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Femoral strength is estimated in clinical routine from 2D Dual-energy X-rays Absorptiometry (DXA). In this study, a new pipeline for femoral strength prediction from DXA images is presented, using a 3D reconstruction method of the shape and the Bone Mineral Density (BMD) distribution and a regression analysis based on partial least squares. A database of 90 proximal femoral cadaveric specimens, that were previously imaged and tested to measure their fracture load, was used to develop and to validate the method. The proposed pipeline resulted in a correlation coefficient of 0.85 between predicted and measured fracture load, while a regression using 2D BMD measurements from DXA resulted in a correlation coefficient of 0.77. With an improved femoral strength prediction from DXA images, this method opens interesting translational perspectives in clinics for a better diagnosis of osteoporosis and fracture risk prediction.

The diagnosis of osteoporosis and the prevention of femur fractures is a major challenge for our society. However, the diagnosis performed in clinical routine from Dual Energy X-ray Absorptiometry (DXA) images is limited. This paper proposes a 3D reconstruction method of both the shape and the Bone Mineral Density (BMD) distribution of the proximal femur from routinely used DXA images. The reconstruction accuracy that can be obtained from single-view and multi-view DXA devices was assessed. This evaluation, from 20 bone specimens and simulated DXA images, highlighted a mean shape accuracy of 1.3mm and a BMD accuracy of 4.4% from a single-view DXA image. A multi-view configuration with 2 views (frontal-sagittal) appeared as a good compromise (mean shape accuracy of 0.9mm and BMD accuracy of 3.2%). We are currently using this method for in vivo clinical studies in order to improve the diagnosis of osteoporosis and the prevention of femur fractures.