Osteoporotic fractures are a major clinical problem and current diagnostic tools have an accuracy of only 50%. The standard clinical assessment of Osteoporosis is based on an exam called dual energy X-rays absorptiometry (DXA) with which the local areal bone mineral density is measured at the hip. However, this investigation has been found to be, in some cases, a poor predictor of bone strength and therefore we need to improve current diagnostic methods in order to potentially improve the prediction of fracture risk. One possibility is provided by the finite element (FE) method, a mathematical model that estimates the bone strength from medical images. The FE method has been applied by several researchers to three-dimensional (3D) images like the ones obtained from quantitative computed tomography (QCT), a technique that can acquire the 3D geometry and density distribution of the bone but that has limitation of high radiation dose to the patient. In Sheffield we developed over the years a DXA-based FE analyses that can estimate the bone strength from two-dimensional (2D) DXA images. However, before applications in clinical studies, we need to understand how much to trust such models by comparing their predictions with results accurately measured in the laboratory (i.e. validate the models). The aim of this study was to validate DXA)-based finite element (FE) models to predict femoral strength in two loading configurations. We collected thirty-six pairs of fresh frozen human proximal femora that were scanned with DXA and QCT. Each pair one femurs was tested until failure in the laboratory in two loading configurations. Subject-specific 2D DXA-based linear FE models and 3D QCT-based nonlinear FE models were generated for each specimen and used to predict the measured femoral strength. The outcomes of the models were compared to standard DXA-based areal bone mineral density (aBMD) measurements. We found that the DXA-based FE models are a good predictor of femoral strength as compared with experimental data ex vivo, with ability to predict femoral strength in between the aBMD and the more complex 3D QCT-based models. However, it remains to be investigated whether this novel approach can provide good predictions of the risk of fracture in vivo.
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