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Biomech Model Mechanobiol. 2017 Jun;16(3):989-1000. doi: 10.1007/s10237-016-0866-2. Epub 2016 Dec 21.

Prediction of femoral strength using 3D finite element models reconstructed from DXA images: validation against experiments.

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Department of Biomedical Engineering, Lund University, BMC D13, 221 84, Lund, Sweden.
Department of Applied Physics, University of Eastern Finland, Kuopio, Finland.
Department of Orthopaedics, Traumatology and Hand Surgery, Kuopio University Hospital, Kuopio, Finland.
Division of Solid Mechanics, Lund University, Lund, Sweden.
Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland.
Department of Biomedical Engineering, Lund University, BMC D13, 221 84, Lund, Sweden.


Computed tomography (CT)-based finite element (FE) models may improve the current osteoporosis diagnostics and prediction of fracture risk by providing an estimate for femoral strength. However, the need for a CT scan, as opposed to the conventional use of dual-energy X-ray absorptiometry (DXA) for osteoporosis diagnostics, is considered a major obstacle. The 3D shape and bone mineral density (BMD) distribution of a femur can be reconstructed using a statistical shape and appearance model (SSAM) and the DXA image of the femur. Then, the reconstructed shape and BMD could be used to build FE models to predict bone strength. Since high accuracy is needed in all steps of the analysis, this study aimed at evaluating the ability of a 3D FE model built from one 2D DXA image to predict the strains and fracture load of human femora. Three cadaver femora were retrieved, for which experimental measurements from ex vivo mechanical tests were available. FE models were built using the SSAM-based reconstructions: using only the SSAM-reconstructed shape, only the SSAM-reconstructed BMD distribution, and the full SSAM-based reconstruction (including both shape and BMD distribution). When compared with experimental data, the SSAM-based models predicted accurately principal strains (coefficient of determination >0.83, normalized root-mean-square error <16%) and femoral strength (standard error of the estimate 1215 N). These results were only slightly inferior to those obtained with CT-based FE models, but with the considerable advantage of the models being built from DXA images. In summary, the results support the feasibility of SSAM-based models as a practical tool to introduce FE-based bone strength estimation in the current fracture risk diagnostics.


Finite element; Proximal femur; Statistical appearance model; Statistical shape model; Validation

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