Prospective longitudinal cohort study of quantitative muscle magnetic resonance imaging in a healthy control population.

Quantitative muscle magnetic resonance imaging (qMRI) is a valuable methodology for assessing muscular injuries and neuromuscular disorders. Notably, muscle diffusion tensor imaging (DTI) gives insights into muscle microstructural and macrostructural characteristics. However, the long-term reproducibility and robustness of these measurements remain relatively unexplored. The purpose of this prospective longitudinal cohort study was to assess the long-term robustness and range of variation of qMRI parameters, especially DTI metrics, in the lower extremity muscles of healthy controls under real-life conditions. Twelve volunteers (seven females, age 44.1 ± 12.1 years, body mass index 23.3 ± 2.0 kg/m2) underwent five leg muscle MRI sessions every 20 ± 4 weeks over a total period of 1.5 years. A multiecho gradient-echo Dixon-based sequence, a multiecho spin-echo T2-mapping sequence, and a spin-echo echo planar imaging diffusion-weighted sequence were acquired bilaterally with a Philips 3-T Achieva MR System using a 16-channel torso coil. Fifteen leg muscles were segmented in both lower extremities. qMRI parameters, including fat fraction (FF), water T2 relaxation time, and the diffusion metrics fractional anisotropy (FA) and mean diffusivity (MD), were evaluated. Coefficients of variance (wsCV) and intraclass correlation coefficients (ICCs) were calculated to assess the reproducibility of qMRI parameters. The standard error of measurement (SEM) and the minimal detectable change (MDC) were calculated to determine the range of variation. All tests were applied to all muscles and, subsequently, to each muscle separately. wsCV showed good reproducibility (≤ 10%) for all qMRI parameters in all muscles. The ICCs revealed excellent agreement between time points (FF = 0.980, water T2 = 0.941, FA = 0.952, MD = 0.948). Random measurement errors assessed by SEM and the MDC were low (< 12%). In conclusion, in this study, we showed that qMRI parameters in healthy volunteers living normal lives are stable over 18 months, thereby defining a benchmark for the expected range of variation over time.

Quantitative muscle magnetic resonance imaging in limb-girdle muscular dystrophy type R1 (LGMDR1): A prospective longitudinal cohort study.

Limb-girdle muscular dystrophy (LGMD) type R1 (LGMDR1) is the most common subtype of LGMD in Europe. Prospective longitudinal data, including clinical assessments and new biomarkers such as quantitative magnetic resonance imaging (qMRI), are needed to evaluate the natural course of the disease and therapeutic options. We evaluated eight thigh and seven leg muscles of 13 LGMDR1 patients (seven females, mean age 36.7 years, body mass index 23.9 kg/m2) and 13 healthy age- and gender-matched controls in a prospective longitudinal design over 1 year. Clinical assessment included testing for muscle strength with quick motor function measure (QMFM), gait analysis and patient questionnaires (neuromuscular symptom score, activity limitation [ACTIVLIM]). MRI scans were performed on a 3-T MRI scanner, including a Dixon-based sequence, T2 mapping and diffusion tensor imaging. The qMRI values of fat fraction (FF), water T2 relaxation time (T2), fractional anisotropy, mean diffusivity, axial diffusivity and radial diffusivity were analysed. Within the clinical outcome measures, significant deterioration between baseline and follow-up was found for ACTIVLIM (p = 0.029), QMFM (p = 0.012). Analysis of qMRI parameters of the patient group revealed differences between time points for both FF and T2 when analysing all muscles (FF: p < 0.001; T2: p = 0.016). The highest increase of fat replacement was found in muscles with an FF of between 10% and 50% at baseline. T2 in muscles with low-fat replacement increased significantly. No significant differences were found for the diffusion metrics. Significant correlations between qMRI metrics and clinical assessments were found at baseline and follow-up, while only T2 changes in thigh muscles correlated with changes in ACTIVLIM over time (ρ = -0.621, p < 0.05). Clinical assessments can show deterioration of the general condition of LGMDR1 patients. qMRI measures can give additional information about underlying pathophysiology. Further research is needed to establish qMRI outcome measures for clinical trials.

Evaluation of Neuromuscular Diseases and Complaints by Quantitative Muscle MRI.

