Effect of knee joint angle on vastus medialis and vastus lateralis rigidity during isometric submaximal voluntary knee extensions.

The use of shear wave elastography during voluntary contraction has enabled the non-invasive assessment of load sharing strategies between agonist muscles. However, the change in joint angle and voluntary contraction intensity can modify contribution between muscles. The aim of this study was to investigate the effect of knee joint angle on the local mechanical properties of the vastus medialis (VM) and the vastus lateralis (VL) during isometric submaximal voluntary contractions from shear wave elastography mapping. The VM and VL Young's modulus at rest and during constant isometric submaximal voluntary contractions (i.e., 25%, 50% and 75% of maximal voluntary contraction [MVC]) were assessed for two knee angles (50° and 100° | knee fully extended = 0°) in twelve participants. No significant difference was found in the VM Young's modulus among all torque levels and knee angles (p > 0.05). VL Young's modulus was significantly higher at 25% MVC for a knee angle of 100° than at 75% MVC for the same knee angle and was greater at 25% MVC for a knee angle of 100° than for 50° (p < 0.05). In contrast to the VM, the contribution of the VL to the knee joint torque production during isometric voluntary contraction appears to depend on the muscle length and the relative knee extension torque level.

Ultra-high field magnetic resonance imaging of the quadriceps tendon enthesis in healthy subjects.

PURPOSE: Although enthesitis is a hallmark of several rheumatologic conditions, current imaging methods are still unable to characterize entheses changes because of the corresponding short transverse relaxation times (T2). A growing number of MR studies have used Ultra-High Field (UHF) MRI in order to assess low-T2 tissues e.g., tendon but never in humans. The purpose of the present study was to assess in vivo the enthesis of the quadriceps tendon in healthy subjects using UHF MRI. METHODS: Eleven healthy subjects volunteered in an osteoarthritis imaging study. The inclusion criteria were: no knee trauma, Lequesne index = 0, less than 3 h of sport activities per week, and Kellgren and Lawrence grade = 0. 3D MR images were acquired at 7 T using GRE sequences and a T2* mapping. Regions of interest i.e., trabecular bone, subchondral bone, enthesis, and tendon body were identified, and T2* values were quantified and compared. RESULTS: Quadriceps tendon enthesis was visible as a hyper-intense signal. The largest and the lowest T2* values were quantified in the subchondral bone region and the tendon body respectively. T2* value within subchondral bone was significantly higher than T2* value within the enthesis. T2* in subchondral bone region was significantly higher than the whole tendon body T2*. CONCLUSION: A T2* gradient was observed along the axis from the enthesis toward the tendon body. It illustrates different water biophysical properties. These results provide normative values which could be used in the field of inflammatory rheumatologic diseases and mechanical disorders affecting the tendon.

Four-dimensional reconstruction and characterization of bladder deformations.

BACKGROUND AND OBJECTIVE: Pelvic floor disorders are prevalent diseases and patient care remains difficult as the dynamics of the pelvic floor remains poorly understood. So far, only 2D dynamic observations of straining exercises at excretion are available in the clinics and 3D mechanical defects of pelvic organs are not well studied. In this context, we propose a complete methodology for the 3D representation of non-reversible bladder deformations during exercises, combined with a 3D representation of the location of the highest strain areas on the organ surface. METHODS: Novel image segmentation and registration approaches have been combined with three geometrical configurations of up-to-date rapid dynamic multi-slice MRI acquisitions for the reconstruction of real-time dynamic bladder volumes. RESULTS: For the first time, we proposed real-time 3D deformation fields of the bladder under strain from in-bore forced breathing exercises. The potential of our method was assessed on eight control subjects undergoing forced breathing exercises. We obtained average volume deviations of the reconstructed dynamic volume of bladders around 2.5% and high registration accuracy with mean distance values of 0.4 ± 0.3 mm and Hausdorff distance values of 2.2 ± 1.1 mm. CONCLUSIONS: The proposed framework provides proper 3D+t spatial tracking of non-reversible bladder deformations. This has immediate applicability in clinical settings for a better understanding of pelvic organ prolapse pathophysiology. This work can be extended to patients with cavity filling or excretion problems to better characterize the severity of pelvic floor pathologies or to be used for preoperative surgical planning.

