Diffusion tractography of the rat knee at microscopic resolution
Abstract
Purpose: To evaluate whole knee joint tractography, including articular cartilage, ligaments, meniscus, and growth plate using diffusion tensor imaging (DTI) at microscopic resolution. Methods: Three rat knee joints were scanned using a modified 3D diffusion‐weighted spin echo pulse sequence with 90‐ and 45‐μm isotropic spatial resolution at 9.4T. The b values varied from 250 to 1250 s/mm 2 with 4 times undersampling in phase directions. Fractional anisotropy (FA) and mean diffusivity (MD) were compared at different spatial resolution and b values. Tractography was evaluated at multiple b values and angular resolutions in different connective tissues, and compared with conventional histology. The mean tract length and tract volume in various types of tissues were also quantified. Results: DTI metrics (FA and MD) showed consistent quantitative results at 90‐ and 45‐μm isotropic spatial resolutions. Tractography of various connective tissues was found to be sensitive to the spatial resolution, angular resolution, and diffusion weightings. Higher spatial resolution (45 μm) supported tracking the cartilage collagen fiber tracts from the superficial zone to the deep zone, in a continuous and smooth progression in the transitional zone. Fiber length and fiber volume in the growth plate were strongly dependent on angular resolution and b values, whereas tractography in ligaments was found to be less dependent on spatial resolution. Conclusion: High spatial and angular resolution DTI and diffusion tractography can be valuable for knee joint research because of its visualization capacity for collagen fiber orientations and quantitative evaluation of tissue’s microscopic properties.
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Undersampling both phase encoding directions helps to fully explore the 2D sparsity preferred in CS reconstruction.
“Undersampling both phase encoding directions helps to fully explore the 2D sparsity preferred in CS reconstruction (Lustig et al. 2007; Wang et al. 2019).”
From Neurite orientation dispersion and density imaging of mouse brain microstructure (2019) · cites this paper as Wang et al. 2019
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- Authors
- Wang, N., Mirando, A. J., Cofer, G., Qi, Y., Hilton, M. J., & Johnson, G. A.
- Affiliations
- Duke University (US)
- Corresponding author
- Wang, Nian
- Venue
- Magnetic Resonance in Medicine
- Publisher
- Wiley
- Published
- 2019-01-22
- Volume
- 81
- Issue
- 6
- Pages
- 3775-3786
- ISSN
- 0740-3194 (ISSN-L)
- 1522-2594
- OpenAlex
- W2914526565
- Cited by
- 30
- References
- 59
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 5 · 2023: 5 · 2022: 4 · 2021: 3 · 2020: 7 · 2019: 3
- FWCI
- 2.81
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Magnetic Resonance in Medicine (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (1R01NS096720-01A1, 1S10OD010683-01)
- National Institute of Arthritis and Musculoskeletal and Skin Diseases (5R01AR063071-07)
- National Institute of Biomedical Imaging and Bioengineering (P41 EB015897)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Ultrasound Imaging and Elastography
- Keywords
- diffusion tractography, knee joint, articular cartilage, collagen fiber orientation, meniscus, ligaments, growth plate, fractional anisotropy, mean diffusivity, spatial resolution, angular resolution, b-value
- MeSH terms
- Animals, Cartilage, Articular, Image Processing, Computer-Assisted, Stifle, Anterior Cruciate Ligament, Anisotropy, Rats, Diffusion Tensor Imaging
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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