Clinically feasible diffusion MRI in muscle: Time dependence and initial findings in Duchenne muscular dystrophy

Purpose: To characterize the diffusion time-dependence in muscle in healthy adult volunteers, boys with Duchenne’s muscular dystrophy (DMD), and age-matched controls in a clinically feasible acquisition time for pediatric applications. / Methods: Diffusion data were acquired using a pulsed gradient stimulated echo diffusion preparation at 5 different diffusion times (70, 130, 190, 250, and 330 ms), at 4 different b-values (0, 200, 400, 600, and 800 s/mm2) and 6 directions (orthogonal x, y, and z and diagonal xy, xz, and yz) and processed to obtain standard diffusion indices (mean diffusivity [MD] and fractional anisotropy [FA]) at each diffusion time. / Results Time-dependent diffusion was seen in muscle in healthy adult volunteers, boys with DMD, and age-matched controls. Boys with DMD showed reduced MD and increased FA values in comparison to age matched controls across a range of diffusion times. A diffusion time of Δ = 190 ms had the largest effect size. / Conclusions: These results could be used to optimize diffusion imaging in this disease further and imply that these diffusion indices may become an important biomarker in monitoring progression in DMD in the future

Normal values and test–retest variability of stimulated-echo diffusion tensor imaging and fat fraction measurements in the muscle

OBJECTIVES: To assess the test–retest variability of both diffusion parameters and fat fraction (FF) estimates in normal muscle, and to assess differences in normal values between muscles in the thigh. METHODS: 29 healthy volunteers (mean age 37 years, range 20–60 years, 17/29 males) completed the study. Magnetic resonance images of the mid-thigh were acquired using a stimulated echo acquisition mode-echoplanar imaging (STEAM-EPI) imaging sequence, to assess diffusion, and 2-point Dixon imaging, to assess FF. Imaging was repeated in 19 participants after a 30 min interval in order to assess test–retest variability of the measurements. RESULTS: Intraclass correlation coefficients (ICCs) for test–retest variability were 0.99 [95% confidence interval, (CI): 0.98, 1] for FF, 0.94 (95% CI: 0.84, 0.97) for mean diffusivity and 0.89 (95% CI: 0.74, 0.96) for fractional anisotropy (FA). FF was higher in the hamstrings than the quadriceps by a mean difference of 1.81% (95% CI:1.63, 2.00)%, p < 0.001. Mean diffusivity was significantly lower in the hamstrings than the quadriceps (0.26 (0.13, 0.39) x10- 3 mm2s−1, p < 0.001) whereas fractional anisotropy was significantly higher in the hamstrings relative to the quadriceps with a mean difference of 0.063 (0.05, 0.07), p < 0.001. CONCLUSIONS: This study has shown excellent test-retest, variability in MR-based FF and diffusion measurements and demonstrated significant differences in these measures between hamstrings and quadriceps in the healthy thigh. ADVANCES IN KNOWLEDGE: Test–retest variability is excellent for STEAM-EPI diffusion and 2-point Dixon-based FF measurements in the healthy muscle. Inter- and intraobserver variability were excellent for region of interest placement for STEAM-EPI diffusion and 2-point Dixon-based FF measurements in the healthy muscle. There are significant differences in FF and diffusion measurements between the hamstrings and quadriceps in the normal muscle

Extended T2-IVIM model for correction of TE dependence of pseudo-diffusion volume fraction in clinical diffusion-weighted magnetic resonance imaging.

