MicroCT-based finite element models as a tool for virtual testing of cortical bone.

The aim of this study was to assess a virtual biomechanics testing approach purely based on microcomputed tomography (microCT or µCT) data, providing non-invasive methods for determining the stiffness and strength of cortical bone. Mouse femurs were µCT scanned prior to three-point-bend tests. Then microCT-based finite element models were generated with spatial variation in bone elastoplastic properties and subject-specific femur geometries. Empirical relationships of density versus Young's moduli and yield stress were used in assigning elastoplastic properties to each voxel. The microCT-based finite element modeling (µFEM) results were employed to investigate the model's accuracy through comparison with experimental tests. The correspondence of elastic stiffness and strength from the µFE analyses and tests was good. The interpretation of the derived data showed a 6.1%, 1.4%, 1.5%, and 1.6% difference between the experimental test result and µFEM output on global stiffness, nominal Young's modulus, nominal yield stress, and yield force, respectively. We conclude that virtual testing outputs could be used to predict global elastic-plastic properties and may reduce the cost, time, and number of test specimens in performing physical experiments.