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Pompe disease is a rare genetic metabolic disorder caused by mutations in acid-alpha glucoside (GAA) leading to pathological lysosomal glycogen accumulation associated with skeletal muscle weakness, respiratory difficulties and cardiomyopathy, dependent from the GAA residual enzyme activity. This study aimed to investigate early proteomic changes in a mouse model of Pompe disease and identify potential therapeutic pathways using proteomic analysis of skeletal muscles from pre-symptomatic Pompe mice. For this purpose, quadriceps samples of Gaa6neo/6neo mutant (Pompe) and wildtype mice, at the age of six weeks, were studied with three biological replicates for each group. The data were validated with skeletal muscle morphology, immunofluorescence studies and western blot analysis. Proteomic profiling identified 538 significantly upregulated and 16 significantly downregulated proteins in quadriceps muscles derived from Pompe animals compared to wildtype mice. The majority of significantly upregulated proteins were involved in metabolism, translation, folding, degrading and vesicular transport, with some having crucial roles in the etiopathology of other neurological or neuromuscular diseases. This study highlights the importance of the early diagnosis and treatment of Pompe disease and suggests potential add-on therapeutic strategies targeting protein dysregulations.

MRI is a helpful tool for monitoring disease progression in late-onset Pompe disease (LOPD). Our study aimed to evaluate if muscle diffusion tensor imaging (mDTI) shows alterations in muscles of LOPD patients with

Background: Muscle diffusion tensor imaging (mDTI) is a promising surrogate biomarker in the evaluation of muscular injuries and neuromuscular diseases. Since mDTI metrics are known to vary between different muscles, separation of different muscles is essential to achieve muscle-specific diffusion parameters. The commonly used technique to assess DTI metrics is parameter maps based on manual segmentation (MSB). Other techniques comprise tract-based approaches, which can be performed in a previously defined volume. This so-called volume-based tractography (VBT) may offer a more robust assessment of diffusion metrics and additional information about muscle architecture through tract properties. The purpose of this study was to assess DTI metrics of human calf muscles calculated with two segmentation techniques-MSB and VBT-regarding their inter-rater reliability in healthy and dystrophic calf muscles. Methods: 20 healthy controls and 18 individuals with different neuromuscular diseases underwent an MRI examination in a 3T scanner using a 16-channel Torso XL coil. DTI metrics were assessed in seven calf muscles using MSB and VBT. Coefficients of variation (CV) were calculated for both techniques. MSB and VBT were performed by two independent raters to assess inter-rater reliability by ICC analysis and Bland-Altman plots. Next to analysis of DTI metrics, the same assessments were also performed for tract properties extracted with VBT. Results: For both techniques, low CV were found for healthy controls (\(\leq\)13%) and neuromuscular diseases (\(\leq\)17%). Significant differences between methods were found for all diffusion metrics except for \(\lambda\)1. High inter-rater reliability was found for both MSB and VBT (ICC \(\geq\) 0.972). Assessment of tract properties revealed high inter-rater reliability (ICC \(\geq\) 0.974). Conclusions: Both segmentation techniques can be used in the evaluation of DTI metrics in healthy controls and different NMD with low rater dependency and high precision but differ significantly from each other. Our findings underline that the same segmentation protocol must be used to ensure comparability of mDTI data.

Background: Myotonic Dystrophies type 1 and type 2 are hereditary myopathies with dystrophic muscle degeneration in varying degrees. Differences in muscle diffusion between both diseases have not been evaluated yet. Objective: To evaluate the ability of muscle diffusion tensor imaging (mDTI) and Dixon fat-quantification to distinguish between Myotonic Dystrophy (DM) type 1 and type 2 and if both diseases show distinct muscle involvement patterns. Methods: We evaluated 6 thigh and 7 calf muscles (both legs) of 10 DM 1, 13 DM 2 and 28 healthy controls (HC) with diffusion tensor imaging, T1w and mDixonquant sequences in a 3T MRI scanner. The quantitative mDTI-values axial diffusivity (λ1), mean diffusivity (MD), radial diffusivity (RD) and fractional anisotropy (FA) as well as fat-fraction were analysed. CTG-triplet repeat-length of DM 1 patients was correlated with diffusion metrics and fat-fraction. Results: mDTI showed significant differences between DM 1 and DM 2 vs. healthy controls in diffusion parameters of the thigh (all p

Introduction Muscle diffusion tensor imaging (mDTI) is a quantitative MRI technique that can provide information about muscular microstructure and integrity. Ultrasound and DTI studies have shown intramuscular differences, and therefore separation of different muscles for analysis is essential. The commonly used methods to assess DTI metrics in muscles are manual segmentation and tract-based analysis. Recently methods such as volume-based tractography have been applied to optimize muscle architecture estimation, but can also be used to assess DTI metrics. Purpose To evaluate diffusion metrics obtained using three different methods-volume-based tractography, manual segmentation-based analysis and tract-based analysis-with respect to their interrater reliability and their ability to detect intramuscular variance. Materials and methods 30 volunteers underwent an MRI examination in a 3 T scanner using a 16-channel Torso XL coil. Diffusion-weighted images were acquired to obtain DTI metrics. These metrics were evaluated in six thigh muscles using volume-based tractography, manual segmentation and standard tractography. All three methods were performed by two independent raters to assess interrater reliability by ICC analysis and Bland-Altman plots. Ability to assess intramuscular variance was compared using an ANOVA with muscle as a between-subjects factor. Results Interrater reliability for all methods was found to be excellent. The highest interrater reliability was found for volume-based tractography (ICC ≥ 0.967). Significant differences for the factor muscle in all examined diffusion parameters were shown in muscles using all methods (main effect p Conclusions Diffusion data can be assessed by volume tractography, standard tractography and manual segmentation with high interrater reliability. Each method produces different results for the investigated DTI parameters. Volume-based tractography was superior to conventional manual segmentation and tractography regarding interrater reliability and detection of intramuscular variance, while tract-based analysis showed the lowest coefficients of variation.