The Impact of Fatty Infiltration on MRI Segmentation of Lower Limb Muscles in Neuromuscular Diseases: A Comparative Study of Deep Learning Approaches.

BACKGROUND: Deep learning methods have been shown to be useful for segmentation of lower limb muscle MRIs of healthy subjects but, have not been sufficiently evaluated on neuromuscular disease (NDM) patients. PURPOSE: Evaluate the influence of fat infiltration on convolutional neural network (CNN) segmentation of MRIs from NMD patients. STUDY TYPE: Retrospective study. SUBJECTS: Data were collected from a hospital database of 67 patients with NMDs and 14 controls (age: 53 ± 17 years, sex: 48 M, 33 F). Ten individual muscles were segmented from the thigh and six from the calf (20 slices, 200 cm section). FIELD STRENGTH/SEQUENCE: A 1.5 T. Sequences: 2D T1 -weighted fast spin echo. Fat fraction (FF): three-point Dixon 3D GRE, magnetization transfer ratio (MTR): 3D MT-prepared GRE, T2: 2D multispin-echo sequence. ASSESSMENT: U-Net 2D, U-Net 3D, TransUNet, and HRNet were trained to segment thigh and leg muscles (101/11 and 95/11 training/validation images, 10-fold cross-validation). Automatic and manual segmentations were compared based on geometric criteria (Dice coefficient [DSC], outlier rate, absence rate) and reliability of measured MRI quantities (FF, MTR, T2, volume). STATISTICAL TESTS: Bland-Altman plots were chosen to describe agreement between manual vs. automatic estimated FF, MTR, T2 and volume. Comparisons were made between muscle populations with an FF greater than 20% (G20+) and lower than 20% (G20-). RESULTS: The CNNs achieved equivalent results, yet only HRNet recognized every muscle in the database, with a DSC of 0.91 ± 0.08, and measurement biases reaching -0.32% ± 0.92% for FF, 0.19 ± 0.77 for MTR, -0.55 ± 1.95 msec for T2, and - 0.38 ± 3.67 cm3 for volume. The performances of HRNet, between G20- and G20+ decreased significantly. DATA CONCLUSION: HRNet was the most appropriate network, as it did not omit any muscle. The accuracy obtained shows that CNNs could provide fully automated methods for studying NMDs. However, the accuracy of the methods may be degraded on the most infiltrated muscles (>20%). EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 1.

The Road Toward Reproducibility of Parametric Mapping of the Heart: A Technical Review.

Parametric mapping of the heart has become an essential part of many cardiovascular magnetic resonance imaging exams, and is used for tissue characterization and diagnosis in a broad range of cardiovascular diseases. These pulse sequences are used to quantify the myocardial T1, T2, T 2 * , and T1ρ relaxation times, which are unique surrogate indices of fibrosis, edema and iron deposition that can be used to monitor a disease over time or to compare patients to one another. Parametric mapping is now well-accepted in the clinical setting, but its wider dissemination is hindered by limited inter-center reproducibility and relatively long acquisition times. Recently, several new parametric mapping techniques have appeared that address both of these problems, but substantial hurdles remain for widespread clinical adoption. This review serves both as a primer for newcomers to the field of parametric mapping and as a technical update for those already well at home in it. It aims to establish what is currently needed to improve the reproducibility of parametric mapping of the heart. To this end, we first give an overview of the metrics by which a mapping technique can be assessed, such as bias and variability, as well as the basic physics behind the relaxation times themselves and what their relevance is in the prospect of myocardial tissue characterization. This is followed by a summary of routine mapping techniques and their variations. The problems in reproducibility and the sources of bias and variability of these techniques are reviewed. Subsequently, novel fast, whole-heart, and multi-parametric techniques and their merits are treated in the light of their reproducibility. This includes state of the art segmentation techniques applied to parametric maps, and how artificial intelligence is being harnessed to solve this long-standing conundrum. We finish up by sketching an outlook on the road toward inter-center reproducibility, and what to expect in the future.