Background: Quantitative muscle MRI (qMRI) is a promising tool for evaluating and monitoring neuromuscular disorders (NMD). However, the application of different imaging protocols and processing pipelines restricts comparison between patient cohorts and disorders. In this qMRI study, we aim to compare dystrophic (limb-girdle muscular dystrophy), inflammatory (inclusion body myositis), and metabolic myopathy (Pompe disease) as well as patients with post-COVID-19 conditions suffering from myalgia to healthy controls. Methods: Ten subjects of each group underwent a 3T lower extremity muscle MRI, including a multi-echo, gradient-echo, Dixon-based sequence, a multi-echo, spin-echo (MESE) T2 mapping sequence, and a spin-echo EPI diffusion-weighted sequence. Furthermore, the following clinical assessments were performed: Quick Motor Function Measure, patient questionnaires for daily life activities, and 6-min walking distance. Results: Different involvement patterns of conspicuous qMRI parameters for different NMDs were observed. qMRI metrics correlated significantly with clinical assessments. Conclusions: qMRI metrics are suitable for evaluating patients with NMD since they show differences in muscular involvement in different NMDs and correlate with clinical assessments. Still, standardisation of acquisition and processing is needed for broad clinical use.

Muscle diffusion MRI reveals autophagic buildup in a mouse model for Pompe disease.

Quantitative muscle MRI is increasingly important in the non-invasive evaluation of neuromuscular disorders and their progression. Underlying histopathotological alterations, leading to changes in qMRI parameters are incompletely unraveled. Early microstructural differences of unknown origin reflected by Diffusion MRI in non-fat infiltrated muscles were detected in Pompe patients. This study employed a longitudinal approach with a Pompe disease mouse model to investigate the histopathological basis of these changes. Monthly scans of Pompe (Gaa6neo/6neo) and wildtype mice (age 1-8 months) were conducted using diffusion MRI, T2-mapping, and Dixon-based water-fat imaging on a 7 T scanner. Immunofluorescence studies on quadriceps muscles were analyzed for lysosomal accumulations and autophagic buildup and correlated with MRI outcome measures. Fat fraction and water-T2 did not differ between groups and remained stable over time. In Pompe mice, fractional anisotropy increased, while mean diffusivity (MD) and radial diffusivity (RD) decreased in all observed muscles. Autophagic marker and muscle fibre diameter revealed significant negative correlations with reduced RD and MD, while lysosomal marker did not show any change or correlation. Using qMRI, we showed diffusion changes in muscles of presymptomatic Pompe mice without fat-infiltrated muscles and correlated them to autophagic markers and fibre diameter, indicating diffusion MRI reveals autophagic buildup.

Quantitative muscle magnetic resonance imaging depicts microstructural abnormalities but no signs of inflammation or dystrophy in post-COVID-19 condition.

BACKGROUND AND PURPOSE: Post-COVID-19 condition (PCC) has high impact on quality of life, with myalgia and fatigue affecting at least 25% of PCC patients. This case-control study aims to noninvasively assess muscular alterations via quantitative muscle magnetic resonance imaging (MRI) as possible mechanisms for ongoing musculoskeletal complaints and premature exhaustion in PCC. METHODS: Quantitative muscle MRI was performed on a 3 Tesla MRI scanner of the whole legs in PCC patients compared to age- and sex-matched healthy controls, including a Dixon sequence to determine muscle fat fraction (FF), a multi-echo spin-echo sequence for quantitative water mapping reflecting putative edema, and a diffusion-weighted spin-echo echo-planar imaging sequence to assess microstructural alterations. Clinical examination, nerve conduction studies, and serum creatine kinase were performed in all patients. Quantitative muscle MRI results were correlated to the results of the 6-min walk test and standardized questionnaires assessing quality of life, fatigue, and depression. RESULTS: Twenty PCC patients (female: n = 15, age = 48.8 ± 10.1 years, symptoms duration = 13.4 ± 4.2 months, body mass index [BMI] = 28.8 ± 4.7 kg/m2 ) were compared to 20 healthy controls (female: n = 15, age = 48.1 ± 11.1 years, BMI = 22.9 ± 2.2 kg/m2 ). Neither FF nor T2 revealed signs of muscle degeneration or inflammation in either study groups. Diffusion tensor imaging (DTI) revealed reduced mean, axial, and radial diffusivity in the PCC group. CONCLUSIONS: Quantitative muscle MRI did not depict any signs of ongoing inflammation or dystrophic process in the skeletal muscles in PCC patients. However, differences observed in muscle DTI depict microstructural abnormalities, which may reflect potentially reversible fiber hypotrophy due to deconditioning. Further longitudinal and interventional studies should prove this hypothesis.

