Analysis of strength and failure pattern of human proximal femur using quantitative computed tomography (QCT)-based finite element method.

This paper presents a novel method for fast and reliable prediction of the failure strength of human proximal femur, using the quantitative computed tomography (QCT)-based linear finite element analysis (FEA). Ten fresh frozen human femora (age: 34±16) were QCT-scanned and the pertinent 3D voxel-based finite element models were constructed. A specially-designed holding frame was used to define and maintain a unique geometrical reference system for both FEA and in-vitro mechanical testing. The analyses and tests were carried out at 8 different loading orientations. A new scheme was developed for assortment of the element risk factor (defined as the ratio of the strain energy density to the yield strain energy for each element) and implemented for the prediction of the failure strength. The predicted and observed failure patterns were in correspondence, and the FEA predictions of the failure loads were in very good agreement with the experimental results (R2=0.86, slope=0.96, p<0.01). The average computational time was 5 min (on a regular desktop personal computer) for an average element number of 197,000. Noting that the run-time for a similar nonlinear model is about 8h, it was concluded that the proposed linear scheme is overwhelmingly efficient in terms of computational costs. Thus, it can efficiently be used to predict the femoral failure strength with the same accuracy of similar nonlinear models.