A numerical model of the fracture healing process that describes tissue development and revascularisation

A dynamic model was developed to simulate complex interactions of mechanical stability, revascularisation and tissue differentiation in secondary fracture healing. Unlike previous models, blood perfusion was included as a spatio-temporal state variable to simulate the revascularisation process. A 2D, axisymmetrical finite element model described fracture callus mechanics. Fuzzy logic rules described the following biological processes: angiogenesis, intramembranous ossification, chondrogenesis, cartilage calcification and endochondral ossification, all of which depended on local strain state and local blood perfusion. In order to evaluate how the predicted revascularisation depended on the mechanical environment, we simulated two different healing cases according to two groups of transverse metatarsal osteotomies in sheep with different axial stability. The model predicted slower revascularisation and delayed bony bridging for the less stable case, which corresponded well to the experimental observations. A revascularisation sensitivity analysis demonstrated the potential of the model to account for different conditions regarding the blood supply.     

Comparison of biophysical stimuli for mechano-regulation of tissue differentiation during fracture healing

Most long-bone fractures heal through indirect or secondary fracture healing, a complex process in which endochondral ossification is an essential part and bone is regenerated by tissue differentiation. This process is sensitive to the mechanical environment, and several authors have proposed mechano-regulation algorithms to describe it using strain, pore pressure and/or interstitial fluid velocity as biofeedback variables. The aim of this study was to compare various mechano-regulation algorithms' abilities to describe normal fracture healing in one computational model. Additionally, we hypothesized that tissue differentiation during normal fracture healing could be equally well regulated by the individual mechanical stimuli, e.g. deviatoric strain, pore pressure or fluid velocity. A biphasic finite element model of an ovine tibia with a 3mm fracture gap and callus was used to simulate the course of tissue differentiation during normal fracture healing. The load applied was regulated in a biofeedback loop, where the load magnitude was determined by the interfragmentary movement in the fracture gap. All the previously published mechano-regulation algorithms studied, simulated the course of normal fracture healing correctly. They predicted (1) intramembranous bone formation along the periosteum and callus tip, (2) endochondral ossification within the external callus and cortical gap, and (3) creeping substitution of bone towards the gap from the initial lateral osseous bridge. Some differences between the effects of the algorithms were seen, but they were not significant. None of the volumetric components, i.e. pore pressure or fluid velocity, alone were able to correctly predict spatial or temporal tissue distribution during fracture healing. However, simulation as a function of only deviatoric strain accurately predicted the course of normal fracture healing. This suggests that the deviatoric component may be the most significant mechanical parameter to guide tissue differentiation during indirect fracture healing.     

Identification of tissue differentiation rates in a mechanobiological model of fracture healing

As a basis for model-based analysis of the processes in secondary fracture healing, a dynamical model is presented that characterises the physiological status in the fracture area by the location-dependent composition of tissues. Five types of tissue are distinguished: connective tissue, cartilage, bone, haematoma and avascular bone. A rule base is given that describes dynamical tissue differentiation processes. The rules consider not only a mechanical stimulus but also osteogenic and a vasculative factors as biological stimuli. Within this model structure, it is possible, e.g., to distinguish intramembranous from endochondral ossification processes. An objective function is introduced to assess accordance between the model-based simulation results and reference healing stages. By minimising this objective function, relevant tissue differentiation rates can be determined. For a reference process of secondary fracture healing it could be shown that the intramembranous ossification rate of 0.313%/day (from connective tissue to bone) is much smaller than the endochondral ossification rate of 1.136%/day (from cartilage to bone). In order to verify the model approach, it is transferred to simulate long bone distraction. Results show that healing patterns of bone distraction can be predicted. Using this method, it is possible to identify model parameters for individual subjects. This will allow a patient-specific analysis of tissue healing processes in future.     

Trabecular bone fracture healing simulation with finite element analysis and fuzzy logic

Trabecular bone fractures heal through intramembraneous ossification. This process differs from diaphyseal fracture healing in that the trabecular marrow provides a rich vascular supply to the healing bone, there is very little callus formation, woven bone forms directly without a cartilage intermediary, and the woven bone is remodelled to form trabecular bone. Previous studies have used numerical methods to simulate diaphyseal fracture healing or bone remodelling, however not trabecular fracture healing, which involves both tissue differentiation and trabecular formation. The objective of this study was to determine if intramembraneous bone formation and remodelling during trabecular bone fracture healing could be simulated using the same mechanobiological principles as those proposed for diaphyseal fracture healing. Using finite element analysis and the fuzzy logic for diaphyseal healing, the model simulated formation of woven bone in the fracture gap and subsequent remodelling of the bone to form trabecular bone. We also demonstrated that the trabecular structure is dependent on the applied loading conditions. A single model that can simulate bone healing and remodelling may prove to be a useful tool in predicting musculoskeletal tissue differentiation in different vascular and mechanical environments.     

