Effect of ultrasound on bone fracture healing: A computational mechanobioregulatory model

Computational models of bone fracture healing and applications: a review

Fracture healing is a very complex physiological process involving multiple events at different temporal and spatial scales, such as cell migration and tissue differentiation, in which mechanical stimuli and biochemical factors assume key roles. With the continuous improvement of computer technology in recent years, computer models have provided excellent solutions for studying the complex process of bone healing. These models not only provide profound insights into the mechanisms of fracture healing, but also have important implications for clinical treatment strategies. In this review, we first provide an overview of research in the field of computational models of fracture healing based on CiteSpace software, followed by a summary of recent advances, and a discussion of the limitations of these models and future directions for improvement. Finally, we provide a systematic summary of the application of computational models of fracture healing in three areas: bone tissue engineering, fixator optimization and clinical treatment strategies. The application of computational models of bone healing in clinical treatment is immature, but an inevitable trend, and as these models become more refined, their role in guiding clinical treatment will become more prominent.

An explainable machine learning-based probabilistic framework for the design of scaffolds in bone tissue engineering

Recently, 3D-printed biodegradable scaffolds have shown great potential for bone repair in critical-size fractures. The differentiation of the cells on a scaffold is impacted among other factors by the surface deformation of the scaffold due to mechanical loading and the wall shear stresses imposed by the interstitial fluid flow. These factors are in turn significantly affected by the material properties, the geometry of the scaffold, as well as the loading and flow conditions. In this work, a numerical framework is proposed to study the influence of these factors on the expected osteochondral cell differentiation. The considered scaffold is rectangular with a 0/90 lay-down pattern and a four-layered strut made of polylactic acid with a 5% steel particle content. The distribution of the different types of cells on the scaffold surface is estimated through a scalar stimulus, calculated by using a mechanobioregulatory model. To reduce the simulation time for the computation of the stimulus, a probabilistic machine learning (ML)-based reduced-order model (ROM) is proposed. Then, a sensitivity analysis is performed using the Shapley additive explanations to examine the contribution of the various parameters to the framework stimulus predictions. In a final step, a multiobjective optimization procedure is implemented using genetic algorithms and the ROM, aiming to identify the material parameters and loading conditions that maximize the percentage of surface area populated by bone cells while minimizing the area corresponding to the other types of cells and the resorption condition. The results of the performed analysis highlight the potential of using ROMs for the scaffold design, by dramatically reducing the simulation time while enabling the efficient implementation of sensitivity analysis and optimization procedures.

BEM evaluation of surface octahedral strains and internal strain gradients in 3D-printed scaffolds used for bone tissue regeneration

Most of the mechnoregulatory computational models appearing so far in tissue engineering for bone healing predictions, utilize as regulators for cell differentiation mainly the octahedral volume strains and the interstitial fluid velocity calculated at any point of the fractured bone area and controlled by empirical constants concerning these two parameters. Other stimuli like the electrical and chemical signaling of bone constituents are covered by those two regulatory fields. It is apparent that the application of the same mechnoregulatory computational models for bone healing predictions in scaffold-aided regeneration is questionable since the material of a scaffold disturbs the signaling pathways developed in the environment of bone fracture. Thus, the goal of the present work is to evaluate numerically two fields developed in the body of two different compressed scaffolds, which seem to be proper for facilitating cell sensing and improving cell viability and cell seeding efficiency. These two fields concern the surface octahedral strains that the cells attached to the scaffold can experience and the internal strain gradients that create electrical pathways due to flexoelectric phenomenon. Both fields are evaluated with the aid of the Boundary Element Method (BEM), which is ideal for evaluating with high accuracy surface strains and stresses as well as strain gradients appearing throughout the analyzed elastic domain.