On the sensitivity of the diffusion MRI signal to brain activity in response to a motor cortex paradigm

Diffusion functional MRI (dfMRI) is a promising technique to map functional activations by acquiring diffusion-weighed spin-echo images. In previous studies, dfMRI showed higher spatial accuracy at activation mapping compared to classic functional MRI approaches. However, it remains unclear whether dfMRI measures result from changes in the intra-/extracellular environment, perfusion and/or T2 values. We designed an acquisition/quantification scheme to disentangle such effects in the motor cortex during a finger tapping paradigm. dfMRI was acquired at specific diffusion weightings to selectively suppress perfusion and free-water diffusion, then times series of the apparent diffusion coefficient (ADC-fMRI) and of the perfusion signal fraction (IVIM-fMRI) were derived. ADC-fMRI provided ADC estimates sensitive to changes in perfusion and free-water volume, but not to T2/T2* values. With IVIM-fMRI we isolated the perfusion contribution to ADC, while suppressing T2 effects. Compared to conventional gradient-echo BOLD fMRI, activation maps obtained with dfMRI and ADC-fMRI had smaller clusters, and the spatial overlap between the three techniques was below 50%. Increases of perfusion fractions were observed during task in both dfMRI and ADC-fMRI activations. Perfusion effects were more prominent with ADC-fMRI than with dfMRI but were significant in less than 25% of activation ROIs. Taken together, our results suggest that the sensitivity to task of dfMRI derives from a decrease of hindered diffusion and an increase of the pseudo-diffusion signal fraction, leading to different, more confined spatial activation patterns compared to classic functional MRI.Comment: Submitted to peer-reviewed journa

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

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 musclespecific 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 in sporadic inclusion body myositis (sIBM): A prospective cohort study

Background: Sporadic inclusion body myositis (sIBM) is the predominant idiopathic inflammatory myopathy (IIM) in older people. Limitations of classical clinical assessments have been discussed as possible explanations for failed clinical trials, underlining the need for more sensitive outcome measures. Quantitative muscle MRI (qMRI) is a promising candidate for evaluating and monitoring sIBM. Objective: Longitudinal assessment of qMRI in sIBM patients. Methods: We evaluated fifteen lower extremity muscles of 12 sIBM patients (5 females, mean age 69.6, BMI 27.8) and 12 healthy age-and gender-matched controls. Seven patients and matched controls underwent a follow-up evaluation after one year. Clinical assessment included testing for muscle strength with Quick Motor Function Measure (QMFM), IBM functional rating scale (IBM-FRS), and gait analysis (6-minute walking distance). 3T-MRI scans of the lower extremities were performed, including a Dixon-based sequence, T2 mapping and Diffusion Tensor Imaging. The qMRI-values fat-fraction (FF), water T2 relaxation time (wT2), fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ1), and radial diffusivity (RD) were analysed. Results: Compared to healthy controls, significant differences for all qMRI parameters averaged over all muscles were found in sIBM using a MANOVA (p < 0.001). In low-fat muscles (FF < 10%), a significant increase of wT2 and FA with an accompanying decrease of MD, λ1, and RD was observed (p≤0.020). The highest correlation with clinical assessments was found for wT2 values in thigh muscles (r≤-0.634). Significant changes of FF (+3.0%), wT2 (+0.6 ms), MD (-0.04 10-3mm2/s), λ1 (-0.05 10-3mm2/s), and RD (-0.03 10-3mm2/s) were observed in the longitudinal evaluation of sIBM patients (p≤0.001). FA showed no significant change (p = 0.242). Conclusion: qMRI metrics correlate with clinical findings and can reflect different ongoing pathophysiological mechanisms. While wT2 is an emerging marker of disease activity, the role of diffusion metrics, possibly reflecting changes in fibre size and intracellular deposits, remains subject to further investigations

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

Author Correction: Quantitative muscle MRI captures early muscle degeneration in calpainopathy

Correction to: Scientific Reports https://doi.org/10.1038/s41598-022-23972-6, published online 16 November 202

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 (Gaa 6neo/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 MRI of skeletal muscle in a cross-sectional cohort of patients with spinal muscular atrophy types 2 and 3

The aim of this study was to document upper leg involvement in spinal muscular atrophy (SMA) with quantitative MRI (qMRI) in a cross-sectional cohort of patients of varying type, disease severity and age. Thirty-one patients with SMA types 2 and 3 (aged 29.6 [7.6-73.9] years) and 20 healthy controls (aged 37.9 [17.7-71.6] years) were evaluated in a 3 T MRI with a protocol consisting of DIXON, T2 mapping and diffusion tensor imaging (DTI). qMRI measures were compared with clinical scores of motor function (Hammersmith Functional Motor Scale Expanded [HFMSE]) and muscle strength. Patients exhibited an increased fat fraction and fractional anisotropy (FA), and decreased mean diffusivity (MD) and T2 compared with controls (all P < .001). DTI parameters FA and MD manifest stronger effects than can be accounted for the effect of fatty replacement. Fat fraction, FA and MD show moderate correlation with muscle strength and motor function: FA is negatively associated with HFMSE and Medical Research Council sum score (τ = -0.56 and -0.59; both P < .001) whereas for fat fraction values are τ = -0.50 and -0.58, respectively (both P < .001). This study shows that DTI parameters correlate with muscle strength and motor function. DTI findings indirectly indicate cell atrophy and act as a measure independently of fat fraction. Combined these data suggest the potential of muscle DTI in monitoring disease progression and to study SMA pathogenesis in muscle