Quantitative MRI Reveals Microstructural Changes in the Upper Leg Muscles After Running a Marathon

Hooijmans, Melissa T.; Monte, Jithsa R.; Froeling, Martijn; Berg-Faay, Sandra van den; Aengevaeren, Vincent L.; Hemke, Robert; Smithuis, Frank F; Eijsvogels, Thijs M. H.; Bakermans, Adrianus J.; Maas, Mario; Nederveen, Aart J.; Strijkers, Gustav J.

doi:10.1002/jmri.27106

Cited by 30 publications

(41 citation statements)

References 41 publications

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“…The MRI protocol included proton density‐weighted (PD), T 2 ‐weighted (T2w) and DWI in an axial slice order from proximal to distal (total acquisition time 27 min). To avoid shimming artifacts due to large field of view (FOV), the upper leg region was divided into three FOVs of 480 × 264 × 150 mm 3 along the z ‐axis (stacks) 25 . For accurate merging the stacks had an overlap of 10 mm.…”

Section: Methodsmentioning

confidence: 99%

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

et al. 2020

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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

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Section: Methodsmentioning

confidence: 99%

“…To avoid shimming artifacts due to large field of view (FOV), the upper leg region was divided into three FOVs of 480 × 264 × 150 mm 3 along the z-axis (stacks). 25 For accurate merging the stacks had an overlap of 10 mm.…”

Section: Data Acquisitionmentioning

confidence: 99%

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

et al. 2020

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“…7,8 Our group investigated changes in DTI indices in the upper leg muscles during recovery after a marathon. 9,10 Distinct changes in DTI indices were detected in muscles that appeared normal on T 2 -weighted images, demonstrating the added value of DTI as a sensitive readout of muscle integrity.…”

Section: Introductionmentioning

confidence: 97%

“…Furthermore, in sport medicine, DTI has shown promise as a relevant tool to understand the muscle recovery process that follows physical activity and after injury 7,8 . Our group investigated changes in DTI indices in the upper leg muscles during recovery after a marathon 9,10 . Distinct changes in DTI indices were detected in muscles that appeared normal on T 2 ‐weighted images, demonstrating the added value of DTI as a sensitive readout of muscle integrity.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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 (λ 3). 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 λ 3 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 λ 3 (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.

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“…In skeletal muscle, the highest diffusivity is observed along the axis of the fiber [axial diffusivity (AD)] and the lowest in the fiber cross section [radial diffusivity (RD)]. Due to its exquisite sensitivity to tissue microstructure, DTI is becoming an increasing popular tool to assess skeletal muscle status in a wide range of diseases ( 1 ) and muscle injuries ( 2 ).…”

Section: Introductionmentioning

confidence: 99%

Diffusion Tensor Imaging of Skeletal Muscle Contraction Using Oscillating Gradient Spin Echo

et al. 2021

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Diffusion tensor imaging (DTI) measures water diffusion in skeletal muscle tissue and allows for muscle assessment in a broad range of neuromuscular diseases. However, current DTI measurements, typically performed using pulsed gradient spin echo (PGSE) diffusion encoding, are limited to the assessment of non-contracted musculature, therefore providing limited insight into muscle contraction mechanisms and contraction abnormalities. In this study, we propose the use of an oscillating gradient spin echo (OGSE) diffusion encoding strategy for DTI measurements to mitigate the effect of signal voids in contracted muscle and to obtain reliable diffusivity values. Two OGSE sequences with encoding frequencies of 25 and 50 Hz were tested in the lower leg of five healthy volunteers with relaxed musculature and during active dorsiflexion and plantarflexion, and compared with a conventional PGSE approach. A significant reduction of areas of signal voids using OGSE compared with PGSE was observed in the tibialis anterior for the scans obtained in active dorsiflexion and in the soleus during active plantarflexion. The use of PGSE sequences led to unrealistically elevated axial diffusivity values in the tibialis anterior during dorsiflexion and in the soleus during plantarflexion, while the corresponding values obtained using the OGSE sequences were significantly reduced. Similar findings were seen for radial diffusivity, with significantly higher diffusivity measured in plantarflexion in the soleus muscle using the PGSE sequence. Our preliminary results indicate that DTI with OGSE diffusion encoding is feasible in human musculature and allows to quantitatively assess diffusion properties in actively contracting skeletal muscle. OGSE holds great potential to assess microstructural changes occurring in the skeletal muscle during contraction, and for non-invasive assessment of contraction abnormalities in patients with muscle diseases.

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Quantitative MRI Reveals Microstructural Changes in the Upper Leg Muscles After Running a Marathon

Cited by 30 publications

References 41 publications

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

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

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

Diffusion Tensor Imaging of Skeletal Muscle Contraction Using Oscillating Gradient Spin Echo

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