Current views on calcium phosphate osteogenicity and the translation into effective bone regeneration strategies.
; Carlier, Aurélie ; et al
in Acta Biomaterialia (2012), 8(11), 3876-87
Calcium phosphate (CaP) has traditionally been used for the repair of bone defects because of its strong resemblance to the inorganic phase of bone matrix. Nowadays, a variety of natural or synthetic CaP ... [more ▼]
Calcium phosphate (CaP) has traditionally been used for the repair of bone defects because of its strong resemblance to the inorganic phase of bone matrix. Nowadays, a variety of natural or synthetic CaP-based biomaterials are produced and have been extensively used for dental and orthopaedic applications. This is justified by their biocompatibility, osteoconductivity and osteoinductivity (i.e. the intrinsic material property that initiates de novo bone formation), which are attributed to the chemical composition, surface topography, macro/microporosity and the dissolution kinetics. However, the exact molecular mechanism of action is unknown. This review paper first summarizes the most important aspects of bone biology in relation to CaP and the mechanisms of bone matrix mineralization. This is followed by the research findings on the effects of calcium (Ca(2)(+)) and phosphate (PO(4)(3)(-)) ions on the migration, proliferation and differentiation of osteoblasts during in vivo bone formation and in vitro culture conditions. Further, the rationale of using CaP for bone regeneration is explained, focusing thereby specifically on the material's osteoinductive properties. Examples of different material forms and production techniques are given, with the emphasis on the state-of-the art in fine-tuning the physicochemical properties of CaP-based biomaterials for improved bone induction and the use of CaP as a delivery system for bone morphogenetic proteins. The use of computational models to simulate the CaP-driven osteogenesis is introduced as part of a bone tissue engineering strategy in order to facilitate the understanding of cell-material interactions and to gain further insight into the design and optimization of CaP-based bone reparative units. Finally, limitations and possible solutions related to current experimental and computational techniques are discussed. [less ▲]Detailed reference viewed: 13 (1 ULg)
Designing optimal calcium phosphate scaffold-cell combinations using an integrative model-based approach.
Carlier, Aurélie ; ; et al
in Acta Biomaterialia (2011), 7(10), 3573-85
Bone formation is a very complex physiological process, involving the participation of many different cell types and regulated by countless biochemical, physical and mechanical factors, including ... [more ▼]
Bone formation is a very complex physiological process, involving the participation of many different cell types and regulated by countless biochemical, physical and mechanical factors, including naturally occurring or synthetic biomaterials. For the latter, calcium phosphate (CaP)-based scaffolds have proven to stimulate bone formation, but at present still result in a wide range of in vivo outcomes, which is partly related to the suboptimal use and combination with osteogenic cells. To optimize CaP scaffold selection and make their use in combination with cells more clinically relevant, this study uses an integrative approach in which mathematical modeling is combined with experimental research. This paper describes the development and implementation of an experimentally informed bioregulatory model of the effect of calcium ions released from CaP-based biomaterials on the activity of osteogenic cells and mesenchymal stem cell driven ectopic bone formation. The amount of bone formation predicted by the mathematical model corresponds to the amount measured experimentally under similar conditions. Moreover, the model is also able to qualitatively predict the experimentally observed impaired bone formation under conditions such as insufficient cell seeding and scaffold decalcification. A strategy was designed in silico to overcome the negative influence of a low initial cell density on the bone formation process. Finally, the model was applied to design optimal combinations of calcium-based biomaterials and cell culture conditions with the aim of maximizing the amount of bone formation. This work illustrates the potential of mathematical models as research tools to design more efficient and cell-customized CaP scaffolds for bone tissue engineering applications. [less ▲]Detailed reference viewed: 35 (15 ULg)
Computational modelling of biomaterial surface interactions with blood platelets and osteoblastic cells for the prediction of contact osteogenesis.