Quantitative MRI combines non-invasive imaging techniques to reveal alterations in muscle pathophysiology. Creating muscle-specific labels manually is time consuming and requires an experienced examiner. Semi-automatic and fully automatic methods reduce segmentation time significantly. Current machine learning solutions are commonly trained on data from healthy subjects using homogeneous databases with the same image contrast. While yielding high Dice scores (DS), those solutions are not applicable to different image contrasts and acquisitions. Therefore, the aim of our study was to evaluate the feasibility of automatic segmentation of a heterogeneous database. To create a heterogeneous dataset, we pooled lower leg muscle images from different studies with different contrasts and fields-of-view, containing healthy controls and diagnosed patients with various neuromuscular diseases. A second homogenous database with uniform contrasts was created as a subset of the first database. We trained three 3D-convolutional neuronal networks (CNN) on those databases to test performance as compared to manual segmentation. All networks, training on heterogeneous data, were able to predict seven muscles with a minimum average DS of 0.75. U-Net performed best when trained on the heterogeneous dataset (DS: 0.80 ± 0.10, AHD: 0.39 ± 0.35). ResNet and DenseNet yielded higher DS, when trained on a heterogeneous dataset (both DS: 0.86), as compared to a homogeneous dataset (ResNet DS: 0.83, DenseNet DS: 0.76). In conclusion, a CNN trained on a heterogeneous dataset achieves more accurate labels for predicting a heterogeneous database of lower leg muscles than a CNN trained on a homogenous dataset. We propose that a large heterogeneous database is needed, to make automated segmentation feasible for different kinds of image acquisitions.

The purpose of this study was to evaluate temporal stability, multi-center reproducibility and the influence of covariates on a multimodal MR protocol for quantitative muscle imaging and to facilitate its use as a standardized protocol for evaluation of pathology in skeletal muscle. Quantitative T2, quantitative diffusion and four-point Dixon acquisitions of the calf muscles of both legs were repeated within one hour. Sixty-five healthy volunteers (31 females) were included in one of eight 3-T MR systems. Five traveling subjects were examined in six MR scanners. Average values over all slices of water-T2 relaxation time, proton density fat fraction (PDFF) and diffusion metrics were determined for seven muscles. Temporal stability was tested with repeated measured ANOVA and two-way random intraclass correlation coefficient (ICC). Multi-center reproducibility of traveling volunteers was assessed by a two-way mixed ICC. The factors age, body mass index, gender and muscle were tested for covariance. ICCs of temporal stability were between 0.963 and 0.999 for all parameters. Water-T2 relaxation decreased significantly (P −3) within one hour by ~ 1 ms. Multi-center reproducibility showed ICCs within 0.879–0.917 with the lowest ICC for mean diffusivity. Different muscles showed the highest covariance, explaining 20–40% of variance for observed parameters. Standardized acquisition and processing of quantitative muscle MRI data resulted in high comparability among centers. The imaging protocol exhibited high temporal stability over one hour except for water T2 relaxation times. These results show that data pooling is feasible and enables assembling data from patients with neuromuscular diseases, paving the way towards larger studies of rare muscle disorders.

PURPOSE: To evaluate differences in diffusion parameters in thigh muscles in patients with glycogen storage disease type V (McArdle disease) using muscle diffusion tensor imaging (mDTI) compared to healthy controls METHODS: In this prospective study, we evaluated thigh muscles from hip to knee of 10 McArdle patients (5 female, mean age 33.7 ± 14.4 years) and 10 healthy age- and gender-matched volunteers. MRI scans were performed at 3 T and comprised mDTI, T1-weighted and T2-weighted imaging between May 2015 and May 2017. Needle biopsy of the vastus lateralis muscle was performed in three McArdle patients. The muscle tissue was analyzed by using histochemical and enzyme-histochemical techniques for glycogen content and histopathological changes. Mean values of the eigenvalues (λ1-λ3), fractional anisotropy (FA), and mean diffusivity (MD) were obtained for the vastus lateralis, vastus medialis, rectus femoris, biceps femoris, semitendinosus, and semimembranosus and compared between groups using Student's t tests, as well as ANCOVA; significance level was set at p

Expansion of CAG repeats, which code for the disease-causing polyglutamine protein, is a common feature in polyglutamine diseases. RNA-mediated mechanisms that contribute to neuropathology in polyglutamine diseases are important. RNA-toxicity describes a phenomenon by which the mutant CAG repeat RNA recruits RNA-binding proteins, thereby leading to aberrant function. For example the MID1 protein binds to mutant huntingtin (HTT) RNA, which is linked to Huntington's disease (HD), at its CAG repeat region and induces protein synthesis of mutant protein. But is this mechanism specific to HD or is it a common mechanism in CAG repeat expansion disorders? To answer this question, we have analyzed the interaction between MID1 and three other CAG repeat mRNAs, Ataxin2 (ATXN2), Ataxin3 (ATXN3), and Ataxin7 (ATXN7), that all differ in the sequence flanking the CAG repeat. We show that ATXN2, ATXN3, and ATXN7 bind to MID1 in a CAG repeat length-dependent manner. Furthermore, we show that functionally, in line with what we have previously observed for HTT, the binding of MID1 to ATXN2, ATXN3, and ATXN7 mRNA induces protein synthesis in a repeat length-dependent manner. Our data suggest that regulation of protein translation by the MID1 complex is a common mechanism for CAG repeat containing mRNAs.