Use of a genetic algorithm for multiobjective design optimization of the femoral stem of a cemented total hip arthroplasty.

There are many designs of the femoral stem of a cemented total hip arthroplasty, and mechanical failure of the stem is caused by several factors related to the cement, such as failure of the cement. Optimization of the shape of the stem, especially multiobjective optimization, is required to solve these design problems because a cement fracture is caused by multiple factors. The objective of this study was to determine a stem geometry considering multiple factors at the same time. A three-dimensional finite element model of the proximal femur was developed from a composite femur. A total of four objective functions--two objective functions, the largest maximum principal stress of proximal and distal sections in the cement mantle, for each of the two boundary conditions, walking and stair climbing--were used. The neighborhood cultivation genetic algorithm was introduced to minimize these objective functions. The results showed that the geometry that leads to a decrease in the proximal cement stress and the geometry that leads to a decrease in the distal cement stress were not the same. However, the results of the walking and the stair climbing conditions matched. Five dominant stem designs were considered to be the Pareto solution, and one design was identified as the "better design" for all objective functions. It was shown that multiobjective optimization using a genetic algorithm may be used for optimizing the shape of the femoral stem in order to avoid cement fracture.