1. Impact of knee geometry on joint contact mechanics after meniscectomy.
- Author
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Deng R, Uzuner S, and Li LP
- Subjects
- Humans, Biomechanical Phenomena, Male, Female, Adult, Computer Simulation, Middle Aged, Menisci, Tibial surgery, Menisci, Tibial physiopathology, Menisci, Tibial diagnostic imaging, Meniscectomy, Knee Joint physiopathology, Knee Joint surgery, Finite Element Analysis, Magnetic Resonance Imaging
- Abstract
Finite element modeling has served as a cornerstone in understanding knee joint mechanics post-meniscectomy, yet the influence of varying knee geometries remains unknown. The present study aimed to fill that gap by employing statistical shape modeling to generate knee models from MRI data of 31 human knees, capturing the population's knee size and shape variations. Finite element simulations were conducted to replicate intact, partial, and total medial meniscectomy conditions during standing. The results revealed a substantial shift in load distribution from the medial to lateral compartment following medial meniscectomy with its magnitude depending on knee geometry. Cartilages experienced variable degrees of pressure changes at different sites, which could also be different for fluid and contact pressures. While changes in joint size led to somewhat predictable alterations in contact pressure, variations in joint shape resulted in unexpected changes in contact and fluid pressures, emphasizing the need for computational simulations. The average knee geometry exhibited the lowest contact and fluid pressures under the given loading and boundary conditions, in contrast to knees with shapes deviating from the average. This study highlights the significance of individual knee shape in the biomechanical outcome of meniscectomy, potentially explaining the variability in clinical outcomes observed post-surgery., Competing Interests: Declarations Competing interests The authors declare no competing interests. Ethical approval The use of MRI of human participants was approved by the University of Calgary, ethics ID#: REB15-1165. The MRI data used in the present study were obtained from the Osteoarthritis Initiative, https://nda.nih.gov/oai/. Dataset identifiers: 1200285; 1200816. No participant information is included in the manuscript., (© 2024. The Author(s).)
- Published
- 2024
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