Journal article
High Resolution Micro-Computed Tomography Reveals a Network of Collagen Channels in the Body Region of the Knee Meniscus
- Abstract:
- The meniscus is an integral part of the human knee, preventing joint degradation by distributing load from the femoral condyles to the tibial plateau. Recent qualitative studies suggested that the meniscus is constituted by an intricate net of collagen channels inside which the fluid flows during loading. The aim of this study is to describe in detail the structure in which this fluid flows by quantifying the orientation and morphology of the collagen channels of the meniscal tissue. A 7 mm cylindrical sample, extracted vertically from the central part of a lateral porcine meniscus was freeze-dried and scanned using the highest-to-date resolution Microscopic Computed Tomography. The orientation of the collagen channels, their size and distribution was calculated. Comparisons with confocal multi-photon microscopy imaging performed on portions of fresh tissue have shown that the freeze-dried procedure adopted here ensures that the native architecture of the tissue is maintained. Sections of the probe at different heights were examined to determine differences in composition and structure along the sample from the superficial to the internal layers. Results reveal a different arrangement of the collagen channels in the superficial layers with respect to the internal layers with the internal layers showing a more ordered structure of the channels oriented at 30∘ with respect to the vertical, a porosity of 66.28% and the mean size of the channels of 22.14 μm
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 1.6MB, Terms of use)
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- Publisher copy:
- 10.1007/s10439-021-02763-6
Authors
+ FP7 People: Marie-Curie Actions
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- Funder identifier:
- 10.13039/100011264
- Grant:
- 796405
- Publisher:
- Springer
- Journal:
- Annals of Biomedical Engineering More from this journal
- Volume:
- 49
- Issue:
- 9
- Pages:
- 2273-2281
- Publication date:
- 2021-04-07
- DOI:
- EISSN:
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1573-9686
- ISSN:
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0090-6964
- Language:
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English
- Keywords:
- Pubs id:
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1171953
- Local pid:
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pubs:1171953
- Source identifiers:
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W3142781693
- Deposit date:
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2026-03-24
- ARK identifier:
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Terms of use
- Copyright date:
- 2021
- Licence:
- CC Attribution (CC BY)
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