; Geris, Liesbet ; et al
in Acta Biomaterialia (2011), 7(2), 779-90
Surface microroughness can induce contact osteogenesis (bone formation initiated at the implant surface) around oral implants, which may result from different mechanisms, such as blood platelet ... [more ▼]
Surface microroughness can induce contact osteogenesis (bone formation initiated at the implant surface) around oral implants, which may result from different mechanisms, such as blood platelet-biomaterial interactions and/or interaction with (pre-)osteoblast cells. We have developed a computational model of implant endosseous healing that takes into account these interactions. We hypothesized that the initial attachment and growth factor release from activated platelets is crucial in achieving contact osteogenesis. In order to investigate this, a computational model was applied to an animal experiment  that looked at the effect of surface microroughness on endosseous healing. Surface-specific model parameters were implemented based on in vitro data (Lincks et al. Biomaterials 1998;19:2219-32). The predicted spatio-temporal patterns of bone formation correlated with the histological data. It was found that contact osteogenesis could not be predicted if only the osteogenic response of cells was up-regulated by surface microroughness. This could only be achieved if platelet-biomaterial interactions were sufficiently up-regulated as well. These results confirmed our hypothesis and demonstrate the added value of the computational model to study the importance of surface-mediated events for peri-implant endosseous healing. [less ▲]Detailed reference viewed: 9 (2 ULg)
In silico design of treatment strategies in wound healing and bone fracture healing
Geris, Liesbet ; ;
in Philosophical Transactions : Mathematical, Physical & Engineering Sciences (2010), 368(1920), 2683-2706
Wound and bone fracture healing are natural repair processes initiated by trauma. Over the last decade, many mathematical models have been established to investigate the healing processes in silico, in ... [more ▼]
Wound and bone fracture healing are natural repair processes initiated by trauma. Over the last decade, many mathematical models have been established to investigate the healing processes in silico, in addition to ongoing experimental work. In recent days, the focus of the mathematical models has shifted from simulation of the healing process towards simulation of the impaired healing process and the in silico design of treatment strategies. This review describes the most important causes of failure of the wound and bone fracture healing processes and the experimental models and methods used to investigate and treat these impaired healing cases. Furthermore, the mathematical models that are described address these impaired healing cases and investigate various therapeutic scenarios in silico. Examples are provided to illustrate the potential of these in silico experiments. Finally, limitations of the models and the need for and ability of these models to capture patient specificity and variability are discussed. [less ▲]Detailed reference viewed: 21 (4 ULg)
Numerical simulation of bone regeneration in a bone chamber.
Geris, Liesbet ; ; et al
in Journal of Dental Research (2009), 88(2), 158-63
While mathematical models are able to capture essential aspects of biological processes like fracture healing and distraction osteogenesis, their predictive capacity in peri-implant osteogenesis remains ... [more ▼]
While mathematical models are able to capture essential aspects of biological processes like fracture healing and distraction osteogenesis, their predictive capacity in peri-implant osteogenesis remains uninvestigated. We tested the hypothesis that a mechano-regulatory model has the potential to predict bone regeneration around implants. In an in vivo bone chamber set-up allowing for controlled implant loading (up to 90 microm axial displacement), bone tissue formation was simulated and compared qualitatively and quantitatively with histology. Furthermore, the model was applied to simulate excessive loading conditions. Corresponding to literature data, implant displacement magnitudes larger than 90 microm predicted the formation of fibrous tissue encapsulation of the implant. In contradiction to findings in orthopedic implant osseointegration, implant displacement frequencies higher than 1 Hz did not favor the formation of peri-implant bone in the chamber. Additional bone chamber experiments are needed to test these numerical predictions. [less ▲]Detailed reference viewed: 10 (0 ULg)
In silico biology of bone modelling and remodelling: regeneration.
