Bone metastases occur in about 15% of all cancer cases. Pathological fractures that result from these tumours most frequently occur in the femur. It is extremely difficult to determine the fracture risk with the current X-ray methods, even for experienced physicians. The purpose of this study was to assess whether the use of a predictive finite element model could improve the prediction of strength in comparison to an clinical assessment. Eight human cadaver femora, with and without simulated metastases, were CT-scanned. A solid calibration phantom was included in each scan. From the scans, eight finite element (FE) models were generated using brick elements. The non-linear mechanical properties were based on bone density. After scanning, laboratory experiments were performed. The femora were loaded under compression until failure. During the experiments the failure forces and the course of failure were registered. These experiments were simulated in the FE-models, in which plastic deformation simulated failure of the bones. Six experienced physicians, were asked to rank the femora on strength using X-rays (AP and ML) and additional information on gender and age. The results showed a strong Pearson’s correlation (r2 = 0.92) between the experimental failure force and predicted failure force. The Spearman’s rank correlations between experiment and predictions ranged between ρ=0.58 and ρ=0.8 for the physicians, whereas it was significantly higher (ρ=0.92) for the FE-model This study showed that femur specific FE models better predicted femoral failure risk under axial loading than experienced physicians. When the model is further improved by adding, for example, other loading conditions, it can be clinically implemented to predict in vivo fracture risk for patients suffering, for example, bone metastases or osteoporosis.