Characterization of surface motion patterns in highly deformable soft tissue organs from dynamic MRI: An application to assess 4D bladder motion.

BACKGROUND AND OBJECTIVES: Dynamic Magnetic Resonance Imaging (MRI) may capture temporal anatomical changes in soft tissue organs with high-contrast but the obtained sequences usually suffer from limited volume coverage which makes the high-resolution reconstruction of organ shape trajectories a major challenge in temporal studies. Because of the variability of abdominal organ shapes across time and subjects, the objective of the present study is to go towards 3D dense velocity measurements to fully cover the entire surface and to extract meaningful features characterizing the observed organ deformations and enabling clinical action or decision. METHODS: We present a pipeline for characterization of bladder surface dynamics during deep respiratory movements. For a compact shape representation, the reconstructed temporal volumes were first used to establish subject-specific dynamical 4D mesh sequences using the large deformation diffeomorphic metric mapping (LDDMM) framework. Then, we performed a statistical characterization of organ dynamics from mechanical parameters such as mesh elongations and distortions. Since we refer to organs as non-flat surfaces, we have also used the mean curvature change as metric to quantify surface evolution. However, the numerical computation of curvature is strongly dependant on the surface parameterization (i.e. the mesh resolution). To cope with this dependency, we employed a non-parametric method for surface deformation analysis. Independent of parameterization and minimizing the length of the geodesic curves, it stretches smoothly the surface curves towards a sphere by minimizing a Dirichlet energy. An Eulerian PDE approach is used to derive a shape descriptor from the curve-shortening flow. Intercorrelations between individuals' motion patterns are computed using the Laplace-Beltrami Operator (LBO) eigenfunctions for spherical mapping. RESULTS: Application to extracting characterization correlation curves for locally-controlled simulated shape trajectories demonstrates the stability of the proposed shape descriptor. Its usability was shown on MRI acquired for seven healthy participants for which the bladder was highly deformed by maximum of inspiration. As expected, the study showed that deformations occured essentially on the top lateral regions. CONCLUSION: Promising results were obtained, showing the organ in its 3D complexity during deformation due to strain conditions. Smooth genus-0 manifold reconstruction from sparse dynamic MRI data is employed to perform a statistical shape analysis for the determination of bladder deformation.

Impaired aerobic capacity and premature fatigue preceding muscle weakness in the skeletal muscle Tfam-knockout mouse model.

Mitochondrial diseases are genetic disorders that lead to impaired mitochondrial function, resulting in exercise intolerance and muscle weakness. In patients, muscle fatigue due to defects in mitochondrial oxidative capacities commonly precedes muscle weakness. In mice, deletion of the fast-twitch skeletal muscle-specific Tfam gene (Tfam KO) leads to a deficit in respiratory chain activity, severe muscle weakness and early death. Here, we performed a time-course study of mitochondrial and muscular dysfunctions in 11- and 14-week-old Tfam KO mice, i.e. before and when mice are about to enter the terminal stage, respectively. Although force in the unfatigued state was reduced in Tfam KO mice compared to control littermates (wild type) only at 14 weeks, during repeated submaximal contractions fatigue was faster at both ages. During fatiguing stimulation, total phosphocreatine breakdown was larger in Tfam KO muscle than in wild-type muscle at both ages, whereas phosphocreatine consumption was faster only at 14 weeks. In conclusion, the Tfam KO mouse model represents a reliable model of lethal mitochondrial myopathy in which impaired mitochondrial energy production and premature fatigue occur before muscle weakness and early death.

Assessment of in vivo bone microarchitecture changes in an anti-TNFα treated psoriatic arthritic patient.