Simulation of the nutrient supply in fracture healing

The healing process for bone fractures is sensitive to mechanical stability and blood supply at the fracture site. Most currently available mechanobiological algorithms of bone healing are based solely on mechanical stimuli, while the explicit analysis of revascularization and its influences on the healing process have not been thoroughly investigated in the literature. In this paper, revascularization was described by two separate processes: angiogenesis and nutrition supply. The mathematical models for angiogenesis and nutrition supply have been proposed and integrated into an existing fuzzy algorithm of fracture healing. The computational algorithm of fracture healing, consisting of stress analysis, analyses of angiogenesis and nutrient supply, and tissue differentiation, has been tested on and compared with animal experimental results published previously. The simulation results showed that, for a small and medium-sized fracture gap, the nutrient supply is sufficient for bone healing, for a large fracture gap, non-union may be induced either by deficient nutrient supply or inadequate mechanical conditions. The comparisons with experimental results demonstrated that the improved computational algorithm is able to simulate a broad spectrum of fracture healing cases and to predict and explain delayed unions and non-union induced by large gap sizes and different mechanical conditions. The new algorithm will allow the simulation of more realistic clinical fracture healing cases with various fracture gaps and geometries and may be helpful to optimise implants and methods for fracture fixation.     

Continual measurement of intramedullary blood perfusion with laser Doppler flowmetry in intact and ostectomized tibiae of rabbits

Blood flow is important for the healing of bone fractures. Until now, however, there have been no publications on the daily, continual measurement of intramedullary blood perfusion using laser Doppler flowmetry (LDF) in the conscious animal. In this study, a model for the daily, continual measurement of intramedullary blood perfusion by LDF and the temperature near the cortex both in intact and ostectomized tibiae in the conscious rabbit is described. The probes for blood perfusion and temperature measurement were implanted permanently at three different localizations into the right tibia of 10 adult New Zealand White rabbits. The probes were held in place by a bilateral, single-plane external fixator. In five of these animals, a midshaft tibial ostectomy was created in order to simulate a fracture. Intramedullary blood perfusion and temperature were measured daily over 49 days. While in intact tibiae no significant (P > 0.05) differences were found in blood perfusion readings taken at various time points, for mean values or for blood perfusion over time, in ostectomized tibiae the differences were significant: various time points (P = 0.0056), mean values (P = 0.0034) and blood perfusion over time (P = 0.0337). Blood perfusion readings at the centre probe were elevated compared with those at the proximal and distal probes. Thus, a revascularization in the ostectomy gap during the fracture healing was proven by means of the LDF. No influence of the blood perfusion on the temperature in the ostectomy area could be determined during healing of the ostectomy. The described model seems suitable for the continual measurement of intramedullary blood perfusion both in intact and ostectomized tibiae in the conscious rabbit.     

A computational model to explore the role of angiogenic impairment on endochondral ossification during fracture healing

While it is well established that an adequate blood supply is critical to successful bone regeneration, it remains poorly understood how progenitor cell fate is affected by the altered conditions present in fractures with disrupted vasculature. In this study, computational models were used to explore how angiogenic impairment impacts oxygen availability within a fracture callus and hence regulates mesenchymal stem cell (MSC) differentiation and bone regeneration. Tissue differentiation was predicted using a previously developed algorithm which assumed that MSC fate is governed by oxygen tension and substrate stiffness. This model was updated based on the hypothesis that cell death, chondrocyte hypertrophy and endochondral ossification are regulated by oxygen availability. To test this, the updated model was used to simulate the time course of normal fracture healing, where it successfully predicted the observed quantity and spatial distribution of bone and cartilage at 10 and 20 days post-fracture (dpf). It also predicted the ratio of cartilage which had become hypertrophic at 10 dpf. Following this, three models of fracture healing with increasing levels of angiogenic impairment were developed. Under mild impairment, the model predicted experimentally observed reductions in hypertrophic cartilage at 10 dpf as well as the persistence of cartilage at 20 dpf. Models of more severe impairment predicted apoptosis and the development of fibrous tissue. These results provide insight into how factors specific to an ischemic callus regulate tissue regeneration and provide support for the hypothesis that chondrocyte hypertrophy and endochondral ossification during tissue regeneration are inhibited by low oxygen.     