Quantitative muscle MRI captures early muscle degeneration in calpainopathy.

To evaluate differences in qMRI parameters of muscle diffusion tensor imaging (mDTI), fat-fraction (FF) and water T2 time in leg muscles of calpainopathy patients (LGMD R1/D4) compared to healthy controls, to correlate those findings to clinical parameters and to evaluate if qMRI parameters show muscle degeneration in not-yet fatty infiltrated muscles. We evaluated eight thigh and seven calf muscles of 19 calpainopathy patients and 19 healthy matched controls. MRI scans were performed on a 3T MRI including a mDTI, T2 mapping and mDixonquant sequence. Clinical assessment was done with manual muscle testing, patient questionnaires (ACTIVLIM, NSS) as well as gait analysis. Average FF was significantly different in all muscles compared to controls (p < 0.001). In muscles with less than 8% FF a significant increase of FA (p < 0.005) and decrease of RD (p < 0.004) was found in high-risk muscles of calpainopathy patients. Water T2 times were increased within the low- and intermediate-risk muscles (p ≤ 0.045) but not in high-risk muscles (p = 0.062). Clinical assessments correlated significantly with qMRI values: QMFM vs. FF: r = - 0.881, p < 0.001; QMFM versus FA: r = - 0.747, p < 0.001; QMFM versus MD: r = 0.942, p < 0.001. A good correlation of FF and diffusion metrics to clinical assessments was found. Diffusion metrics and T2 values are promising candidates to serve as sensitive early and non-invasive methods to capture early muscle degeneration in non-fat-infiltrated muscles in calpainopathies.

Robustness and stability of volume-based tractography in a multicenter setting.

Muscle diffusion tensor imaging (mDTI)-based tractography is a promising tool with which to detect subclinical changes in muscle injuries and to evaluate pathophysiology in neuromuscular diseases. Classic region of interest (ROI)-based tractography is very time-consuming and requires an examiner with extensive experience. (Semi)automatic approaches such as volume-based tractography (VBT) can diminish this problem but its robustness and stability are unknown. The aim of the current study was to assess the performance of VBT in a multicenter setting and to evaluate semiautomatic segmentation approaches in the analysis of VBT-derived data in terms of the comparability of the outcome measures. Five traveling volunteers underwent 3-T mDTI of seven calf muscles of both legs at six different MR sites. Tract properties and diffusion metrics were calculated using VBT. Within-subject coefficients of variance (wsCVs) and intraclass correlation coefficients (ICCs) were calculated to assess the multicenter reproducibility of tract properties such as tract density (TD), mean tract length, volume and tract propagation angle, and diffusion metrics such as fractional anisotropy, mean diffusivity, axial diffusivity (λ1 ) and radial diffusivity in traveling subjects. Furthermore, 50 individual datasets from five different centers (10 datasets per center) were pooled to assess the feasibility of VBT with manual and semiautomatic segmentation. To assess the differences of tract properties and diffusion metrics between segmentation approaches an ANOVA was performed, and ICC and Bland-Altman plots were analyzed. wsCVs and ICCs showed good reproducibility of the tract properties TD and volume, as well as diffusion metrics. ANOVA showed no significant differences between manual and semiautomatic approaches. ICCs were excellent (≥ 0.992) and Bland-Altman analysis did not reveal any systemic bias between the methods. Tract properties and diffusion metrics derived from VBT showed good comparability among centers. Semiautomatic approaches revealed excellent agreement with gold standard of manual segmentation. These findings suggest that pooling data from different centers to construct a reference database for tractography results is feasible using semiautomatic segmentation approaches.

3D Automated Segmentation of Lower Leg Muscles Using Machine Learning on a Heterogeneous Dataset.

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.

High Inter-Rater Reliability of Manual Segmentation and Volume-Based Tractography in Healthy and Dystrophic Human Calf Muscle.