OBJECTIVE: Psoriatic arthritis (PsA) is an inflammatory rheumatic disease, mediated in part by TNFα and associated with bone loss. Anti-TNFα treatment should inhibit this phenomenon and reduce the systemic bone loss. Ultra-high field MRI (UHF MRI) may be used to quantify bone microarchitecture (BM) in-vivo. In this study, we quantified BM using UHF MRI in a PsA patient and followed up the changes related to anti-TNFα treatment. SUBJECTS AND METHODS: A non-treated PsA patient with knee arthritis and 7 gender-matched controls were scanned using a gradient re-echo sequence at UHF MRI. After a year of Adalimumab treatment, the patient underwent a second UHF MRI. A PET-FNa imaging was performed before and after treatment to identify and localize the abnormal metabolic areas. BM was characterized using typical morphological parameters quantified in 32 regions of interest (ROIs) located in the patella, proximal tibia, and distal femur. RESULTS: Before treatment, the BM parameters were statistically different from controls in 24/32 ROIs with differences reaching up to 38%. After treatment, BM parameters were normalized for 15 out of 24 ROIs. The hypermetabolic areas disclosed by PET-FNa before the treatment partly resumed after the treatment. CONCLUSION: Thanks to UHF MRI, we quantified in vivo BM anomalies in a PsA patient and we illustrated a major reversion after one year of treatment. Moreover, BM results highlighted that the abnormalities were not only localized in hypermetabolic regions identified by PET-FNa, suggesting that the bone loss was global and not related to inflammation.

Overview of MR Image Segmentation Strategies in Neuromuscular Disorders.

Neuromuscular disorders are rare diseases for which few therapeutic strategies currently exist. Assessment of therapeutic strategies efficiency is limited by the lack of biomarkers sensitive to the slow progression of neuromuscular diseases (NMD). Magnetic resonance imaging (MRI) has emerged as a tool of choice for the development of qualitative scores for the study of NMD. The recent emergence of quantitative MRI has enabled to provide quantitative biomarkers more sensitive to the evaluation of pathological changes in muscle tissue. However, in order to extract these biomarkers from specific regions of interest, muscle segmentation is mandatory. The time-consuming aspect of manual segmentation has limited the evaluation of these biomarkers on large cohorts. In recent years, several methods have been proposed to make the segmentation step automatic or semi-automatic. The purpose of this study was to review these methods and discuss their reliability, reproducibility, and limitations in the context of NMD. A particular attention has been paid to recent deep learning methods, as they have emerged as an effective method of image segmentation in many other clinical contexts.

Supervised segmentation framework for evaluation of diffusion tensor imaging indices in skeletal muscle.

Diffusion tensor imaging (DTI) is becoming a relevant diagnostic tool to understand muscle disease and map muscle recovery processes following physical activity or after injury. Segmenting all the individual leg muscles, necessary for quantification, is still a time-consuming manual process. The purpose of this study was to evaluate the impact of a supervised semi-automatic segmentation pipeline on the quantification of DTI indices in individual upper leg muscles. Longitudinally acquired MRI datasets (baseline, post-marathon and follow-up) of the upper legs of 11 subjects were used in this study. MR datasets consisted of a DTI and Dixon acquisition. Semi-automatic segmentations for the upper leg muscles were performed using a transversal propagation approach developed by Ogier et al on the out-of-phase Dixon images at baseline. These segmentations were longitudinally propagated for the post-marathon and follow-up time points. Manual segmentations were performed on the water image of the Dixon for each of the time points. Dice similarity coefficients (DSCs) were calculated to compare the manual and semi-automatic segmentations. Bland-Altman and regression analyses were performed, to evaluate the impact of the two segmentation methods on mean diffusivity (MD), fractional anisotropy (FA) and the third eigenvalue (λ3 ). The average DSC for all analyzed muscles over all time points was 0.92 ± 0.01, ranging between 0.48 and 0.99. Bland-Altman analysis showed that the 95% limits of agreement for MD, FA and λ3 ranged between 0.5% and 3.0% for the transversal propagation and between 0.7% and 3.0% for the longitudinal propagations. Similarly, regression analysis showed good correlation for MD, FA and λ3 (r = 0.99, p < 60; 0.0001). In conclusion, the supervised semi-automatic segmentation framework successfully quantified DTI indices in the upper-leg muscles compared with manual segmentation while only requiring manual input of 30% of the slices, resulting in a threefold reduction in segmentation time.

