A predictive mechano-biological model of the bone-implant healing

Abstract

The quality of the fixation orthopaedic implant to its surrounding bone determines its clinical longevity. Up to 20% of hip replacement operations are currently revisions for aseptic loosening. While this fixation quality is determined primarily by the bone and tissue anchoring the implant, conditions influencing bone growth in the early post-operative period include the surgical technique and coupled mechanical and biochemical factors. The aim of the study was to propose an original mechano-biological formulation of the healing process of periprosthetic tissue. The multiphasic porous model involved the solid osseous matrix, the extracellular fluid phase, the osteoblastic cellular phase responsible from the bone formation and the growth factor phase promoting the cellular activity. To derive the non-linear convective-diffuse governing equations, mass balance was associated to cell active haptotactic and chemotactic migration, growth factor diffusion, cell proliferation (logistic law) and bone formation (reactive medium). The in-vivo application concerned a canine axisymmetric implant which was stable and mechanically unloaded. Predictive numerical results were compared to ex-vivo data from a histologic study. The generic healing pattern involving two main oscillations of the radial bone formation was well predicted. In the future, the model could assist in evaluating the role of growth factor concentrations and their temporal delivering as far as the role of pertinent sources such as bioactive coating or additional biomaterials.

Bone ingrowth on the surface of endosseous implants. Part 1: Mathematical model

“…Although the interest of these works is unquestionable, it is the authors' opinion that mechanobiological models in which specific biological processes coupled with mechanics are modelled together with their influence on the structure and mechanical properties of tissues constitute a richer source of information for the understanding of many problems in biomedical sciences. However, it is a field where not many works exist, being possible to find only a few addressed 4 A c c e p t e d m a n u s c r i p t to the study of peri-implant endosseous healing (Geris et al, 2004;Andreykiv et al, 2005;Ambard and Swider, 2006;Liu and Niebur, 2007). We would like to remark that all these works consider in different depth several aspects of the biology of bone healing around implants, but they do not contemplate, or they do it in a superficial manner, the effect of the implant surface topography on biological processes.…”

In silicobiology of bone modelling and remodelling: regeneration

“…Based on the implant osseointegration experiments (Søballe 1993) that were used by Prendergast et al (1997) to develop their model, Ambard & Swider (2006) proposed a bioregulatory model of bone implant healing, where the migration of osteoblasts towards the implant surface is mediated both by the presence of an osteogenic growth factor and the local matrix density. Geris et al (2008a) started from the model of Bailón-Plaza & van der Meulen (2001) and introduced key aspects of healing such as angiogenesis and directed cell migration.…”

Wave front migration of endothelial cells in a bone-implant interface

“…With our canine experimental model, histological studies showed that several types of distribution patterns of neo-formed bone could be found, and all involved peaks in the drill-hole zone and at the implant surface (Vestermark et al, 2004;Ambard and Swider, 2006;Swider et al, 2010). Unfortunately, studies about the neo-vascularization and the activity of endothelial cells have not been carried out yet.…”

“…While some updating could be made with bony tissue (Ambard and Swider, 2006), convective and diffusive properties of vascular tissue were poorly known especially in bone neovascularization. This showed that mixed theoretical-experimental studies, in-vitro and in-vivo, could be planned to reinforce the model relevance.…”

“…The theory inspired by works in implant fixation (Ambard and Swider, 2006;Gué rin et al, 2009) and tumors angiogenesis (Anderson and Chaplain, 1998) was completed by source terms to take into account the proliferation and diffusive terms to enhance the prediction of growth factor migrations. It was applied to a canine experimental model and extended by a parametric sensitivity analysis.…”