Probabilistic design strategy for improved Austin-Moore stem used in artificial cementless hip prosthesis considering material property uncertainty

Introduction. The use of probabilistic analysis is important when the input data are random, that leads to stochastic results. This paper describes the integration of a probabilistic design strategy of the solid and hollow stems implanted in a proximal femur in order to compare their advantages. The used hollow stem is called “Improved Austin-Moore” (IAM) model.

Materials and Methods. Probabilistic methods allow variations in factors which control the biomechanical effects of the implanted femur to be taken into account while determining its performance. Different material properties were generated randomly using Monte Carlo simulation (MCS). Monte Carlo sampling techniques were applied, and different von Mises stresses of the layers (bone and metal) were chosen as a performance indicator.

Results. A simple 2D implant-bone study of solid and IAM stem design was carried out with a high level of confidence, 99.87%, which corresponds to a target reliability index with regard to statistical uncertainties. The probabilistic design results show that the input and output parameters for the IAM stem are highly correlated relative to those for the solid stem.

Discussion and Conclusions. The sensitivity analysis shows that the input parameters for the IAM stem play a much larger part in the output parameters relative to the solid stem. The IAM stem is much more advantageous than the solid stem which causes an increase in the performance of the hip prosthesis.

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