr. Lee has nothing to disclose. Dr. Montag has nothing to disclose. Dr. Horsfall has nothing to disclose. Dr. Gold has received personal compensation for activities with Novartis as a consultant. Dr. O9Connor has nothing to disclose. Dr. Sicotte has nothing to disclose.

Role of Family History for Alzheimer Biomarker Abnormalities in the Adult Children Study

To assess whether family history (FH) of Alzheimer disease (AD) alone influences AD biomarker abnormalities. Adult Children Study. Washington University's Charles F. and Joanne Knight Alzheimer's Disease Research Center. A total of 269 cognitively normal middle- to older-aged individuals with and without an FH for AD. Clinical and cognitive measures, magnetic resonance imaging-based brain volumes, diffusion tensor imaging-based white matter microstructure, cerebrospinal fluid biomarkers, and molecular imaging of cerebral fibrillar amyloid with positron emission tomography using the [(11)C] benzothiazole tracer, Pittsburgh compound B. A positive FH for AD was associated with an age-related decrease of cerebrospinal fluid Aβ42; the ε4 allele of apolipoprotein E (APOE4) did not alter this effect. Age-adjusted cerebrospinal fluid Aβ42 was decreased for individuals with APOE4 compared with the level for those without, and the decrease was larger for individuals with a positive FH compared with the decrease for those without. The variation of cerebrospinal fluid tau and Pittsburgh compound B mean cortical binding potential increased by age. For individuals younger than 55, an age-related increase in mean cortical binding potential was associated with APOE4 but not FH. For individuals older than 55, a positive FH and a positive APOE4 implied the fastest age-related increase in mean cortical binding potential. A positive FH was associated with decreased fractional anisotropy from diffusion tensor imaging in the genu and splenium of the corpus callosum. Independent of APOE4, FH is associated with age-related change of several cerebrospinal fluid, Pittsburgh compound B, and diffusion tensor imaging biomarkers in cognitively normal middle- to older-aged individuals, suggesting that non- APOE susceptibility genes for AD influence AD biomarkers.

Assessment of Skeletal Muscle Damage in Mice using Diffusion Tensor MRI

Diagnosis of acute muscle strains is still typically made based on physical exam and patient history, but muscle injuries can be detected with magnetic resonance imaging (MRI). Conventionally, muscle strains are revealed best by T2-weighted MRI, which optimizes contrast between edema and muscular tissue. PURPOSE: To determine if variables calculated from diffusion tensor imaging (DTI) would serve as an earlier and more sensitive marker of damage after a muscle strain injury in dystrophic (mdx) and control mice. We hypothesize that DTI biomarkers will provide a more informative assessment of muscle injury, and these measures will further elucidate the increased susceptibility to injury of the mdx model. METHODS: Unilateral injury to the tibialis anterior muscle (TA) was induced by 15 maximal lengthening contractions in mdx mice (n=3) and control mice (n=3). High resolution T1 and T2-weighted structural MRI (100μm × 100μm × 750 μm) including T2 mapping and spin echo DTI (150μm × 150μm × 750 μm × 12 directions) were acquired on a 7T MRI system. T2 and diffusion tensor parameters (ie apparent diffusion coefficient [ADC], fractional anisotropy [FA], axial and radial diffusivity [AD and RD]) were calculated at each pixel location. TA imaging was compared to functional changes and HE staining and immunofluorescent labeling of TA cross-sections. RESULTS: Injury was confirmed by a significant loss of isometric torque (85% in mdx vs. 42% in controls). Parameter values were calculated as the percent increase in relation to the contralateral, uninjured TA of each animal. Greater increase in ADC, AD, and RD of the injured muscle was present in the mdx mice vs. controls when compared at proximal, medial, and distal locations of the muscle. These changes were paralleled by decreases in FA. On average, changes in DTI parameters were 1.8× greater in the mdx mice vs. controls. In comparison, changes in T2 did not indicate clear differences between mdx and controls. CONCLUSIONS: These data suggest that DTI may be a better indicator of muscle injury, even at early time points where the MR signal changes are dominated by local edema. Supported by grants from the Muscular Dystrophy association (MDA, grant 4278) and NIH-NIAMS (K01AR053235) to RML