Creating Rigidly Stabilized Fractures for Assessing Intramembranous Ossification,Distraction Osteogenesis,or Healing of Critical Sized Defects

Assessing modes of skeletal repair is essential for developing therapies to be used clinically to treat fractures. Mechanical stability plays a large role in healing of bone injuries. In the worst-case scenario mechanical instability can lead to delayed or non-union in humans. However, motion can also stimulate the healing process. In fractures that have motion cartilage forms to stabilize the fracture bone ends, and this cartilage is gradually replaced by bone through recapitulation of the developmental process of endochondral ossification. In contrast, if a bone fracture is rigidly stabilized bone forms directly via intramembranous ossification. Clinically, both endochondral and intramembranous ossification occur simultaneously. To effectively replicate this process investigators insert a pin into the medullary canal of the fractured bone as described by Bonnarens⁴. This experimental method provides excellent lateral stability while allowing rotational instability to persist. However, our understanding of the mechanisms that regulate these two distinct processes can also be enhanced by experimentally isolating each of these processes. We have developed a stabilization protocol that provides rotational and lateral stabilization. In this model, intramembranous ossification is the only mode of healing that is observed, and healing parameters can be compared among different strains of genetically modified mice ^5-7, after application of bioactive molecules ^8,9, after altering physiological parameters of healing ¹⁰, after modifying the amount or time of stabilization ¹¹, after distraction osteogenesis ¹², after creation of a non-union ¹³, or after creation of a critical sized defect. Here, we illustrate how to apply the modified Ilizarov fixators for studying tibial fracture healing and distraction osteogenesis in mice.     

Influence of fracture gap size on the pattern of long bone healing: a computational study

Following fractures, bones restore their original structural integrity through a complex process in which several cellular events are involved. Among other factors, this process is highly influenced by the mechanical environment of the fracture site. In this study, we present a mathematical model to simulate the effect of mechanical stimuli on most of the cellular processes that occur during fracture healing, namely proliferation, migration and differentiation. On the basis of these three processes, the model then simulates the evolution of geometry, distributions of cell types and elastic properties inside a healing fracture. The three processes were implemented in a Finite Element code as a combination of three coupled analysis stages: a biphasic, a diffusion and a thermoelastic step. We tested the mechano-biological regulatory model thus created by simulating the healing patterns of fractures with different gap sizes and different mechanical stimuli. The callus geometry, tissue differentiation patterns and fracture stiffness predicted by the model were similar to experimental observations for every analysed situation.     

Magnitudes of local stress and strain along bony surfaces predict the course and type of fracture healing

A new quantitative tissue differentiation theory which relates the local tissue formation in a fracture gap to the local stress and strain is presented. Our hypothesis proposes that the amounts of strain and hydrostatic pressure along existing calcified surfaces in the fracture callus determine the differentiation of the callus tissue. The study compares the local strains and stresses in the callus as calculated from a finite element model with histological findings from an animal fracture model. The hypothesis predicts intramembranous bone formation for strains smaller approximately +/- 5% and hydrostatic pressures smaller than +/- 0.15 MPa. Endochondral ossification is associated with compressive pressures larger than about -0.15 MPa and strains smaller than +/- 15%. All other conditions seemed to lead to connective tissue or fibrous cartilage. The hypothesis enables a better understanding of the complex tissue differentiation seen in histological images and the mechanical conditions for healing delayed healing or nonunions.     

Substrate Stiffness and Oxygen as Regulators of Stem Cell Differentiation during Skeletal Tissue Regeneration: A Mechanobiological Model

Extrinsic mechanical signals have been implicated as key regulators of mesenchymal stem cell (MSC) differentiation. It has been possible to test different hypotheses for mechano-regulated MSC differentiation by attempting to simulate regenerative events such as bone fracture repair, where repeatable spatial and temporal patterns of tissue differentiation occur. More recently, in vitro studies have identified other environmental cues such as substrate stiffness and oxygen tension as key regulators of MSC differentiation; however it remains unclear if and how such cues determine stem cell fate in vivo. As part of this study, a computational model was developed to test the hypothesis that substrate stiffness and oxygen tension regulate stem cell differentiation during fracture healing. Rather than assuming mechanical signals act directly on stem cells to determine their differentiation pathway, it is postulated that they act indirectly to regulate angiogenesis and hence partially determine the local oxygen environment within a regenerating tissue. Chondrogenesis of MSCs was hypothesized to occur in low oxygen regions, while in well vascularised regions of the regenerating tissue a soft local substrate was hypothesised to facilitate adipogenesis while a stiff substrate facilitated osteogenesis. Predictions from the model were compared to both experimental data and to predictions of a well established computational mechanobiological model where tissue differentiation is assumed to be regulated directly by the local mechanical environment. The model predicted all the major events of fracture repair, including cartilaginous bridging, endosteal and periosteal bony bridging and bone remodelling. It therefore provides support for the hypothesis that substrate stiffness and oxygen play a key role in regulating MSC fate during regenerative events such as fracture healing.     

