Thu. May 19th, 2022

Biomechanical and inflammatory mechanisms implemented in computer models of knee joint degradation

image: For the first time, both biomechanical and inflammatory mechanisms were implemented in computer models of knee joint degradation.
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Credit: Atte Eskelinen and Gustavo A. Orozco.

Post-traumatic osteoarthritis is a disorder of the musculoskeletal system that particularly casts a shadow over the lives of a young and active population. Inhibition of the progression of cartilage damage with early intervention is essential. To predict how an intervention would affect the condition of an injured knee joint, knowledge of biomechanical and inflammatory aspects of osteoarthritis progression is necessary. For the first time, researchers have now captured both mechanisms in a physics-based computational model that predicts cartilage degradation and a possible recovery scenario after anterior cruciate ligament injury and reconstruction. The fruits of an international collaborative study (UEF, UCSF, CC, MIT) were recently published in the Journal of Orthopedic Research.

Rupture of the anterior cruciate ligament is a typical sports injury. An injured knee joint can be treated with ligament reconstruction aimed at restoring the joint environment to a healthy condition. However, this goal is not always achieved. Instead, the biomechanical load may be elevated locally and the arthritis can cause swelling and pain in the knee. Both of these mechanisms also promote the breakdown of articular cartilage located at the ends of bones, possibly leading to a crippling disease called osteoarthritis.

Currently, there is no cure for osteoarthritis. Thus, the prevention of disease progression is a prestigious goal that can only be achieved if the disease mechanisms are understood and their effects can be predicted. Insightful predictions open doors for designing new intervention strategies and evaluating their effectiveness. To tackle these challenges, researchers from the University of Eastern Finland (UEF), the University of California San Francisco (UCSF), the Cleveland Clinic (CC) and the Massachusetts Institute of Technology (MIT) are now reporting on a new workflow for predicting both biomechanical and first time the inflammation-related changes that occur in post-traumatic osteoarthritis.

The workflow consists of magnetic resonance imaging of ligament reconstructed patients, clinical gait analysis and subject-specific 3D calculation models that provide insight into time-dependent destructive changes in cartilage composition. By having access to the synovial fluid absorbed from the patient’s knee, the researchers were also able to include the clinical concentrations of inflammatory molecules in the calculation models.

“When we compared the model predictions with quantitative magnetic resonance images at 1- and 3-year follow-up times, we observed a striking similarity in sites of cartilage degeneration. In short, the biomechanical degradation due to tissue cutting occurred especially near chondral lesions, whereas the effect of inflammation was seen in broader areas, ”says the newspaper’s first author, postdoctoral researcher Gustavo Orozco, Ph.d.

“Interestingly enough, our model also predicts that if the inflammation could be stopped before it became chronic, restoration of the cartilage composition closer to healthy levels is possible. This scenario may be possible with rapid clearance of proinflammatory molecules as well as supplementation of the synovial fluid with drugs that prohibit excessive cytokine activation, ”adds the researcher at an early stage. Atte Eskelinen, Cand.mag.

The long-term goal is to develop a new generation of computational mechanical mechanobiological models that are able to predict the effects of both biomechanical and biochemical osteoarthritis progression mechanisms for several years to come. The new study is a milestone on that path and highlights the possibility of including both gait analysis and synovial fluid samples in predictable numerical models.

“Our computational approach could also be improved in the future to include various rehabilitation protocols, such as weight loss and anticatabolic drugs, to guide the decision-making of healthcare professionals with numerical predictions,” concludes researcher in early phase Joonas Kosonen, Cand.mag.

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The study has received support from the European Union’s Horizon 2020 research and innovation program under Marie Sklodowska-Curie Grant No. 713645. The study has also been funded by the Academy of Finland, strategic funding from the University of Eastern Finland, the Finnish Cultural Foundation, Instrumentarium Science Foundation, Swedish Research Council, Maire Lisko Foundation, Sigrid Jusélius Foundation, Päivikki and Sakari Sohlberg Foundation, Maud Kuistila Memorial Foundation, Saastamoinen Foundation, National Institutes of Health and American Orthopedic Society of Sports Medicine.


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