Geris, Liesbet ; ;
in Philosophical Transactions : Mathematical, Physical & Engineering Sciences (2009), 367(1895), 2031-53
Bone regeneration is the process whereby bone is able to (scarlessly) repair itself from trauma, such as fractures or implant placement. Despite extensive experimental research, many of the mechanisms ... [more ▼]
Bone regeneration is the process whereby bone is able to (scarlessly) repair itself from trauma, such as fractures or implant placement. Despite extensive experimental research, many of the mechanisms involved still remain to be elucidated. Over the last decade, many mathematical models have been established to investigate the regeneration process in silico. The first models considered only the influence of the mechanical environment as a regulator of the healing process. These models were followed by the development of bioregulatory models where mechanics was neglected and regeneration was regulated only by biological stimuli such as growth factors. The most recent mathematical models couple the influences of both biological and mechanical stimuli. Examples are given to illustrate the added value of mathematical regeneration research, specifically in the in silico design of treatment strategies for non-unions. Drawbacks of the current continuum-type models, together with possible solutions in extending the models towards other time and length scales are discussed. Finally, the demands for dedicated and more quantitative experimental research are presented. [less ▲]Detailed reference viewed: 16 (0 ULg)
Modelling the early phases of bone regeneration around an endosseous oral implant
; Geris, Liesbet ; et al
in Computer Methods in Biomechanics & Biomedical Engineering (2009), 12(4), 459-468
The objective of this study was to see whether a mathematical model of fracture healing was able to mimic bone formation around an unloaded screw-shaped titanium implant as it is well-believed that both ... [more ▼]
The objective of this study was to see whether a mathematical model of fracture healing was able to mimic bone formation around an unloaded screw-shaped titanium implant as it is well-believed that both processes exhibit many biological similarities. This model describes the spatio-temporal evolution of cellular activities, ranging from mesenchymal stem cell migration, proliferation, differentiation to bone formation, which are initiated and regulated by the growth factors present at the peri-implant site. For the simulations, a finite volume code was used and adequate initial and boundary conditions were applied. Two sets of analyses have been performed, in which either initial and boundary condition or model parameter values were changed with respect to the fracture healing model parameter values. For a number of combinations, the spatio-temporal evolution of bone density was well-predicted. However reducing cell proliferation rate and increasing osteoblast differentiation and osteogenic growth factor synthesis rates, the simulation results were in agreement with the experimental data. [less ▲]Detailed reference viewed: 12 (2 ULg)
The influence of micro-motion on the tissue differentiation around immediately loaded cylindrical turned titanium implants.
; ; Geris, Liesbet et al
in Archives of Oral Biology (2006), 51(1), 1-9
OBJECTIVE: The aim of this study was to evaluate the effect of various degrees of implant displacement on the tissue differentiation around immediately loaded cylindrical turned titanium implants. DESIGN ... [more ▼]
OBJECTIVE: The aim of this study was to evaluate the effect of various degrees of implant displacement on the tissue differentiation around immediately loaded cylindrical turned titanium implants. DESIGN: The experiments were conducted in repeated sampling bone chambers placed in the tibia of 10 rabbits. Tissues could grow into the bone chambers via perforations. Due to its double structure, tissues inside the chamber could be harvested leaving the chamber intact. This allowed several experiments within the same animal. The chambers contained a cylindrical turned titanium implant that was loaded in a well-controlled manner. In each of the 10 chambers, four experiments were conducted with the following test conditions: immediate implant loading by inducing 0 (control), 30, 60 and 90 microm implant displacement, 800 cycles per day at a frequency of 1 Hz, twice a week during a period of 6 weeks. Histological and histomorphometrical analyses were performed on methylmethacrylate histological sections. An ANOVA was conducted on the dataset. RESULTS: The total tissue volume was significantly lowest in the unloaded control condition. The bone volume fraction on the other hand, was significantly larger in the unloaded and 90 microm implant displacement, compared to the 30 microm implant displacement. Bone density increased with increasing micro-motion with significantly higher values for the 60 microm- and 90 microm-test conditions compared to the unloaded situation. The chance to have bone-to-implant contact decreased in case of micro-motion at the tissues-implant interface. CONCLUSION: The magnitude of implant displacement had a statistically significant effect on the tissue differentiation around immediately loaded cylindrical turned titanium implants. Implant micro-motion had a detrimental effect on the bone-to-implant contact in an immediate loading regimen. [less ▲]Detailed reference viewed: 17 (0 ULg)
Numerical simulation of tissue differentiation around loaded titanium implants in a bone chamber.
