Bone fracture healing under Ilizarov fixator: Influence of fixator configuration, fracture geometry, and loading

Abstract

This study aims to enhance the understanding of the relationship between Ilizarov fixator configuration and its effects on bone fracture healing. Using Taylor spatial frame (TSF) as an example, the roles of critical parameters (ie, TSF ring diameter, wire pre-tension, fracture gap size, and axial load) that govern fracture healing during the early stages were investigated by using computational modelling in conjunction with mechanical testing involving an advanced 3D optical measurement system. The computational model was first validated using the mechanical test results and then used to simulate mesenchymal stem cell (MSC) differentiations within different regions of the fracture site under various combinations of TSF ring diameter, wire pre-tension, fracture gap size, and axial load values. Predicted spatially dependent MSC differentiation patterns and the influence of each parameter on differentiations were compared with in vivo results, and good agreement was seen between the two. Gap size was identified as the most influential parameter in MSC differentiation, and the influence of axial loading and TSF configuration (ie, ring diameter and wire pre-tension) on cell differentiation was seen to be gap size dependent. Most changes in cell differentiation were predicted in the external callus (periosteal), which is the crucial region of the callus in the early stages.However, for small gap sizes (eg, 1 mm), significant changes were predicted in the endosteal callus as well. The study exhibits the potential of computational models in assessing the performance of Ilizarov fixators as well as assisting surgeons in patient-specific clinical treatment planning. KEYWORDS 3D optical measurement system, mechanical test, mechano-regulation, mesenchymal stem cell, Taylor spatial frame

Biohybrid Bovine Bone Matrix for Controlled Release of Mesenchymal Stem/Stromal Cell Lyosecretome: A Device for Bone Regeneration

“…Future studies can investigate bone fracture healing under the application of SBlyo under different bone fracture geometries and loading conditions. This can be facilitated using computational modeling and incorporation of advection/diffusion, cell proliferation, and differentiation into the model, as reported in [48,49].…”

A probabilistic approach for modelling bone fracture healing under Ilizarov circular fixator

“…Previous studies focusing on the very early stage of healing under ICF 35,36 have suggested that the fracture site mechanical microenvironment is more sensitive to fracture gap size (GS) than axial loading (P). Interestingly, the findings of this study suggest that the fracture site is more sensitive to P than GS at the beginning of stage III of secondary healing.…”

“…This requires systematic parametric investigations into fracture healing under controlled environments which can be achieved using validated computational models. However, most of the existing computational studies on fracture healing 8,25,[28][29][30][31][32][33] including those relevant to ICFs [34][35][36] have neglected the uncertainties associated with such factors and taken deterministic approaches.…”

The status and challenges of replicating the mechanical properties of connective tissues using additive manufacturing

“…Bone tissue implants need to have a similar stiffness to the surrounding bone, in order to avoid stress shielding and to improve bone regeneration (Ganadhiepan et al, 2019a;Ghimire et al, 2019;Miramini et al, 2018;Zhang¹ et al, 2013), yet they are frequently manufactured from stainless steel or titanium, which is much stiffer (Miramini et al, 2015). Many different studies have created FGBMs by varying the size of the lattice unit cell throughout the material to alter the stiffness of the scaffold in different locations (Mahbod and Asgari, 2019;Torres et al, 2016;Zhang et al, 2019).…”