The effects of musculoskeletal loading regimes on numerical evaluations of acetabular component.

The importance of clinical studies notwithstanding, the failure assessment of implant-bone structure has alternatively been carried out using finite element analysis. However, the accuracy of the finite element predicted results is dependent on the applied loading and boundary conditions. Nevertheless, most finite element-based evaluations on acetabular component used a few selective load cases instead of the eight load cases representing the entire gait cycle. These in silico evaluations often suffer from limitations regarding the use of simplified musculoskeletal loading regimes. This study attempts to analyse the influence of three different loading regimes representing a gait cycle, on numerical evaluations of acetabular component. Patient-specific computer tomography scan-based models of intact and resurfaced pelvises were used. One such loading regime consisted of the second load case that corresponded to peak hip joint reaction force. Whereas the other loading regime consisted of the second and fifth load cases, which corresponded to peak hip joint reaction force and peak muscle forces, respectively. The third loading regime included all the eight load cases. Considerable deviations in peri-acetabular strains, standard error ranging between 115 and 400 µε, were observed for different loading regimes. The predicted bone strains were lower when selective loading regimes were used. Despite minor quantitative variations in bone density changes (less than 0.15 g cm(-3)), the final bone density pattern after bone remodelling was found to be similar for all the loading regimes. Underestimations in implant-bone micromotions (40-50 µm) were observed for selective loading regimes after bone remodelling. However, at immediate post-operative condition, such underestimations were found to be less (less than 5 µm). The predicted results highlight the importance of inclusion of eight load cases representing the gait cycle for in silico evaluations of resurfaced pelvis.