Non-invasive prediction of the mouse tibia mechanical properties from microCT images: comparison between different finite element models

Abstract

New treatments for bone diseases require testing in animal models before clinical translation, and the mouse tibia is among the most common models. In vivo micro-Computed Tomography (microCT)-based micro-Finite Element (microFE) models can be used for predicting the bone strength non-invasively, after proper validation against experimental data. Different modelling techniques can be used to estimate the bone properties, and the accuracy associated with each is unclear. The aim of this study was to evaluate the ability of different microCT-based microFE models to predict the mechanical properties of the mouse tibia under compressive load. Twenty tibiae were microCT scanned at 10.4 µm voxel size and subsequently compressed at 0.03 mm/s until failure. Stiffness and failure load were measured from the load–displacement curves. Different microFE models were generated from each microCT image, with hexahedral or tetrahedral mesh, and homogeneous or heterogeneous material properties. Prediction accuracy was comparable among models. The best correlations between experimental and predicted mechanical properties, as well as lower errors, were obtained for hexahedral models with homogeneous material properties. Experimental stiffness and predicted stiffness were reasonably well correlated (R2 = 0.53–0.65, average error of 13–17%). A lower correlation was found for failure load (R2 = 0.21–0.48, average error of 9–15%). Experimental and predicted mechanical properties normalized by the total bone mass were strongly correlated (R2 = 0.75–0.80 for stiffness, R2 = 0.55–0.81 for failure load). In conclusion, hexahedral models with homogeneous material properties based on in vivo microCT images were shown to best predict the mechanical properties of the mouse tibia.

The Role of the Loading Condition in Predictions of Bone Adaptation in a Mouse Tibial Loading Model

“…The use of heterogeneous material properties would help to understand the role of TMD changes in strain distribution, but would alter the strain profile especially in the trabecular regions (Webster et al, 2012). However, this was not conducted due to the small increment to predictions of structural failure in the murine caudal vertebra (Webster et al, 2012) and mouse tibia (Oliviero et al, 2021b) at the expense of a large computational cost. Although the use of tetrahedral mesh would capture the strain distribution at the surface more smoothly in principle (Cheong et al, 2020a,b), both hexahedral and tetrahedral models of the mouse tibia were found to yield similar results in stiffness, failure load and local strain distributions in the cortical bone (Oliviero et al, 2021b).…”

“…However, this was not conducted due to the small increment to predictions of structural failure in the murine caudal vertebra (Webster et al, 2012) and mouse tibia (Oliviero et al, 2021b) at the expense of a large computational cost. Although the use of tetrahedral mesh would capture the strain distribution at the surface more smoothly in principle (Cheong et al, 2020a,b), both hexahedral and tetrahedral models of the mouse tibia were found to yield similar results in stiffness, failure load and local strain distributions in the cortical bone (Oliviero et al, 2021b). Moreover, simple loading was applied to quantify the changes to the micromechanical properties, rather than determine the mechanical environment induced by the loading.…”

Combining PTH(1-34) and mechanical loading has increased benefit to tibia bone mechanics in ovariectomised mice

“…A connectivity lter (connectivity rule = 6, bwlabeln function in Matlab) was used to remove from the binary image the unconnected bone islands and the connected bone voxels were converted into 8-node hexahedral elements. Bone was considered homogenous, isotropic, and linear elastic, with a modulus of elasticity of 14.8GPa, and Poisson's ratio of 0.3 14,30 . Uniaxial compression was applied by xing the nodes of the most distal section of the model and by applying an axial displacement equal to 0.1mm at the proximal end.…”

“…The 10% of the total tibia length was excluded from this analysis at each extremity of the model to reduce the boundary effects. These models have been recently validated against state-of-the-art experiments for the prediction of local deformation and structural properties 14,30 . The resulting linear microFE models were solved (Ansys, Release 15.0, ANSYS, Inc.) on a high-performance computing (HPC) system (ShARC, University of She eld; 8 cores, memory = 32GB/core) in approximately 30 minutes.…”

“…three-/four-point bending) 13 , the destructive nature of these tests prohibits monitoring of biomechanical changes in a single animal over time, and thus are limited to studies of cross-sectional design. Recently, micro-computed tomography (microCT)-based micro-nite element (microFE) models of the mouse tibia were developed and validated against experimental data 14,15 . These models are useful to non-invasively evaluate the longitudinal mechanical behaviour of the mouse bone 16,17 .…”