Abstract
Introduction
Unicompartmental Knee Replacement Arthroplasty (UKA) is a treatment option for early knee OA that appears under-utilised, partly because of a lack of clear guidance on how to best restore lasting knee function using such devices. Computational tools can help consider inherent uncertainty in patient anatomy, implant positioning and loading when predicting the performance of any implant. In the present research an approach for creating patient-specific finite element models (FEM) incorporating joint and muscle loads was developed to assess the response of the underlying bone to UKA implantation.
Methods
As a basis for future uncertainty modelling of UKA performance, the geometriesof 173 lower limbs weregenerated from clinical CT scans. These were segmented (ScanIP, Simpleware Ltd, UK) to reconstruct the 3D surfaces of the femur, tibia, patella and fibula. The appropriate UKA prosthesis (DePuy, U.S.) size was automatically selected according to tibial plateau size and virtually positioned (Figure 1). Boolean operations and mesh generation were accomplished with ScanIP.
A patient-specific musculoskeletal model was generated in open-source software OpenSim (Delp et al. 2007) based on the Gait2392 model. The model was scaled to a specific size and muscle insertion points were modified to corresponding points on lower limb of patient. Hip joint load, muscle forces and lower limb posture during gait cycle were calculated from the musculoskeletal model. The FE meshes of lower limb bones were transformed to the corresponding posture at each time point of a gait cycle and FE analyses were performed (Ansys, Inc. U.S) to evaluate the strain distribution on the tibial plateau in the implanted condition.
Results
With the tibial component positioned above, along or below the joint line, the lower limb alignment was more varus, remained unaltered or more valgus respectively (Figure 2). With the tibial component positioned 3mm above the joint line, the peak strain in the underlying bone was 670 µstrain on medial (UKA) side and 6780 µstrain on the intact side. With the tibial component positioned 3mm below the joint line, the peak strain was 3010 µstrain on the medial side and 5330 µstrain on the intact side. Here, the strains on the medial side increased by 2640 µstrain whilst they were reduced by 1450 µstrain on the intact side compared to the unimplanted case.
Conclusion
The present research has delivered a framework which can be exploited in future uncertainty modelling of UKA performance predictions. The patient-specific model incorporates loading, anatomical and material property variability, and can be applied to evaluate the performance of UKA prostheses for metrics such as stress/strain/micromotions in larger patient populations.
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