The bi-exponential intravoxel-incoherent-motion (IVIM) model for diffusion-weighted MRI (DWI) fails to account for differential T 2 s in the model compartments, resulting in overestimation of pseudodiffusion fraction f. An extended model, T2-IVIM, allows removal of the confounding echo-time (TE) dependence of f, and provides direct compartment T 2 estimates. Two consented healthy volunteer cohorts (n  =  5, 6) underwent DWI comprising multiple TE/b-value combinations (Protocol 1: TE  =  62-102 ms, b  =  0-250 mm-2s, 30 combinations. Protocol 2: 8 b-values 0-800 mm-2s at TE  =  62 ms, with 3 additional b-values 0-50 mm-2s at TE  =  80, 100 ms; scanned twice). Data from liver ROIs were fitted with IVIM at individual TEs, and with the T2-IVIM model using all data. Repeat-measures coefficients of variation were assessed for Protocol 2. Conventional IVIM modelling at individual TEs (Protocol 1) demonstrated apparent f increasing with longer TE: 22.4  ±  7% (TE  =  62 ms) to 30.7  ±  11% (TE  =  102 ms); T2-IVIM model fitting accounted for all data variation. Fitting of Protocol 2 data using T2-IVIM yielded reduced f estimates (IVIM: 27.9  ±  6%, T2-IVIM: 18.3  ±  7%), as well as T 2  =  42.1  ±  7 ms, 77.6  ±  30 ms for true and pseudodiffusion compartments, respectively. A reduced Protocol 2 dataset yielded comparable results in a clinical time frame (11 min). The confounding dependence of IVIM f on TE can be accounted for using additional b/TE images and the extended T2-IVIM model

MRI in acute muscle tears in athletes: can quantitative T2 and DTI predict return to play better than visual assessment?

Objectives To assess the ability of quantitative T2, diffusion tensor imaging (DTI) and radiologist’s scores to detect muscle changes following acute muscle tear in soccer and rugby players. To assess the ability of these parameters to predict return to play times. Methods In this prospective, longitudinal study, 13 male athletes (age 19 to 34 years; mean 25 years) underwent MRI within 1 week of suffering acute muscle tear. Imaging included measurements of T2 and DTI parameters. Images were also assessed using modified Peetrons and British athletics muscle injury classification (BAMIC) scores. Participants returned for a second scan within 1 week of being determined fit to return to play. MRI measurements were compared between visits. Pearson’s correlation between visit 1 measurements and return to play times was assessed. Results There were significant differences between visits in BAMIC scores (Z = − 2.088; p = 0.037), modified Peetrons (Z = − 2.530; p = 0.011) and quantitative MRI measurements; T2, 13.12 ms (95% CI, 4.82 ms, 21.42 ms; p = 0.01); mean diffusivity (0.22 (0.04, 0.39); p = 0.02) and fractional anisotropy (0.07 (0.01, 0.14); p = 0.03). BAMIC scores showed a significant correlation with return to play time (Rs = 0.64; p = 0.02), but modified Peetrons scores and quantitative parameters did not. Conclusions T2 and DTI measurements in muscle can detect changes due to healing following muscle tear. Although BAMIC scores correlated well with return to play times, in this small study, quantitative MRI values did not, suggesting that T2 and DTI measurements are inferior predictors of return to play time compared with visual scoring. Key Points • Muscle changes following acute muscle tear can be measured using T2 and diffusion measurements on MRI. • Measurements of T2 and diffusion using MRI are not as good as a radiologist’s visual report at predicting return to play time after acute muscle tear

T₂-adjusted computed diffusion-weighted imaging: A novel method to enhance tumour visualisation.

PurposeTo introduce T2-adjusted computed DWI (T2-cDWI), a method that provides synthetic images at arbitrary b-values and echo times (TEs) that improve tissue contrast by removing or increasing T2 contrast in diffusion-weighted images.Materials and methodsIn addition to the standard DWI acquisition protocol T2-weighted echo-planar images at multiple (≥2) echo times were acquired. This allows voxelwise estimation of apparent diffusion coefficient (ADC) and T2 values, permitting synthetic images to be generated at any chosen b-value and echo time. An analytical model is derived for the noise properties in T2-cDWI, and validated using a diffusion test-object. Furthermore, we present T2-cDWI in two example clinical case studies: (i) a patient with mesothelioma demonstrating multiple disease tissue compartments and (ii) a patient with primary ovarian cancer demonstrating solid and cystic disease compartments.ResultsMeasured image noise in T2-cDWI from phantom experiments conformed to the analytical model and demonstrated that T2-cDWI at high computed b-value/TE combinations achieves lower noise compared with conventional DWI. In patients, T2-cDWI with low b-value and long TE enhanced fluid signal while suppressing solid tumour components. Conversely, large b-values and short TEs overcome T2 shine-through effects and increase the contrast between tumour and fluid compared with conventional high-b-value DW images.ConclusionT2-cDWI is a promising clinical tool for improving image signal-to-noise, image contrast, and tumour detection through suppression of T2 shine-through effects