Model-Based Design to Enhance Neotissue Formation in Additively Manufactured Calcium-Phosphate-Based Scaffolds.

In biomaterial-based bone tissue engineering, optimizing scaffold structure and composition remains an active field of research. Additive manufacturing has enabled the production of custom designs in a variety of materials. This study aims to improve the design of calcium-phosphate-based additively manufactured scaffolds, the material of choice in oral bone regeneration, by using a combination of in silico and in vitro tools. Computer models are increasingly used to assist in design optimization by providing a rational way of merging different requirements into a single design. The starting point for this study was an in-house developed in silico model describing the in vitro formation of neotissue, i.e., cells and the extracellular matrix they produced. The level set method was applied to simulate the interface between the neotissue and the void space inside the scaffold pores. In order to calibrate the model, a custom disk-shaped scaffold was produced with prismatic canals of different geometries (circle, hexagon, square, triangle) and inner diameters (0.5 mm, 0.7 mm, 1 mm, 2 mm). The disks were produced with three biomaterials (hydroxyapatite, tricalcium phosphate, and a blend of both). After seeding with skeletal progenitor cells and a cell culture for up to 21 days, the extent of neotissue growth in the disks' canals was analyzed using fluorescence microscopy. The results clearly demonstrated that in the presence of calcium-phosphate-based materials, the curvature-based growth principle was maintained. Bayesian optimization was used to determine the model parameters for the different biomaterials used. Subsequently, the calibrated model was used to predict neotissue growth in a 3D gyroid structure. The predicted results were in line with the experimentally obtained ones, demonstrating the potential of the calibrated model to be used as a tool in the design and optimization of 3D-printed calcium-phosphate-based biomaterials for bone regeneration.

Coupling biomechanical models of implants with biodegradation models: A case study for biodegradable mandibular bone fixation plates.

In fracture fixation, biodegradable implant materials are an interesting alternative to conventional non-biodegradable materials as the latter often require a second implant removal surgery to avoid long-term complications. In this study, we present an in silico strategy to design/study biodegradable metal implants focusing on mandibular fracture fixation plates of WE43 (Mg alloy). The in silico strategy is composed of an orchestrated interaction between three separate computational models. The first model simulates the mass loss of the degradable implant based on the chemistry of Mg biodegradation. A second model estimates the loading on the jaw plate in the physiological environment, incorporating a phenomenological dynamic bone regeneration process. The third model characterizes the mechanical behavior of the jaw plate and the influence of material degradation on the mechanical behavior. A sensitivity analysis was performed on parameters related to choices regarding numerical implementation and parameter dependencies were implemented to guarantee robust and correct results. Different clinical scenarios were tested, related to the amount of screws used to fix the plate. The results showed a lower initial strength when more screw holes were left open, as well as a faster decrease over time in strength due to the increased area available for surface degradation. The obtained degradation results were found to be in accordance with previously reported data of in vivo studies with biodegradable plates. The combination of these three models allows for the design of patient-specific biodegradable fixation implants able to deliver the desired mechanical behavior tuned to the bone regeneration process.

Image-based flow simulation of platelet aggregates under different shear rates.

Hemodynamics is crucial for the activation and aggregation of platelets in response to flow-induced shear. In this paper, a novel image-based computational model simulating blood flow through and around platelet aggregates is presented. The microstructure of aggregates was captured by two different modalities of microscopy images of in vitro whole blood perfusion experiments in microfluidic chambers coated with collagen. One set of images captured the geometry of the aggregate outline, while the other employed platelet labelling to infer the internal density. The platelet aggregates were modelled as a porous medium, the permeability of which was calculated with the Kozeny-Carman equation. The computational model was subsequently applied to study hemodynamics inside and around the platelet aggregates. The blood flow velocity, shear stress and kinetic force exerted on the aggregates were investigated and compared under 800 s-1, 1600 s-1 and 4000 s-1 wall shear rates. The advection-diffusion balance of agonist transport inside the platelet aggregates was also evaluated by local Péclet number. The findings show that the transport of agonists is not only affected by the shear rate but also significantly influenced by the microstructure of the aggregates. Moreover, large kinetic forces were found at the transition zone from shell to core of the aggregates, which could contribute to identifying the boundary between the shell and the core. The shear rate and the rate of elongation flow were investigated as well. The results imply that the emerging shapes of aggregates are highly correlated to the shear rate and the rate of elongation. The framework provides a way to incorporate the internal microstructure of the aggregates into the computational model and yields a better understanding of the hemodynamics and physiology of platelet aggregates, hence laying the foundation for predicting aggregation and deformation under different flow conditions.

A computational analysis of the effect of supporting organs on predicted vesical pressure in stress urinary incontinence.

Stress urinary incontinence (SUI) or urine leakage from urethra occurs due to an increase in abdominal pressure resulting from stress like a cough or jumping height. SUI is more frequent among post-menopausal women. In the absence of bladder contraction, vesical pressure exceeds urethral pressure leading to urine leakage. The main aim of this study is to utilize fluid-structure interaction techniques to model bladder and urethra computationally under an external pressure like sneezing. Both models have been developed with linear elastic properties for the bladder wall while the patient model has also been simulated utilizing the Mooney-Rivlin solid model. The results show a good agreement between the clinical data and the predicted values of the computational models, specifically the pressure at the center of the bladder. There is 1.3% difference between the predicted vesical pressure and the vesical pressure obtained from urodynamic tests. It can be concluded that the accuracy of the predicted pressure in the center of the bladder is significantly higher for the simulation assuming nonlinear material property (hyperelastic) for the bladder in comparison to the accuracy of the linear elastic model. The model is beneficial for exploring treatment solutions for SUI disorder. Graphical abstract 3D processing of bladder deformation during abdominal pressure of a the physiological model and b the pathological model (starting from left to right and up to down, consecutively).