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

A Comparison of Skeletal Muscle Diffusion Tensor Imaging Tractography Seeding Methods

The internal arrangement of a muscle's fibers with respect to its mechanical line of action (muscle architecture) is a major determinant of muscle function. Muscle architecture can be quantified using diffusion tensor magnetic resonance imaging-based tractography, which propagates streamlines from a set of seed points by integrating vectors that represent the direction of greatest water diffusion (and by inference, the local fiber orientation). Previous work has demonstrated that tractography outcomes are sensitive to the method for defining seed points, but this sensitivity has not been fully examined. To do so, we developed a realistic simulated muscle architecture and implemented four novel methods for tract seeding: seeding along the muscle-aponeurosis boundary with an updated procedure for rounding seed points prior to lookup in the muscle boundary mask and diffusion tensor matrix (APO-3); voxel-based seeding throughout the muscle volume at a user-specified spatial frequency (VXL-1); voxel-based seeding throughout the muscle volume at a variable spatial frequency (VXL-2), and seeding near external and internal muscle boundaries (VXL-3). We then implemented these methods in an example human dataset. The updated aponeurosis seeding procedures allow more accurate and robust tract propagation from seed points. The voxel-based seeding methods had quantification outcomes that closely matched the updated aponeurosis seeding method. Further, the voxel-based methods can accelerate the overall workflow and may be beneficial in high throughput analysis of multi-muscle datasets. Continued evaluation of these methods in a wider range of muscle architectures is warranted.

Relationships between quantitative magnetic resonance imaging measures at the time of return to sport and clinical outcomes following acute hamstring strain injury

Hamstring strain injuries (HSI) are a common occurrence in athletics and complicated by high rates of reinjury. Evidence of remaining injury observed on magnetic resonance imaging (MRI) at the time of return to sport (RTS) may be associated with strength deficits and prognostic for reinjury, however, conventional imaging has failed to establish a relationship. Quantitative measure of muscle microstructure using diffusion tensor imaging (DTI) may hold potential for assessing a possible association between injury-related structural changes and clinical outcomes. The purpose of this study was to determine the association of RTS MRI-based quantitative measures, such as edema volume, muscle volume, and DTI metrics, with clinical outcomes (i.e., strength and reinjury) following HSI. Spearman's correlations and Firth logistic regressions were used to determine relationships in between-limb imaging measures and between-limb eccentric strength and reinjury status, respectively. Twenty injuries were observed, with four reinjuries. At the time of RTS, between-limb differences in eccentric hamstring strength were significantly associated with principal effective diffusivity eigenvalue λ1 (r = -0.64, p = 0.003) and marginally associated with mean diffusivity (r = -0.46, p = 0.056). Significant relationships between other MRI-based measures of morphology and eccentric strength were not detected, as well as between any MRI-based measure and reinjury status. In conclusion, this preliminary evidence indicates DTI may track differences in hamstring muscle microstructure, not captured by conventional imaging at the whole muscle level, that relate to eccentric strength.

From Voxels to Physiology: A Review of Diffusion Magnetic Resonance Imaging Applications in Skeletal Muscle

Skeletal muscle has a classic structure function relationship; both skeletal muscle microstructure and architecture are directly related to force generating capacity. Biopsy, the gold standard for evaluating muscle microstructure, is highly invasive, destructive to muscle, and provides only a small amount of information about the entire volume of a muscle. Similarly, muscle fiber lengths and pennation angles, key features of muscle architecture predictive of muscle function, are traditionally studied via cadaveric dissection. Noninvasive techniques such as diffusion magnetic resonance imaging (dMRI) offer quantitative approaches to study skeletal muscle microstructure and architecture. Despite its prevalence in applications for musculoskeletal research, clinical adoption is hindered by a lack of understanding regarding its sensitivity to clinically important biomarkers such as muscle fiber cross-sectional area. This review aims to elucidate how dMRI has been utilized to study skeletal muscle, covering fundamentals of muscle physiology, dMRI acquisition techniques, dMRI modeling, and applications where dMRI has been leveraged to noninvasively study skeletal muscle changes in response to disease, aging, injury, and human performance. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

The role of pennation angle and architectural gearing to rate of force development in dynamic and isometric muscle contractions

BACKGROUND

Associations between muscle architecture and rate of force development (RFD) have been largely studied during fixed-end (isometric) contractions. Fixed-end contractions may, however, limit muscle shape changes and thus alter the relationship between muscle architecture an RFD.

AIM

We compared the correlation between muscle architecture and architectural gearing and knee extensor RFD when assessed during dynamic versus fixed-end contractions.

METHODS

Twenty-two recreationally active male runners performed dynamic knee extensions at constant acceleration (2000°s-2) and isometric contractions at a fixed knee joint angle (fixed-end contractions). Torque, RFD, vastus lateralis muscle thickness, and fascicle dynamics were compared during 0-75 and 75-150 ms after contraction onset.