Deep learning-based fully automatic segmentation of wrist cartilage in MR images.

The study objective was to investigate the performance of a dedicated convolutional neural network (CNN) optimized for wrist cartilage segmentation from 2D MR images. CNN utilized a planar architecture and patch-based (PB) training approach that ensured optimal performance in the presence of a limited amount of training data. The CNN was trained and validated in 20 multi-slice MRI datasets acquired with two different coils in 11 subjects (healthy volunteers and patients). The validation included a comparison with the alternative state-of-the-art CNN methods for the segmentation of joints from MR images and the ground-truth manual segmentation. When trained on the limited training data, the CNN outperformed significantly image-based and PB-U-Net networks. Our PB-CNN also demonstrated a good agreement with manual segmentation (Sørensen-Dice similarity coefficient [DSC] = 0.81) in the representative (central coronal) slices with a large amount of cartilage tissue. Reduced performance of the network for slices with a very limited amount of cartilage tissue suggests the need for fully 3D convolutional networks to provide uniform performance across the joint. The study also assessed inter- and intra-observer variability of the manual wrist cartilage segmentation (DSC = 0.78-0.88 and 0.9, respectively). The proposed deep learning-based segmentation of the wrist cartilage from MRI could facilitate research of novel imaging markers of wrist osteoarthritis to characterize its progression and response to therapy.

Fat fraction distribution in lower limb muscles of patients with CMT1A: A quantitative MRI study.

OBJECTIVE: To quantitatively describe the MRI fat infiltration pattern of muscle degeneration in Charcot-Marie-Tooth (CMT) type 1A (CMT1A) disease and to look for correlations with clinical variables. METHODS: MRI fat fraction was assessed in lower-limb musculature of patients with CMT1A and healthy controls. More particularly, 14 muscle compartments were selected at leg and thigh levels and for proximal, distal, and medial slices. Muscle fat infiltration profile was determined quantitatively in each muscle compartment and along the entire volume of acquisition to determine a length-dependent gradient of fat infiltration. Clinical impairment was evaluated with muscle strength measurements and CMT Examination Scores (CMTESs). RESULTS: A total of 16 patients with CMT1A were enrolled and compared to 11 healthy controls. Patients with CMT1A showed a larger muscle fat fraction at leg and thigh levels with a proximal-to-distal gradient. At the leg level, the largest fat infiltration was quantified in the anterior and lateral compartments. CMTES was correlated with fat fraction, especially in the anterior compartment of leg muscles. Strength of plantar flexion was also correlated with fat fraction of the posterior compartments of leg muscles. CONCLUSION: On the basis of quantitative MRI measurements combined with a dedicated segmentation method, muscle fat infiltration quantified in patients with CMT1A disclosed a length-dependent peroneal-type pattern of fat infiltration and was correlated to main clinical variables. Quantification of fat fraction at different levels of the leg anterior compartment might be of interest in future clinical trials.

In vivo characterization of skeletal muscle function in nebulin-deficient mice.

INTRODUCTION: The conditional nebulin knockout mouse is a new model mimicking nemaline myopathy, a rare disease characterized by muscle weakness and rods within muscle fibers. We investigated the impact of nebulin (NEB) deficiency on muscle function in vivo. METHODS: Conditional nebulin knockout mice and control littermates were studied at 10 to 12 months. Muscle function (force and fatigue) and anatomy (muscles volume and fat content) were measured in vivo. Myosin heavy chain (MHC) composition and nebulin (NEB) protein expression were assessed by protein electrophoresis. RESULTS: Conditional nebulin knockout mice displayed a lower NEB level (-90%) leading to a 40% and 45% reduction in specific maximal force production and muscles volume, respectively. Nebulin deficiency was also associated with higher resistance to fatigue and increased MHC I content. DISCUSSION: Adult nebulin-deficient mice displayed severe muscle atrophy and weakness in vivo related to a low NEB content but an improved fatigue resistance due to a slower contractile phenotype.

A novel segmentation framework dedicated to the follow-up of fat infiltration in individual muscles of patients with neuromuscular disorders.

