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Osteoporos Int. 2006;17(6):855-64. Epub 2006 Mar 18.

Volumetric quantitative computed tomography of the proximal femur: relationships linking geometric and densitometric variables to bone strength. Role for compact bone.

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Service de Radiologie Ostéo-Articulaire, Hôpital Lariboisière, 2, rue Ambroise Paré, 75010, Paris, France, and Institute of Medical Physics, University of Erlangen, Germany.



In assessing cervical fractures of the proximal femur, this in vitro quantitative computed tomography (QCT) study had three objectives: to compare QCT to dual-energy X-ray absorptiometry (DXA) for predicting the failure load of the proximal femur, to compare the contributions of density and geometry to bone failure load, and to compare the contributions of cortical and trabecular bone to bone failure load. A novel three-dimensional (3D) analysis tool [medical image analysis framework (MIAF-Femur)] was used to analyze QCT scans.


The proximal ends of 28 excised femurs were studied (1) using QCT to separately measure bone mineral density (BMD) and geometric variables of trabecular and cortical bone, (2) using mechanical tests to failure in a stance configuration, and (3) using DXA to measure BMD. The variables were described with mean, standard deviation, and range. Correlation matrix and multivariate linear models were computed.


Among correlations, cortical thicknesses of the femoral neck were significantly correlated with femoral failure load, especially of the inferoanterior quadrant (r2=0.41; p<0.001), as was cortical volume at the "extended neck" (r2=0.41; p<0.001). Femoral failure load variance was best explained by a combination of QCT variables. Combining densitometric and geometric variables measured by QCT explained 76% of femoral failure load variance compared with 69% with the DXA model. Geometric variables (measured by QCT) explained 43% of femoral failure load variance compared with 72% for densitometric variables (measured by QCT). A model including only trabecular variables explained 52% of femoral failure load variance compared with 59% for a model including only cortical variables.


The QCT-MIAF reported here provides analysis of both geometric and densitometric variables characterizing cortical and trabecular bone. Confirmation of our results in an independent sample would suggest that QCT may better explain failure load variance for cervical fracture than the gold standard DXA-provided BMD.

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