Investigation of the Influence of Osteoporosis and Aging on Periprosthetic Femoral Fractures using Finite Element Analyses

Abstract

With the increasing life expectancy and more active lifestyles of patients, the number of total hip replacements is constantly rising. Consequently, the incidence of periprosthetic femoral fractures (PFF) is also growing and facilitated by osteoporosis as well as advancing age of the patient. One way to prevent PFF is to optimize the treatment of individual patients, who are potentially at risk of osteoporotic fractures, by choosing the most suitable implant design for their subject specific circumstances. Thereby, revision surgeries due to PFF can be avoided. In this context appropriate models are necessary to predict fractures for aging and osteoporotic bone. On the basis of quantitative computed tomography (QCT) data subject specific finite element models with a heterogeneous material definition were created that can simulate PFF via element deletion. Statistical studies on the changes of bone quality with increasing patient age and developing osteoporosis were incorporated into the models. With statistical data, the bone mineral density (BMD) values measured in the QCT scans of the modelled femurs were varied, while the individual heterogeneous density distribution was preserved. The new density values were mapped onto the FE meshes of the femurs. This way, the femur was modelled to mirror the condition of the bone in different age groups and with different severity levels of osteoporosis in high age. The final models incorporate the subject specific geometry and density distribution of a patient's femur as well as the statistical density values resulting from aging and osteoporosis. The FE analyses revealed that a statistical change of bone density with aging leads to a relative small decrease in fracture load for periprosthetic fractures of a femur with a cementless endoprosthesis. However, for osteoporosis, the fracture load can differ by up to 56% with a cementless endoprosthesis, depending on the severity level of the disease.