A computerized pre-clinical test for cemented hip prostheses based on finite element techniques

Despite the success of cemented total hip replacement (THR), high failure rates are occasionally reported for cemented hip implants that are introduced on the orthopaedic market. Rigorous pre-clinical testing of hip implants could prevent these disasters, by detecting unsafe implant designs at a pre-clinical stage. The failure risk of the implant should be assessed, by testing against the most dominant failure scenarios for cemented reconstructions. At present no dependable pre-clinical tests exist. Failure of the femoral component in THR is often believed to related to the damage accumulation failure scenario. According to this scenario, repetitive loading of the reconstruction produces creep and microcrack accumulation in the cement and along the interfaces. This leads to implant migration, peri-prosthetic osteolysis, and to gross loosening of the implant. This thesis is aimed at developing a validated pre-clinical test for cemented hip prostheses against this failure scenario, based on computer finite element (FEA) simulation. An extensive description is given of the FEA simulation developed to simulate the mechanical failure processes involved: creep and microcrack accumulation in the cement. The FEA tool can be used to predict cement crack formation and implant migration, when applied to models of cemented THR reconstructions. Research is performed to determine the loading conditions in the pre-clinical test. It is found that the loading configuration should include a hip joint force and an additional set of abductor forces. The forces should represent not only walking, but also stair climbing, as this latter task is shown to be more critical for failure in cemented THR. Finally, the thesis describes the successful validation of the FEA-based pre-clinical test, relative to the results of experimental fatigue tests on cemented THR reconstructions and relative to clinical survival data. For the first time, an FEA simulation is able to detect inferior implants, based on accurate predictions of the failure mechanisms occurring in real reconstruction