Prediction of the Time Course of Callus Stiffness as a Function of Mechanical Parameters in Experimental Rat Fracture Healing Studies - A Numerical Study

Numerous experimental fracture healing studies are performed on rats, in which different experimental, mechanical parameters are applied, thereby prohibiting direct comparison between each other. Numerical fracture healing simulation models are able to predict courses of fracture healing and offer support for pre-planning animal experiments and for post-hoc comparison between outcomes of different in vivo studies. The aims of this study are to adapt a pre-existing fracture healing simulation algorithm for sheep and humans to the rat, to corroborate it using the data of numerous different rat experiments, and to provide healing predictions for future rat experiments. First, material properties of different tissue types involved were adjusted by comparing experimentally measured callus stiffness to respective simulated values obtained in three finite element (FE) models. This yielded values for Young’s moduli of cortical bone, woven bone, cartilage, and connective tissue of 15,750 MPa, 1,000 MPa, 5 MPa, and 1 MPa, respectively. Next, thresholds in the underlying mechanoregulatory tissue differentiation rules were calibrated by modifying model parameters so that predicted fracture callus stiffness matched experimental data from a study that used rigid and flexible fixators. This resulted in strain thresholds at higher magnitudes than in models for sheep and humans. The resulting numerical model was then used to simulate numerous fracture healing scenarios from literature, showing a considerable mismatch in only 6 of 21 cases. Based on this corroborated model, a fit curve function was derived which predicts the increase of callus stiffness dependent on bodyweight, fixation stiffness, and fracture gap size. By mathematically predicting the time course of the healing process prior to the animal studies, the data presented in this work provides support for planning new fracture healing experiments in rats. Furthermore, it allows one to transfer and compare new in vivo findings to previously performed studies with differing mechanical parameters.     

The mechanical heterogeneity of the hard callus influences local tissue strains during bone healing: a finite element study based on sheep experiments

During secondary fracture healing, various tissue types including new bone are formed. The local mechanical strains play an important role in tissue proliferation and differentiation. To further our mechanobiological understanding of fracture healing, a precise assessment of local strains is mandatory. Until now, static analyses using Finite Elements (FE) have assumed homogenous material properties. With the recent quantification of both the spatial tissue patterns (Vetter et al., 2010) and the development of elastic modulus of newly formed bone during healing (Manjubala et al., 2009), it is now possible to incorporate this heterogeneity. Therefore, the aim of this study is to investigate the effect of this heterogeneity on the strain patterns at six successive healing stages. The input data of the present work stemmed from a comprehensive cross-sectional study of sheep with a tibial osteotomy (Epari et al., 2006). In our FE model, each element containing bone was described by a bulk elastic modulus, which depended on both the local area fraction and the local elastic modulus of the bone material. The obtained strains were compared with the results of hypothetical FE models assuming homogeneous material properties. The differences in the spatial distributions of the strains between the heterogeneous and homogeneous FE models were interpreted using a current mechanobiological theory (Isakson et al., 2006). This interpretation showed that considering the heterogeneity of the hard callus is most important at the intermediate stages of healing, when cartilage transforms to bone via endochondral ossification.     

A 3D computational simulation of fracture callus formation: influence of the stiffness of the external fixator

The stiffness of the external fixation highly influences the fracture healing pattern. In this work we study this aspect by means of a finite element model of a simple transverse mid-diaphyseal fracture of an ovine metatarsus fixed with a bilateral external fixator. In order to simulate the regenerative process, a previously developed mechanobiological model of bone fracture healing was implemented in three dimensions. This model is able to simulate tissue differentiation, bone regeneration, and callus growth. A physiological load of 500 N was applied and three different stiffnesses of the external fixator were simulated (2300, 1725, and 1150 N/mm). The interfragmentary strain and load sharing mechanism between bone and the external fixator were compared to those recorded in previous experimental works. The effects of the stiffness on the callus shape and tissue distributions in the fracture site were also analyzed. We predicted that a lower stiffness of the fixator delays fracture healing and causes a larger callus, in correspondence to well-documented clinical observations.     