RESULTS

Resting fascicle angle was moderately and positively correlated with RFD during fixed-end contractions (r = 0.42 and 0.46 from 0-75 and 75-150 ms, respectively; p < 0.05), while more strongly (p < 0.05) correlated with RFD during dynamic contractions (r = 0.69 and 0.73 at 0-75 and 75-150 ms, respectively; p < 0.05). Resting fascicle angle was (very) strongly correlated with architectural gearing (r = 0.51 and 0.73 at 0-75 ms and 0.50 and 0.70 at 75-150 ms; p < 0.05), with gearing in turn also being moderately to strongly correlated with RFD in both contraction conditions (r = 0.38-0.68).

CONCLUSION

Resting fascicle angle was positively correlated with RFD, with a stronger relationship observed in dynamic than isometric contraction conditions. The stronger relationships observed during dynamic muscle actions likely result from different restrictions on the acute changes in muscle shape and architectural gearing imposed by isometric versus dynamic muscle contractions.

Predicted effects of image acquisition and analysis conditions on DTMRI tractography-based muscle architecture estimates

PURPOSE

To quantify the effects of the intrinsic signal pattern, image acquisition conditions, and data analysis conditions on diffusion-tensor MRI (DTMRI) tractography-based muscle architecture estimates using a sampling-reconstruction assessment framework.

METHODS

Numerical models of muscles were constructed with realistic architectural properties. DTMRI signals were computed at signal-to-noise ratio (SNR) of 24-96 and common voxel sizes. Fiber tracking was performed, and the results were compared with the known architectural properties.

RESULTS

SNR exerted the most significant impact on the outcome. The outcome variables approached asymptotes at SNR ≈ 54. Large in-plane voxel dimensions reduced the similarity between reconstructed fibers and the known architectural properties. Higher order polynomials helped reconstruct fibers with more complicated geometry but overfit noise for less complex geometries. The intrinsic fiber curvature also affected the robustness of polynomial smoothing to SNR. Other conditions, such as the fiber dimensionality, voxel aspect ratio, and slice thickness, did not affect the outcomes.

CONCLUSION

SNR ≥ 54 is recommended for accurate muscle architecture characterization using DTMRI. Averaged across all simulated conditions, the greatest percent errors under SNR = 54 were -5.6% and -4.0% for the pennation angle and fiber-tract length estimates, respectively. For fiber tracts with intermediate intrinsic curvature, the greatest percent error for the curvature estimate was 9.8% for SNR = 54. Smaller in-plane voxel size (≤1.5 mm) is preferred to minimize the estimation error in architectural properties. If necessary, slice thickness may be adjusted within typical ranges to achieve sufficient SNR when slices are aligned near the fiber direction. Third-order polynomial fitting is appropriate for smoothing fiber tracts.

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.

Diffusion tensor imaging: Influence of segmentation on fiber tracking in the supraspinatus muscle-An inter-operator reliability analysis

The ability of muscle to generate force depends on its architecture and health condition. MR-based diffusion tensor imaging of muscle (mDTI) is an innovative approach for showing the fiber arrangement for the whole muscle volume. For accurate calculations of fiber metrics, muscle segmentation prior to tractography is regarded as necessary. Since segmentation is known to be operator dependent, it is important to understand how segmentation affects tractography. The aim of this study was to compare the results of deterministic fiber tracking based on muscle models generated by two independent operators. In addition, this study compares the results with a segmentation-free approach. Fifteen subjects underwent mDTI of the right shoulder. The results showed that mDTI can be successfully applied to complex joints such as the human shoulder. Furthermore, operator segmentation did not influence the results of fiber tracking and fascicle length (FL), fiber volume (FV), fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) showed excellent intraclass correlation estimates (≥ 0.975). As an exploratory approach, the segmentation-free fiber tracking showed significant differences in terms of mean fascicle length. Based on these findings, we conclude that tractography is not sensitive to small deviations in muscle segmentation. Furthermore, it implies that mDTI and automatic segmentation approaches or even a segmentation-free analysis can be considered for evaluation of muscle architecture.

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.

Effect of two eccentric hamstring exercises on muscle architectural characteristics assessed with diffusion tensor MRI

OBJECTIVES

To evaluate the effect of a Nordic hamstring exercise or Diver hamstring exercise intervention on biceps femoris long head, semitendinosus and semimembranosus muscle's fascicle length and orientation through diffusion tensor imaging (DTI) with magnetic resonance imaging.

METHODS

In this three-arm, single-center, randomized controlled trial, injury-free male basketball players were randomly assigned to a Nordic, Diver hamstring exercise intervention or control group. The primary outcome was the DTI-derived fascicle length and orientation of muscles over 12 weeks.

RESULTS

Fifty-three participants were included for analysis (mean age 22 ± 7 years). Fascicle length in the semitendinosus over 12 weeks significantly increased in the Nordic-group (mean [M]: 20.8 mm, 95% confidence interval [95% CI]: 7.8 to 33.8) compared with the Control-group (M: 0.9 mm, 95% CI: -7.1 to 8.9), mean between-groups difference: 19.9 mm, 95% CI: 1.9 to 37.9, p = 0.026. Fascicle orientation in the biceps femoris long head over 12 weeks significantly decreased in the Diver-group (mean: -2.6°, 95% CI: -4.1 to -1.0) compared with the Control-group (mean: -0.2°, 95% CI: -1.4 to 1.0), mean between-groups difference: -2.4°, 95% CI: -4.7 to -0.1, p = 0.039.

