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8th Combined Meeting Of Orthopaedic Research Societies (CORS)


Summary Statement

An MRI-derived subject-specific finite element model of a knee joint was loaded with subject-specific kinetic data to investigate stress and strain distribution in knee cartilage during the stance phase of gait in-vivo.


Finite element analysis (FEA) has been widely used to predict the local stress and strain distribution at the tibiofemoral joint to study the effects of ligament injury, meniscus injury and cartilage defects on soft tissue loading under different loading conditions. Previous studies have focused on static FEA of the tibiofemoral joint, with few attempts to conduct subject-specific FEA on the knee during physical activity. In one FEA study utilising subject-specific loading during gait, the knee was simplified by using linear springs to represent ligaments. To address the gap that no studies have performed subject-specific FEA at the tibiofemoral joint with detailed structures, the present study aims to develop a highly detailed subject-specific FE model of knee joint to precisely simulate the stress distribution at knee cartilage during the stance phase of the gait cycle.


A detailed three-dimensional model of a healthy human knee was developed from MRI images of a living subject, including the main anatomical structures (bones, all principal ligaments, menisci and articular cartilages). The femur, tibia and fibula were considered as rigid bodies, while the menisci and articular cartilage were modelled as linearly elastic, isotropic and homogeneous while the ligaments were considered to be hyperelastic. Loading and boundary condition assignment was based on the kinematic and kinetic data recorded during gait analysis. Ten time intervals during the stance phase of gait were separately simulated to quantify the time–dependent stress distribution throughout the cycle from heel-strike to toe-off. Loading condition of the tibiofemoral joint varys during the gait cycle since the joint angle changes from extension to flextion, therefore different joint angles at relative time interval were determined to accurately simulate the varing loading condition.


The compressive stress and tensile strain distributions in the femoral cartilage, tibia cartilage and menisci of each selected time interval during the stance phase of gait cycle were quantified and corresponded to specific amount of varus/valgus knee moment obtained by inverse dynamics analysis of the kinematic and kinetic data from gait analysis. Therefore a correlation between stress/strain and the frontal movement was established and analysed. For example, at 10% of stance phase, the stress concentration was observed on the lateral compartment due to the valgus moment created at heel strike. At the next interval, the stress concentration shifted to the medial side as the frontal knee moment shifted to a varus orientation.


The results suggest that the stress distribution of tibiofemoral articular cartilage is qualitatively consistent with the valgus and varus moment observed during the stance phase of gait. The methods described could be applied to investigate the effects of injury and reconstruction on stress distribution within the tibiofemoral joint.