Obtaining physiological loading conditions of joints in-vivo can be challenging. An invasive method to measure such loads are instrumented prostheses, but also, the bone microstructure, which can be measured non-invasively, contains information on the physiological loads. The loads are “imprinted” by bone (re)modeling and can be predicted using inverse bone remodeling (IBR). In brief, IBR uses finite-element (FE) models and scales applied unit loads such that the tissue is loaded homogeneously. It was shown to predict peak joint loads in agreement with measurements of instrumented prostheses at the proximal femur. Yet, IBR requires high-resolution CT scans, which are often unavailable in a clinical scenario. To overcome the requirement for fully depicting the microstructure and reducing the computational costs, we recently adapted IBR to utilize homogenized-FE models instead of micro-FE. The objective of this study was to test the viability of IBR with clinically feasible homogenized-FE models to predict in-vivo hip joint loading.

The peak joint loads were predicted for 19 proximal femora using homogenized-FE models. Trabecular and cortical bone was modeled separately using a density-dependent material. Four unit loads of 1kN each were applied at the femoral head, coplanar to the frontal plane, at -20°, 20°, 60°, and 100°.

The predicted peak angle was 20° in 18 of 19 samples, and the average peak magnitude was 3.23kN±0.5kN. The predicted angles and magnitudes were similar to those previously presented in literature using micro-FE-based IBR (20°, 3.37kN±0.6kN) or instrumented prostheses (18.2°±2.0°, 2.7kN±0.4kN). The average solving time was reduced from 497 CPU-hours (micro-FE) to just 50 CPU-seconds (homogenized-FE).

These preliminary results show, that IBR can be used with homogenized models to predict physiological peak joint loads. However, the FE models were created from micro-CT data. Thus, it still has to be investigated if real clinical CT data can be used similarly.

In the following study, predictive capabilities of the mean-field cluster model [1,2] in accounting for the space distribution of inclusions in two-phase particulate composites are demonstrated. In particular, the case of multiple families of inclusions is addressed. The analysis is performed for the linear and nonlinear regime (elastic-plastic or elastic-viscoplastic).
For the inelastic regime, the incremental linearization of elasto-plastic law or the additive tangent interaction law for elastic-viscoplastic case are used to adopt the scheme for non-linear material behaviour. The formulated micromechanical scheme is implemented and verified with respect to the results of numerical homogenization using the finite element method.
Representative volume elements (RVE) containing multiple inclusions, arranged in regular or random patterns, and subjected to periodic boundary conditions are considered. Predictive capabilities of the method are verified as concerns estimation of the overall response, as well as the mean stress and mean strain within each inclusion in the RVE. The possibility of using the tool in the material morphology optimization is assessed.

[1] A. Molinari and M. El Mouden. Int. J. Solids Struct., 33:3131–3150, 1996.

[2] K. Kowalczyk-Gajewska, M. Majewski, S. Mercier and A. Molinari. Int. J. Solids
Struct., 224:111040, 2021.

Tissue engineering and regenerative medicine are promising biomedical approaches to regenerate severe bone defects, caused by trauma, diseases or prolonged physical activities. Scaffold structures support seeded cells and should provide an optimal environment for cell growth. Computational fluid dynamics (CFD) simulations are a key component to investigate the influence of the scaffold structure on flow characteristics and mass transfer. Wall shear stresses (WSS) are of specific interest. The aim of this work is to optimize sinusoidal scaffold structures to improve and optimize cell proliferation and cell nutrition conditions. The scaffolds are computationally created and meshed using SALOME®, while the CFD simulations are carried out using the open‑source CFD toolbox OpenFOAM®. A diffusive‑advective mass transport equation is solved on a laminar flow field using the solver scalarTranportFoam for the evaluation of the nutrient distribution of the scaffolds. The fluid flow is described by the three‑dimensional Navier-Stokes equations. CFD results are validated via µ-particle image velocimetry (µPIV) measurements using scaffolds that are printed into a microchannel using the Two-Photon polymerization technique. The numerical results indicate that both increased frequency and amplitude of the sinusoidal channel regions lead to a velocity decrease inside the sinus regions and vortex formation at high frequencies. µ-PIV measurements confirm that the CFD simulations predict vortex formation and WSS as a function of flow rate with reasonable accuracy, which also allows to predict influence on mass transport. These results confirm the potential of CFD for design and evaluation of optimized scaffold structures. Geometric variations can be easily pre‑evaluated and optimized before printing the scaffolds for experimental evaluation. This integrated computational and experimental design loop is important because minor changes in the flow field, especially near the walls, can directly affect the cell bioactivity.

Biodentine is made of calcium silicate, calcium carbonate, zirconium dioxide, and water. It is used for dental replacement. It significantly outperforms the stiffness and hardness of construction cement pastes, which are chemically similar. We here report a comprehensive investiagation on the multiscale mechanics of Biodentine, combining grid nanoindentation, ultrasonic testing, statistics-informed micromechanical modeling. The key to the superior properties of Biodentine is a highly dense, calcite-reinforced hydrate phase, with surprisingly unifrom load levels, underlining the high level of optimization of the material.

References:

Dohnalik et al, Mech Adv Mat Str, DOI: 10.1080/15376494.2022.2073493, 2022

Dohnalik et al., J Mech Beh Biomed Mat 124, 104863, 2021

Collagen is the most abundant protein in human body. At the nanoscale, collagen forms collagen fibrils (CF) with diameters between 50-500 nm. CFs show time-dependent material behavior, which suggests they are also viscoelastic. Current available tools and methods are not able to measure viscoelastic material properties in a reproducible manner. Here, we present methods to perform force-controlled creep as well dynamic nano-mechanical analysis (DMA) in tension. The method is applied to individual CFs and electrospun PLLA nanofibers (PLLAs). Electrospinning is an emerging technique for fabrication of nanofibrous biomaterials similar to CFs of musculoskeletal tissues [1, 2].

We conducted creep experiments on CFs from and mouse tail tendon collagen fibrils and nano DMA experiments on obth CFs and electrospun PLLAs. Both experiments are facilitated through a recently developed instrument then NanoTens, for testing of nano- and microscale fibers with quick coupling and uncoupling [3].

In creep experiments we show that the transient behaviour at medium strains can be empirically described using a linear Burgers model in Kelvin-Voigt configuration. Here elastic elements exhibit moduli in the range of 0.2-10 GPa and viscous elements exhibit viscosities in the range of 10²-10⁴ MPa.s for the dashpot within the Kelvin-Voigt body and 10³-10⁶ MPa.s for the dashpot in series.

In nano DMA experiments We observe similar elastic behavior in monotonic tensile tests and elastic response in nanoDMA for CFs and PLLAs. However, the loss modulus and tangent of PLLAs is significantly higher compared to CFs. This warrants room for further optimization of PLLA material properties.

In conclusion, the the NanoTens opens the door for assessing the time-dependent properties of indivudal CFs and thus to establish a unified constitutive CF model.

1. Sensini and Cristofolini, Materials, 11(10), 2018.

2. Sensini et al., Front.Bioeng.Biotech. 2(9), 2021.

3. Nalbach et al., Rev. Sci. Instrum., 2022. Rev.Sci.Instrum. 93 2022