CONCLUSION

The Nordic hamstring exercise intervention did significantly increase the fascicle length of the semitendinosus and the Diver hamstring exercise intervention did significantly change the orientation of fascicles of the biceps femoris long head. As both exercises are complementary to each other, the combination is relevant for preventing hamstring injuries.

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.

A handbook for beginners in skeletal muscle diffusion tensor imaging: physical basis and technical adjustments

Magnetic resonance imaging (MRI) of skeletal muscle is routinely performed using morphological sequences to acquire anatomical information. Recently, there is an increasing interest in applying advanced MRI techniques that provide pathophysiologic information for skeletal muscle evaluation to complement standard morphologic information. Among these advanced techniques, diffusion tensor imaging (DTI) has emerged as a potential tool to explore muscle microstructure. DTI can noninvasively assess the movement of water molecules in well-organized tissues with anisotropic diffusion, such as skeletal muscle. The acquisition of DTI studies for skeletal muscle assessment requires specific technical adjustments. Besides, knowledge of DTI physical basis and skeletal muscle physiopathology facilitates the evaluation of this advanced sequence and both image and parameter interpretation. Parameters derived from DTI provide a quantitative assessment of muscle microstructure with potential to become imaging biomarkers of normal and pathological skeletal muscle. KEY POINTS: • Diffusion tensor imaging (DTI) allows to evaluate the three-dimensional movement of water molecules inside biological tissues. • The skeletal muscle structure makes it suitable for being evaluated with DTI. • Several technical adjustments have to be considered for obtaining robust and reproducible DTI studies for skeletal muscle assessment, minimizing potential artifacts.

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.

MRI and muscle imaging for idiopathic inflammatory myopathies

Although idiopathic inflammatory myopathies (IIM) are a heterogeneous group of diseases nearly all patients display muscle inflammation. Originally, muscle biopsy was considered as the gold standard for IIM diagnosis. The development of muscle imaging led to revisiting not only the IIM diagnosis strategy but also the patients' follow-up. Different techniques have been tested or are in development for IIM including positron emission tomography, ultrasound imaging, ultrasound shear wave elastography, though magnetic resonance imaging (MRI) remains the most widely used technique in routine. Whereas guidelines on muscle imaging in myositis are lacking here we reviewed the relevance of muscle imaging for both diagnosis and myositis patients' follow-up. We propose recommendations about when and how to perform MRI on myositis patients, and we describe new techniques that are under development.

A Longitudinal Study of T2 Mapping Combined With Diffusion Tensor Imaging to Quantitatively Evaluate Tissue Repair of Rat Skeletal Muscle After Frostbite

Purpose: T2 mapping and diffusion tensor imaging (DTI) enable the detection of changes in the skeletal muscle microenvironment. We assessed T2 relaxation times, DTI metrics, performed histological characterization of frostbite-induced skeletal muscle injury and repair, and provided diagnostic imaging biomarkers.

Design and Methods: Thirty-six Sprague Dawley rats (200 ± 10 g) were obtained. Thirty rats were used for establishing a skeletal muscle frostbite model, and six were untreated controls. Functional MR sequences were performed on rats on days 0, 3, 5, 10, and 14 (n = 6 per time point). Rats were then sacrificed to obtain the quadriceps muscles. Tensor eigenvalues (λ1, λ2, and λ3), mean diffusivity (MD), fractional anisotropy (FA), and T2 values were compared between the frostbite model and control rats. ImageJ was used to measure the extracellular area fraction (EAF), muscle fiber cross-sectional area (fCSA), and skeletal muscle tumor necrosis factor α (TNF-α), and Myod1 expression. The correlation between the histological and imaging parameters of the frostbitten skeletal muscle was evaluated. Kolmogorov–Smirnoff test, Leven’s test, one-way ANOVA, and Spearman coefficient were used for analysis.

Results: T2 relaxation time of frostbitten skeletal muscle was higher at all time points (p < 0.01). T2 relaxation time correlated with EAF, and TNF-α and Myod1 expression (r = 0.42, p < 0.05; r = 0.86, p < 0.01; r = 0.84, p < 0.01). The average tensor metrics (MD, λ1, λ2, and λ3) of skeletal muscle at 3 and 5 days of frostbite increased (p < 0.05), and fCSA correlated with λ1, λ2, and λ3, and MD (r = 0.65, p < 0.01; r = 0.48, p < 0.01; r = 0.52, p < 0.01; r = 0.62, p < 0.01).

Conclusion: T2 mapping and DTI imaging detect frostbite-induced skeletal muscle injury early. This combined approach can quantitatively assess skeletal muscle repair and regeneration within 2 weeks of frostbite. Imaging biomarkers for the diagnosis of frostbite were suggested.

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.