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Updated: Oct 19, 2025

Proximal Cadaveric Femur Preparation for Fracture Strength Testing and Quantitative CT-based Finite Element Analysis
Published on: March 11, 2017
Influence of loading conditions in finite element analysis assessed by HR-pQCT on ex vivo fracture prediction
M Revel1, F Bermond2, F Duboeuf3
1Univ Lyon, Univ Claude Bernard Lyon 1, INSERM, LYOS UMR1033, F69008 Lyon, France; Univ Lyon, Univ Gustave Eiffel, Univ Claude Bernard Lyon 1, LBMC UMR_T9406, F69622 Lyon, France.
Abstract:
Many fractures occur in individuals with normal areal Bone Mineral Density (aBMD) measured by Dual X-ray Absorptiometry (DXA). High Resolution peripheral Quantitative Computed Tomography (HR-pQCT) allows for non-invasive evaluation of bone stiffness and strength through micro finite element (μFE) analysis at the tibia and radius. These μFE outcomes are strongly associated with fragility fractures but do not provide clear enhancement compared with DXA measurements. The objective of this study was to establish whether a change in loading conditions in standard μFE analysis assessed by HR-pQCT enhance the discrimination of low-trauma fractured radii (n = 11) from non-fractured radii (n = 16) obtained experimentally throughout a mechanical test reproducing a forward fall. Micro finite element models were created using HR-pQCT images, and linear analyses were performed using four different types of loading conditions (axial, non-axial with two orientations and torsion). No significant differences were found between the failure load assessed with the axial and non-axial models. The different loading conditions tested presented the same area under the receiver operating characteristic (ROC) curves of 0.79 when classifying radius fractures with an accuracy of 81.5%. In comparison, the area under the curve (AUC) is 0.77 from DXA-derived ultra-distal aBMD of the forearm with an accuracy of 85.2%. These results suggest that the restricted HR-pQCT scanned region seems not sensitive to loading conditions for the prediction of radius fracture risk based on ex vivo experiments (n = 27).
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