Abstract
Computational models can be used to evaluate the functional properties of knee joints and possible risk locations within joints. Current models with fibril-reinforced cartilage layers do not provide information about realistic human movement during walking. This study aimed to evaluate stresses and strains within a knee joint by implementing load data from a gait cycle in healthy and meniscectomised knee joint models with fibril-reinforced cartilages. A 3D finite element model of a knee joint with cartilages and menisci was created from magnetic resonance images. The gait cycle data from varying joint rotations, translations and axial forces were taken from experimental studies and implemented into the model. Cartilage layers were modelled as a fibril-reinforced poroviscoelastic material with the menisci considered as a transversely isotropic elastic material. In the normal knee joint model, relatively high maximum principal stresses were specifically predicted to occur in the medial condyle of the knee joint during the loading response. Bilateral meniscectomy increased stresses, strains and fluid pressures in cartilage on the lateral side, especially during the first 50% of the stance phase of the gait cycle. During the entire stance phase, the superficial collagen fibrils modulated stresses of cartilage, especially in the medial tibial cartilage. The present computational model with a gait cycle and fibril-reinforced biphasic cartilage revealed time- and location-dependent differences in stresses, strains and fluid pressures occurring in cartilage during walking. The lateral meniscus was observed to have a more significant role in distributing loads across the knee joint than the medial meniscus, suggesting that meniscectomy might initiate a post-traumatic process leading to osteoarthritis at the lateral compartment of the knee joint.
Acknowledgements
The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 281180. Financial support from the Academy of Finland (Grant 140730, 218038 and 138574), Kuopio University Hospital, Finland (EVO, 5041722), Jenny and Antti Wihuri Foundation, Strategic funding of the University of Eastern Finland and National Doctoral Programme of Musculoskeletal Disorders and Biomaterials, Finland, is also acknowledged. CSC – IT Center for Science, Finland is acknowledged for technical support.
Conflict of interest statement: The authors have no conflicts of interest.