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Cited by 7Knee injuries and reconstruction techniquesMedical Image Segmentation TechniquesLower Extremity Biomechanics and Pathologies

The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.

An in vivo subject-specific 3D functional knee joint model using combined MR imaging

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Chen, Bailiang, Lambrou, Tryphon, Offiah, Amaka C., Gondim Teixeira, Pedro A., Fry, Martin, Todd-Pokropek, Andrew·2013·International Journal of Computer Assisted Radiology and Surgery
DOI 10.1007/s11548-012-0801-7
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Abstract

Purpose We aim to quantitatively characterise the knee joint function in vivo under body-weight-bearing conditions via subject-specific models extracted from magnetic resonance (MR) data, in order to better understand the knee joint kinematic function in 3D.Methods Six healthy volunteers without any record of knee abnormality were scanned using a combined MR imaging strategy to record quasi-squatting motion and 3D knee anatomy. After a semi-automatic segmentation to delineate tibio-femoral articulation components, motion data were mapped to the anatomical data using a bi-rigid registration in order to achieve six degrees of freedom. The individual knee joint function was characterised by analysing the tibio-femoral articulation contact mechanism based on the reconstructed models in 3D and MR images in 2D. Contact points were extracted and their trajectory was plotted on the tibia plateau.Results The 3D models clearly show the relative rotation and gliding between tibia and femur during global flexion. Within the measured flexion arc, the contact points move less between 30[Formula: see text] and 100[Formula: see text] on both tibial plateaux as compared to that on the rest of the flexion arc. Four out of the six volunteers showed a global pattern of less moving extent of contact points on the medial tibial plateau than on the lateral tibial plateau in both 3D and 2D.Conclusion The proposed subject-specific model is able to characterise knee joint kinematic function. It provides a way to describe knee joint surface kinematics quantitatively, which may help to better understand the knee function and joint derangements.

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Crossref · 10.1007/s11548-012-0801-7

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Metadata

Authors
Chen, B., Lambrou, T., Offiah, A. C., Gondim Teixeira, P. A., Fry, M., & Todd-Pokropek, A.
Affiliations
  • Centre Hospitalier Régional et Universitaire de Nancy (FR)
  • University of Lincoln (GB)
  • University of Sheffield (GB)
  • University College London (GB)
Corresponding author
Chen, Bailiang
ORCID
Venue
International Journal of Computer Assisted Radiology and Surgery
Publisher
Springer Science and Business Media LLC
Published
2012-12-02
Volume
8
Issue
5
Pages
741-750
ISSN
  • 1861-6410 (ISSN-L)
  • 1861-6429
DOI
10.1007/s11548-012-0801-7
OpenAlex
W2080682424
Cited by
7
References
29
Citations by year
2021: 2 · 2019: 1 · 2018: 1 · 2017: 1 · 2016: 1 · 2015: 1
FWCI
0.33
Type
journal article
Language
en
Open access
Licence
Locations
  • International Journal of Computer Assisted Radiology and Surgery (publishedVersion)
  • PubMed (publishedVersion)
  • HAL (submittedVersion)
  • UCL Discovery (University College London) (submittedVersion)
  • Figshare (submittedVersion, cc-by)
Topics
  • Health Sciences › Medicine › Surgery › Knee injuries and reconstruction techniques
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
  • Physical Sciences › Engineering › Biomedical Engineering › Lower Extremity Biomechanics and Pathologies
Keywords
knee kinematics, subject-specific knee model, squatting motion
MeSH terms
Adult, Female, Humans, Knee Joint, Magnetic Resonance Imaging, Male, Range of Motion, Articular, Imaging, Three-Dimensional, Healthy Volunteers

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