Separate modeling of cortical and trabecular bone offers little improvement in FE predictions of local structural stiffness at the proximal tibia

Influence of loading conditions in finite element analysis assessed by HR-pQCT on ex vivo fracture prediction

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).

Risk assessment of resurfacing implant loosening and femur fracture under low-energy impacts taking into account degenerative changes in bone tissues. Computer simulation

BACKGROUND AND OBJECTIVE

Degenerative diseases of the musculoskeletal system significantly reduce the quality of human life. Hip resurfacing is used to treat degenerative diseases in the later stages. After surgery, there is a risk of endoprosthesis loosening and low-energy fracture during daily physical activity. Computer modeling is a promising way to predict the optimal low-energy loads that do not lead to bone destruction. This paper aims to study numerically the mechanical behavior of the proximal femur, amenable to degenerative changes and subjected to hip resurfacing under low-energy impact equivalent to physiological loads.

METHODS

A numerical model of the mechanical behavior of the femur after hip resurfacing arthroplasty under low-energy impacts equivalent to physiological loads is presented. The model is based on the movable cellular automaton method (discrete elements), where the mechanical behavior of bone tissue is described using the Biot poroelasticity accounting for the presence and transfer of interstitial biological fluid.

RESULTS

For the first time, it is shown that a poroelastic model allows predicting the service life of endoprostheses, taking into account the individual characteristics of the bone tissues amenable to various degenerative diseases. The obtained results indicate that the changes in the bone properties have a significant influence on the critical forces corresponding to the first appearance of microcracks and the fracture formation. At the same time, their effect on the type of fracture is negligible. A much more impact on the type of fracture has the kinematic and dynamic conditions of the exposure.

CONCLUSIONS

The obtained results show the promise of using the proposed model for predicting the operational resource of resurfacing endoprostheses, taking into account the physiological features of the structure of the patient's bone tissues.

QCT-FE modeling of the proximal tibia: Effect of mapping strategy on convergence time and model accuracy

Quantitative computed tomography (QCT) based finite element (FE) modeling, referred to as QCT-FE, has seen rapid growth and application for modeling bone mechanics. With this approach, varying bone material properties are set via experimentally-derived density-modulus equations. One challenge though associated with QCT-FE is to identify the appropriate mapping strategy for assigning elastic moduli to elements. The goal of this study was to evaluate different QCT-FE mapping strategies to identify the optimum approach with fastest convergence rate and highest accuracy. Four proximal tibial medial compartments were imaged using QCT and experimentally tested to characterize proximal tibial subchondral bone stiffness at four surface points, resulting in a total of 16 indentation measures. Three material mapping methods were analyzed: (1) constant-E where an average elastic modulus was assigned to each element; (2) node-based where the material properties were first mapped on nodes then interpolated to Gaussian integration points; and (3) element-based in which the material properties were directly assigned to Gaussian integration points. Different element sizes were assessed with edge-lengths ranging from 0.9 to 3 mm. Results indicated that all converged models showed similar coefficient-of-determination (R²) and normalized root-mean-square errors (RMSE%). Though, the constant-E and node-based methods converged with the element edge-length of 1.5 mm (prediction error of 4.8% and 2.5%, respectively) whereas the element-based method converged with a larger element having an edge-length 2.5 mm (error = 4.9%). In conclusion, the element-based method, with a larger element size, resulted in similar predictive accuracy, faster convergence and shorter run-times relative to the constant-E and node-based approaches. As such, we recommend the element-based method for future subject-specific QCT-FE modeling.