PURPOSE: To propose a novel segmentation framework that is dedicated to the follow-up of fat infiltration in individual muscles of patients with neuromuscular disorders. METHODS: We designed a semi-automatic segmentation pipeline of individual leg muscles in MR images based on automatic propagation through nonlinear registrations of initial delineation in a minimal number of MR slices. This approach has been validated for the segmentation of individual muscles from MRI data sets, acquired over a 10-month period, from thighs and legs in 10 patients with muscular dystrophy. The robustness of the framework was evaluated using conventional metrics related to muscle volume and clinical metrics related to fat infiltration. RESULTS: High accuracy of the semi-automatic segmentation (mean Dice similarity coefficient higher than 0.89) was reported. The provided method has excellent reliability regarding the reproducibility of the fat fraction estimation, with an average intraclass correlation coefficient score of 0.99. Furthermore, the present segmentation framework was determined to be more reliable than the intra-expert performance, which had an average intraclass correlation coefficient of 0.93. CONCLUSION: The proposed framework of segmentation can successfully provide an effective and reliable tool for accurate follow-up of any MRI biomarkers in neuromuscular disorders. This method could assist the quantitative assessment of muscular changes occurring in such diseases.

Muscle alterations induced by electrostimulation are lower at short quadriceps femoris length.

PURPOSE: This study aimed at determining through MRI investigations, force and soreness assessments whether the modulation of muscle length is a relevant strategy for minimising neuromuscular electrical stimulation (NMES)-induced muscle damage in young healthy participants. METHODS: Comparison of 2 NMES sessions (40 isometric electrically-evoked contractions of the knee extensors) was randomly performed on 1 knee flexed at 50° (short muscle length) and the contralateral at 100° (long muscle length) in a single group of healthy participants. Indirect markers of muscle damage including changes in maximal voluntary isometric contraction (MVC) force, muscle volume and transverse relaxation time (T2) were measured before, 2 days (D2), 4 days (D4) and 7 days (D7) after the NMES sessions in each limb of the ten participants. RESULTS: Although stimulation intensity was similar during the NMES session on both limbs, significantly lower force production was recorded at long muscle length (peak at 30 ± 5% MVC force) as compared to short muscle length (peak at 61 ± 12% MVC force). In the following days, MVC force at long muscle length was decreased from D2 to D7, whereas no significant change occurred at short muscle length. Increases in muscle volume and T2 were found at each time point in stimulated muscles at long muscle length, whereas no change was found at short muscle length. CONCLUSION: For the same stimulation intensity, NMES-induced isometric contractions generate higher knee extension force output and result in lower muscle tissues alterations that could be related to a lower intramuscular shear strain when exercise is performed at short muscle length.

Spatial difference can occur between activated and damaged muscle areas following electrically-induced isometric contractions.

KEY POINTS: T2 mapping combined to image registration and statistical parametric mapping analysis is a suitable methodology to accurately localize and compare the extent of both activated and damaged muscle areas. Activated muscle areas following electrically-induced isometric contractions are superficial, but damaged regions are muscle specific and can be related to the muscle morphology and/or the relative spatial position within a muscle group leading to potential intramuscular muscle shear strain. Tissues other than active skeletal muscle fibres can be altered during unaccustomed neuromuscular electrical stimulation-induced isometric contractions. ABSTRACT: Skeletal muscle isometric contractions induced by neuromuscular electrical stimulation (NMES) exercise can generate damage within activated muscles. This study aimed at comparing the localization and the extent of NMES-activated muscle areas and induced damage regions using magnetic resonance imaging. Thirteen healthy subjects performed a single bout of NMES-induced isometric contractions known to induce a decrease in maximal voluntary isometric contraction (MVC) and increase in muscle volume and transverse relaxation time (T2 ). All the parameters were measured before, immediately after (POST), 7 days (D7), 14 days (D14) and 21 days (D21) after the NMES session. Spatial normalization of T2 maps were performed to compare the localization of muscle activation areas and damaged muscle regions from statistical mapping analyses. A significant decrease in MVC was found at POST (-26 ± 9%) and in delayed time at D7 (-20 ± 6%) and D14 (-12 ± 5%). Although muscle activation was statistically detected through T2 increase at POST in superficial parts of the two muscles located beneath the stimulation electrodes (i.e. vastus lateralis and vastus medialis), alterations quantified in a delayed time from increased T2 were mainly located in the deep muscle region of the vastus lateralis (+57 ± 24% of mean T2 ) and superficial area of the vastus medialis (+24 ± 16% of mean T2 ) at D7 and were still observed in whole muscle at D21. The discrepancy between activated and damaged areas in the vastus lateralis implies that tissues other than active skeletal muscle fibres were altered during unaccustomed NMES-induced isomeric contractions.