Geris, Liesbet ; ; et al
in Journal of Biomechanics (2004), 37(5), 763-9
The application of a bone chamber provides a controlled environment for the study of tissue differentiation and bone adaptation. The influence of different mechanical and biological factors on the ... [more ▼]
The application of a bone chamber provides a controlled environment for the study of tissue differentiation and bone adaptation. The influence of different mechanical and biological factors on the processes can be measured experimentally. The goal of the present work is to numerically model the process of peri-implant tissue differentiation inside a bone chamber, placed in a rabbit tibia. 2D and 3D models were created of the tissue inside the chamber. A number of loading conditions, corresponding to those applied in the rabbit experiments, were simulated. Fluid velocity and maximal distortional strain were considered as the stimuli that guide the differentiation process of mesenchymal cells into fibroblasts, chondrocytes and osteoblasts. Mesenchymal cells migrate through the chamber from the perforations in the chamber wall. This process is modelled by the diffusion equation. The predicted tissue phenotypes as well as the process of tissue ingrowth into the chamber show a qualitative agreement with the results of the rabbit experiments. Due to the limited number of animal experiments (four) and the observed inter-animal differences, no quantitative comparison could be made. These results however are a strong indication of the feasibility of the implemented theory to predict the mechano-regulation of the differentiation process inside the bone chamber. [less ▲]Detailed reference viewed: 5 (0 ULg)
Assessment of mechanobiological models for the numerical simulation of tissue differentiation around immediately loaded implants.
Geris, Liesbet ; ; et al
in Computer Methods in Biomechanics & Biomedical Engineering (2003), 6(5-6), 277-88
Nowadays, there is a growing consensus on the impact of mechanical loading on bone biology. A bone chamber provides a mechanically isolated in vivo environment in which the influence of different ... [more ▼]
Nowadays, there is a growing consensus on the impact of mechanical loading on bone biology. A bone chamber provides a mechanically isolated in vivo environment in which the influence of different parameters on the tissue response around loaded implants can be investigated. This also provides data to assess the feasibility of different mechanobiological models that mathematically describe the mechanoregulation of tissue differentiation. Before comparing numerical results to animal experimental results, it is necessary to investigate the influence of the different model parameters on the outcome of the simulations. A 2D finite element model of the tissue inside the bone chamber was created. The differentiation models developed by Prendergast, et al. ["Biophysical stimuli on cells during tissue differentiation at implant interfaces", Journal of Biomechanics, 30(6), (1997), 539-548], Huiskes et al. ["A biomechanical regulatory model for periprosthetic fibrous-tissue differentiation", Journal of Material Science: Materials in Medicine, 8 (1997) 785-788] and by Claes and Heigele ["Magnitudes of local stress and strain along bony surfaces predict the course and type of fracture healing", Journal of Biomechanics, 32(3), (1999) 255-266] were implemented and integrated in the finite element code. The fluid component in the first model has an important effect on the predicted differentiation patterns. It has a direct effect on the predicted degree of maturation of bone and a substantial indirect effect on the simulated deformations and hence the predicted phenotypes of the tissue in the chamber. Finally, the presence of fluid also causes time-dependent behavior. Both models lead to qualitative and quantitative differences in predicted differentiation patterns. Because of the different nature of the tissue phenotypes used to describe the differentiation processes, it is however hard to compare both models in terms of their validity. [less ▲]Detailed reference viewed: 8 (2 ULg)