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 (≤13%) and neuromuscular diseases (≤17%). Significant differences between methods were found for all diffusion metrics except for λ1. High inter-rater reliability was found for both MSB and VBT (ICC ≥ 0.972). Assessment of tract properties revealed high inter-rater reliability (ICC ≥ 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.

Quantitative Muscle-MRI Correlates with Histopathology in Skeletal Muscle Biopsies.

BACKGROUND: Skeletal muscle biopsy is one of the gold standards in the diagnostic workup of muscle disorders. By histopathologic analysis, characteristic features like inflammatory cellular infiltrations, fat and collagen replacement of muscle tissue or structural defects of the myofibers can be detected. In the past years, novel quantitative MRI (qMRI) techniques have been developed to quantify tissue parameters, thus providing a non-invasive diagnostic tool in several myopathies. OBJECTIVE: This proof-of-principle study was performed to validate the qMRI-techniques to skeletal muscle biopsy results. METHODS: Ten patients who underwent skeletal muscle biopsy for diagnostic purposes were examined by qMRI. Fat fraction, water T2-time and diffusion parameters were measured in the muscle from which the biopsy was taken. The proportion of fat tissue, the severity of degenerative and inflammatory parameters and the amount of type 1- and type 2- muscle fibers were determined in all biopsy samples. The qMRI-data were then correlated to the histopathological findings. RESULTS: The amount of fat tissue in skeletal muscle biopsy correlated significantly with the fat fraction derived from the Dixon sequence. The water T2-time, a parameter for tissue edema, correlated with the amount of vacuolar changes of myofibers and endomysial macrophages in the histopathologic analysis. No significant correlations were found for diffusion parameters. CONCLUSION: In this proof-of-principle study, qMRI techniques were related to characteristic histopathologic features in neuromuscular disorders. The study provides the basis for further development of qMRI methods in the follow-up of patients with neuromuscular disorders, especially in the context of emerging treatment strategies.

Evaluation of interrater reliability of different muscle segmentation techniques in diffusion tensor imaging.

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 < 0.001). 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.

Diffusion tensor imaging reveals changes in non-fat infiltrated muscles in late onset Pompe disease.

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 <10% fat-fraction. We evaluated 6 thigh and 7 calf muscles (both legs) of 18 LOPD and 29 healthy controls (HC) with muscle diffusion tensor imaging (mDTI), 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 analyzed. 6-Minute Walk Test (6-MWT) data were correlated to diffusion metrics. We found that mDTI showed significant differences between LOPD and HC in diffusion parameters (P < .05). Thigh muscles with <10% fat-fraction showed significant differences in MD, RD, and λ1-3 . MD positively correlated with 6-MWT (P = .06). To conclude, mDTI reveals diffusion restrictions in muscles of LOPD with and without fat-infiltration and reflects structural changes prior to fatty degeneration.

Diffusion tensor imaging of the human thigh: consideration of DTI-based fiber tracking stop criteria.

OBJECTIVES: To consider the tract-based analysis of DTI parameters in human muscle by assessing different fiber tracking stop criteria settings on diffusion parameters. MATERIALS AND METHODS: 30 healthy volunteers underwent a 3 T MRI. Diffusion-weighted images were acquired to perform DTI and fiber tracking analysis for six thigh muscles. Whole thigh muscles were evaluated by fiber tractography using different fiber tracking stop parameters [FA (0.01-0.15) to (0.4-0.99); angle 10°-30°, step size 0.75 mm, 1.5 mm, 3 mm]. Diffusion and tractography-derived parameters per stop criterion were compared using a repeated measure ANOVA including Bonferroni-corrected post hoc tests. RESULTS: We found significant differences in all examined diffusion parameters between different stop criteria (main effect p < 0.001). We showed different influence of tracking parameters on diffusion parameters in examined muscles (main effect p ≤ 0.001). CONCLUSIONS: Statistically significant differences in fiber tracking results using different stop criteria were shown. Fiber tracking stop criteria do have an important influence on study results and should be considered in the development of study protocols and comparison of studies. We recommend a FA minimum of 0.10 and a step size lower than voxel size, e.g., a half with a constant ratio between step size and angle of 10°/mm.