L-tyrosine supplementation does not ameliorate skeletal muscle dysfunction in zebrafish and mouse models of dominant skeletal muscle α-actin nemaline myopathy.

L-tyrosine supplementation may provide benefit to nemaline myopathy (NM) patients, however previous studies are inconclusive, with no elevation of L-tyrosine levels in blood or tissue reported. We evaluated the ability of L-tyrosine treatments to improve skeletal muscle function in all three published animal models of NM caused by dominant skeletal muscle α-actin (ACTA1) mutations. Highest safe L-tyrosine concentrations were determined for dosing water and feed of wildtype zebrafish and mice respectively. NM TgACTA1D286G-eGFP zebrafish treated with 10 µM L-tyrosine from 24 hours to 6 days post fertilization displayed no improvement in swimming distance. NM TgACTA1D286G mice consuming 2% L-tyrosine supplemented feed from preconception had significant elevations in free L-tyrosine levels in sera (57%) and quadriceps muscle (45%) when examined at 6-7 weeks old. However indicators of skeletal muscle integrity (voluntary exercise, bodyweight, rotarod performance) were not improved. Additionally no benefit on the mechanical properties, energy metabolism, or atrophy of skeletal muscles of 6-7 month old TgACTA1D286G and KIActa1H40Y mice eventuated from consuming a 2% L-tyrosine supplemented diet for 4 weeks. Therefore this study yields important information on aspects of the clinical utility of L-tyrosine for ACTA1 NM.

Diffusion Properties and 3D Architecture of Human Lower Leg Muscles Assessed with Ultra-High-Field-Strength Diffusion-Tensor MR Imaging and Tractography: Reproducibility and Sensitivity to Sex Difference and Intramuscular Variability.

Purpose To demonstrate the reproducibility of the diffusion properties and three-dimensional structural organization measurements of the lower leg muscles by using diffusion-tensor imaging (DTI) assessed with ultra-high-field-strength (7.0-T) magnetic resonance (MR) imaging and tractography of skeletal muscle fibers. On the basis of robust statistical mapping analyses, this study also aimed at determining the sensitivity of the measurements to sex difference and intramuscular variability. Materials and Methods All examinations were performed with ethical review board approval; written informed consent was obtained from all volunteers. Reproducibility of diffusion tensor indexes assessment including eigenvalues, mean diffusivity, and fractional anisotropy (FA) as well as muscle volume and architecture (ie, fiber length and pennation angle) were characterized in lower leg muscles (n = 8). Intramuscular variability and sex differences were characterized in young healthy men and women (n = 10 in each group). Student t test, statistical parametric mapping, correlation coefficients (Spearman rho and Pearson product-moment) and coefficient of variation (CV) were used for statistical data analysis. Results High reproducibility of measurements (mean CV ± standard deviation, 4.6% ± 3.8) was determined in diffusion properties and architectural parameters. Significant sex differences were detected in FA (4.2% in women for the entire lower leg; P = .001) and muscle volume (21.7% in men for the entire lower leg; P = .008), whereas architecture parameters were almost identical across sex. Additional differences were found independently of sex in diffusion properties and architecture along several muscles of the lower leg. Conclusion The high-spatial-resolution DTI assessed with 7.0-T MR imaging allows a reproducible assessment of structural organization of superficial and deep muscles, giving indirect information on muscle function. ©RSNA, 2018 Online supplemental material is available for this article.