ArticleTissue engineering. Part A2017
Article in Tissue engineering. Part A, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed, 40 citations in OpenAlex.
- Relationships between diffusion tensor parameters and measures of skeletal muscle fiber size and strength after anterior cruciate ligament injury.Magnetic resonance imaging · 2025Article
- 3D vector field-guided toolpathing for 3D bioprinting.Communications engineering · 2025Article
- Diffusion Tensor Imaging of Rat Rotator Cuff Muscle With Histopathological Correlation: An Exploratory Study.NMR in biomedicine · 2025Article
- From Voxels to Physiology: A Review of Diffusion Magnetic Resonance Imaging Applications in Skeletal Muscle.Journal of magnetic resonance imaging : JMRI · 2025Review
- Double pulsed field gradient diffusion MRI to assess skeletal muscle microstructure.Magnetic resonance in medicine · 2023Article
- Compensating the cell-induced light scattering effect in light-based bioprinting using deep learning.Biofabrication · 2021Article
- Three-dimensional printed talar prosthesis with biological function for giant cell tumor of the talus: A case report and review of the literature.World journal of clinical cases · 2021Article
- Varying diffusion time to discriminate between simulated skeletal muscle injury models using stimulated echo diffusion tensor imaging.Magnetic resonance in medicine · 2021Article
- Exercise-induced muscle damage: mechanism, assessment and nutritional factors to accelerate recovery.European journal of applied physiology · 2021Review
- Medical imaging of tissue engineering and regenerative medicine constructs.Biomaterials science · 2021Review
- Photopolymerizable Biomaterials and Light-Based 3D Printing Strategies for Biomedical Applications.Chemical reviews · 2020Review
- Controlled Growth Factor Release in 3D-Printed Hydrogels.Advanced healthcare materials · 2020Article
- Review
- High-fidelity 3D Printing using Flashing Photopolymerization.Additive manufacturing · 2019Article
- Relationships between tissue microstructure and the diffusion tensor in simulated skeletal muscle.Magnetic resonance in medicine · 2018Article
- Nanoscale 3D printing of hydrogels for cellular tissue engineering.Journal of materials chemistry. B · 2018Article
- Article
- Erbium-Based Perfusion Contrast Agent for Small-Animal Microvessel Imaging.Contrast media & molecular imaging · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
The ability to noninvasively assess skeletal muscle microstructure, which predicts function and disease, would be of significant clinical value. One method that holds this promise is diffusion tensor magnetic resonance imaging (DT-MRI), which is sensitive to the microscopic diffusion of water within tissues and has become ubiquitous in neuroimaging as a way of assessing neuronal structure and damage. However, its application to the assessment of changes in muscle microstructure associated with injury, pathology, or age remains poorly defined, because it is difficult to precisely control muscle microstructural features in vivo. However, recent advances in additive manufacturing technologies allow precision-engineered diffusion phantoms with histology informed skeletal muscle geometry to be manufactured. Therefore, the goal of this study was to develop skeletal muscle phantoms at relevant size scales to relate microstructural features to MRI-based diffusion measurements. A digital light projection based rapid 3D printing method was used to fabricate polyethylene glycol diacrylate based diffusion phantoms with (1) idealized muscle geometry (no geometry; fiber sizes of 30, 50, or 70 μm or fiber size of 50 μm with 40% of walls randomly deleted) or (2) histology-based geometry (normal and after 30-days of denervation) containing 20% or 50% phosphate-buffered saline (PBS). Mean absolute percent error (8%) of the printed phantoms indicated high conformity to templates when "fibers" were >50 μm. A multiple spin-echo echo planar imaging diffusion sequence, capable of acquiring diffusion weighted data at several echo times, was used in an attempt to combine relaxometry and diffusion techniques with the goal of separating intracellular and extracellular diffusion signals. When fiber size increased (30-70 μm) in the 20% PBS phantom, fractional anisotropy (FA) decreased (0.32-0.26) and mean diffusivity (MD) increased (0.44 × 10
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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.