RUM2021 RUM2021-EuroNorth
Osteoarthritis (OA) is the most common musculoskeletal joint disease, in which primarily the articular cartilage and subchondral bone are degenerated causing unbearable pain within a joint. OA affects more than 250 million people and places a huge financial burden on both the patient and the society.
Currently, preventing the onset and development of OA is still the best clinical course of action. FE modelling could be used to predict locations susceptible to osteoarthritis. To create patient-specific models, three inputs are required: geometry, motion and material property. The knee geometry can be obtained from clinical magnetic resonance imaging (MRI) via manual segmentation of the tissues of interest. The knee motion can either be measured using motion capture or, if such systems are not available, from literature. The material properties of the tissues can be obtained experimentally.
To use this approach in a clinical setting, or at least in studies with large number of subjects, the workflow should be improved. Here we develop a fast and reliable method of implementing patient-specific motion into computational models. Using this method, we identify OA risk areas in 7 patients with ACL reconstruction and 6 controls. Different degenerative mechanisms, such as excessive cartilage deformations, stresses and fluid velocity, were assessed. To verify the computational model reliability, the model predictions were compared against structural and compositional changes assessed using advanced MRI techniques.
The results showed that simplified and faster models yield similar results as more complex and computationally intensive approaches. Additionally, the locations susceptible to OA onset and progression predicted by these simplified models matched clinical follow-up information. This computational approach could be utilized to rapidly identify patients at risk of developing OA in a clinical setting and could reveal optimal and personalized rehabilitation and prevention protocols to prevent or delay the disease progression.
I invite you to watch the attached video for an overview of this topic.
