ArticleMagnetic resonance in medicine2021
Varying diffusion time to discriminate between simulated skeletal muscle injury models using stimulated echo diffusion tensor imaging.
Article in Magnetic resonance in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- The effect of microstructural variations in tendon and ligament on diffusion tensor MRI.bioRxiv : the preprint server for biology · 2026Article
- Relationships between diffusion tensor parameters and measures of skeletal muscle fiber size and strength after anterior cruciate ligament injury.Magnetic resonance imaging · 2025Article
- Diffusion Tensor Imaging of Rat Rotator Cuff Muscle With Histopathological Correlation: An Exploratory Study.NMR in biomedicine · 2025Article
- Texture analysis of T1- and T2-weighted images identifies myofiber atrophy and grip strength decline in streptozotocin-induced type 1 diabetic sarcopenia rats.Journal of orthopaedic surgery and research · 2025Article
- From Voxels to Physiology: A Review of Diffusion Magnetic Resonance Imaging Applications in Skeletal Muscle.Journal of magnetic resonance imaging : JMRI · 2025Review
- Stimulated echo acquisition mode (STEAM) diffusion tensor imaging with different diffusion encoding times in the supraspinatus muscle: Test-retest reliability and comparison to spin echo diffusion tensor imaging.NMR in biomedicine · 2025Article
- Multi-parametric quantitative MRI of the lower limb muscles in a longitudinal study of limb-girdle muscular dystrophy R9.PloS one · 2025Article
- A registration strategy to characterize DTI-observed changes in skeletal muscle architecture due to passive shortening.PloS one · 2025Article
- Investigating skeletal muscle micro-trauma with time-dependent diffusion and the random permeable barrier model.Scientific reports · 2024Article
- Accelerated, Physics-Inspired Inference of Skeletal Muscle Microstructure From Diffusion-Weighted MRI.IEEE transactions on medical imaging · 2024Article
- Compositional and Functional MRI of Skeletal Muscle: A Review.Journal of magnetic resonance imaging : JMRI · 2024Review
- A registration strategy to characterize DTI-observed changes in skeletal muscle architecture due to passive shortening.bioRxiv : the preprint server for biology · 2024Article
- Time-dependent diffusion tensor imaging and diffusion modeling of age-related differences in the medial gastrocnemius and feasibility study of correlations to histopathology.NMR in biomedicine · 2023Article
- Double pulsed field gradient diffusion MRI to assess skeletal muscle microstructure.Magnetic resonance in medicine · 2023Article
- Diffusion-tensor magnetic resonance imaging captures increased skeletal muscle fibre diameters in Becker muscular dystrophy.Journal of cachexia, sarcopenia and muscle · 2023Article
- Intravoxel Incoherent Motion Magnetic Resonance Imaging in Skeletal Muscle: Review and Future Directions.Journal of magnetic resonance imaging : JMRI · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
purposeEvaluate the relationship between muscle microstructure, diffusion time (Δ), and the diffusion tensor (DT) to identify the optimal Δ where changes in muscle fiber size may be detected.
methodsThe DT was simulated in models with histology informed geometry over a range of Δ with a stimulated echo DT imaging (DTI) sequence using the numerical simulation application DifSim. The difference in the DT at each Δ between healthy and injured skeletal muscle models was calculated, to identify the optimal Δ at which changes in muscle fiber size may be detected. The random permeable barrier model (RPBM) was used to estimate muscle microstructure from the simulated DT measurements, which were compared to the ground truth.
resultsAcross all models, fractional anisotropy provided greater contrast between injured and control models than diffusivity measurements. Compared to control models, in atrophic injury models, the greatest difference in the DT was found between 90 ms and 250 ms. In models with acute edema, the contrast between injured and control muscle increased with increasing diffusion time, although these models had smaller mean fiber areas. RPBM systematically underestimated fiber size but accurately estimated surface area-to-volume ratio of simulated models.
conclusionThese findings may better inform pulse sequence parameter selection when performing DTI experiments in vivo. If only a single diffusion experiment can be performed, the selected Δ should be ~170 ms to maximize the ability to discriminate between different injury models. Ideally several diffusion times between 90 ms and 500 ms should be sampled in order to maximize diffusion contrast, particularly when the disease process is unknown.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.