A musculoskeletal finite element model of rat knee joint for evaluating cartilage biomechanics during gait

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  • Gustavo A. Orozco
  • Kalle Karjalainen
  • Eng Kuan Moo
  • Stenroth, Lauri
  • Petri Tanska
  • Jaqueline Lourdes Rios
  • Teemu V. Tuomainen
  • Mikko J. Nissi
  • Hanna Isaksson
  • Walter Herzog
  • Rami K. Korhonen

Abnormal loading of the knee due to injuries or obesity is thought to contribute to the development of osteoarthritis (OA). Small animal models have been used for studying OA progression mechanisms. However, numerical models to study cartilage responses under dynamic loading in preclinical animal models have not been developed. Here we present a musculoskeletal finite element model of a rat knee joint to evaluate cartilage biomechanical responses during a gait cycle. The rat knee joint geometries were obtained from a 3-D MRI dataset and the boundary conditions regarding loading in the joint were extracted from a musculoskeletal model of the rat hindlimb. The fibril-reinforced poroelastic (FRPE) properties of the rat cartilage were derived from data of mechanical indentation tests. Our numerical results showed the relevance of simulating anatomical and locomotion characteristics in the rat knee joint for estimating tissue responses such as contact pressures, stresses, strains, and fluid pressures. We found that the contact pressure and maximum principal strain were virtually constant in the medial compartment whereas they showed the highest values at the beginning of the gait cycle in the lateral compartment. Furthermore, we found that the maximum principal stress increased during the stance phase of gait, with the greatest values at midstance. We anticipate that our approach serves as a first step towards investigating the effects of gait abnormalities on the adaptation and degeneration of rat knee joint tissues and could be used to evaluate biomechanically-driven mechanisms of the progression of OA as a consequence of joint injury or obesity.

Original languageEnglish
Article numbere1009398
JournalPLOS Computational Biology
Volume18
Issue number6
Pages (from-to)1-23
ISSN1553-734X
DOIs
Publication statusPublished - 2022

Bibliographical note

Publisher Copyright:
© 2022 Orozco et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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