Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5891332 | Bone | 2013 | 12 Pages |
PurposeFemoral fracture is a common medical problem in osteoporotic individuals. Bone mineral density (BMD) is the gold standard measure to evaluate fracture risk in vivo. Quantitative computed tomography (QCT)-based homogenized voxel finite element (hvFE) models have been proved to be more accurate predictors of femoral strength than BMD by adding geometrical and material properties. The aim of this study was to evaluate the ability of hvFE models in predicting femoral stiffness, strength and failure location for a large number of pairs of human femora tested in two different loading scenarios.MethodsThirty-six pairs of femora were scanned with QCT and total proximal BMD and BMC were evaluated. For each pair, one femur was positioned in one-legged stance configuration (STANCE) and the other in a sideways configuration (SIDE). Nonlinear hvFE models were generated from QCT images by reproducing the same loading configurations imposed in the experiments. For experiments and models, the structural properties (stiffness and ultimate load), the failure location and the motion of the femoral head were computed and compared.ResultsIn both configurations, hvFE models predicted both stiffness (R2Â =Â 0.82 for STANCE and R2Â =Â 0.74 for SIDE) and femoral ultimate load (R2Â =Â 0.80 for STANCE and R2Â =Â 0.85 for SIDE) better than BMD and BMC. Moreover, the models predicted qualitatively well the failure location (66% of cases) and the motion of the femoral head.ConclusionsThe subject specific QCT-based nonlinear hvFE model cannot only predict femoral apparent mechanical properties better than densitometric measures, but can additionally provide useful qualitative information about failure location.
⺠We tested paired human femora in one-legged stance and sideways configurations. ⺠QCT-based FE models predicted femoral mechanical properties better than BMD and BMC. ⺠QCT-based FE models explained up to 85% of femoral strength. ⺠QCT-based FE models predicted qualitatively well the failure location. ⺠QCT-based FE models have been validated through accurate experiments.