A mathematical framework to study the effects of growth factor influences on fracture healing

During fracture healing, multipotential stem cells differentiate into specialized cells responsible for producing the different tissues involved in the bone regeneration process. This cell differentiation has been shown to be regulated by locally expressed growth factors. The details of their regulatory mechanisms need to be understood. In this work, we present a two-dimensional mathematical model of the bone healing process for moderate fracture gap sizes and fracture stability. The inflammatory and tissue regeneration stages of healing are simulated by modeling mesenchymal cell migration; mesenchymal cell, chondrocyte and osteoblast proliferation and differentiation, and extracellular matrix synthesis and degradation over time. The effects of two generic growth factors on cell differentiation are based on the experimentally studied chondrogenic and osteogenic effects of bone morphogenetic proteins-2 and 4 and transforming growth factor-beta-1, respectively. The model successfully simulates the progression of healing and predicts that the rate of osteogenic growth factor production by osteoblasts and the duration of the initial release of growth factors upon injury are particularly important parameters for complete ossification and successful healing. This temporo-spatial model of fracture healing is the first model to consider the effects of growth factors. It will help us understand the regulatory mechanisms involved in bone regeneration and provides a mathematical framework with which to design experiments and understand pathological conditions.     

A mechano-regulation model for tissue differentiation during fracture healing: analysis of gap size and loading

Bone has a capability to repair itself when it is fractured. Repair involves the generation of intermediate tissues, such as fibrous connective tissue, cartilage and woven bone, before final bone healing can occur. The intermediate tissues serve to stabilise the mechanical environment and provide a scaffold for differentiation of new tissues. The repair process is fundamentally affected by mechanical loading and by the geometric configuration of the fracture fragments. Biomechanical analyses of fracture healing have previously computed the stress distribution within the callus and identified the components of the stress tensor favouring or inhibiting differentiation of particular tissue phenotypes. In this paper, a biphasic poroelastic finite element model of a fracture callus is used to simulate the time-course of tissue differentiation during fracture healing. The simulation begins with granulation tissue (post-inflammation phase) and finishes with bone resorption. The biomechanical regulatory model assumes that tissue differentiation is controlled by a combination of shear strain and fluid flow acting within the tissue. High shear strain and fluid flows are assumed to deform the precursor cells stimulating formation of fibrous connective tissue, lower levels stimulate formation of cartilage, and lower again allows ossification. This mechano-regulatory scheme was tested by simulating healing in fractures with different gap sizes and loading magnitudes. The appearance and disappearance of the various tissues found in a callus was similar to histological observation. The effect of gap size and loading magnitude on the rate of reduction of the interfragmentary strain was sufficiently close to confirm the hypothesis that tissue differentiation phenomena could be governed by the proposed mechano-regulation model.     

A mathematical model of pulmonary gas exchange under inflammatory stress

During a severe local or systemic inflammatory response, immune mediators target lung tissue. This process may lead to acute lung injury and impaired diffusion of gas molecules. Although several mathematical models of gas exchange have been described, none simulate acute lung injury following inflammatory stress. In view of recent laboratory and clinical progress in the understanding of the pathophysiology of acute lung injury, such a mathematical model would be useful. We first derived a partial differential equations model of gas exchange on a small physiological unit of the lung (≈25 alveoli), which we refer to as a respiratory unit (RU). We next developed a simple model of the acute inflammatory response and implemented its effects within a RU, creating a single RU model. Linking multiple RUs with various ventilation/perfusion ratios and taking into account pulmonary venous blood remixing yielded our lung-scale model. Using the lung-scale model, we explored the predicted effects of inflammation on ventilation/perfusion distribution and the resulting pulmonary venous partial pressure oxygen level during systemic inflammatory stresses. This model represents a first step towards the development of anatomically faithful models of gas exchange and ventilation under a broad range of local and systemic inflammatory stimuli resulting in acute lung injury, such as infection and mechanical strain of lung tissue.     

Modelling the effects of different fracture geometries and healing stages on ultrasound signal loss across a long bone fracture

The effect on the signal amplitude of ultrasonic waves propagating along cortical bone plates was modelled using a 2D Finite Difference code. Different healing stages, represented by modified fracture geometries were introduced to the plate model. A simple transverse and oblique fracture filled with water was introduced to simulate the inflammatory stage. Subsequently, a symmetric external callus surrounding a transverse fracture was modelled to represent an advanced stage of healing. In comparison to the baseline (intact plate) data, a large net loss in signal amplitude was produced for the simple transverse and oblique cases. Changing the geometry to an external callus with different mechanical properties caused the net loss in signal amplitude to reduce significantly. This relative change in signal amplitude as the geometry and mechanical properties of the fracture site change could potentially be used to monitor the healing process.     

Modelling the effects of different fracture geometries and healing stages on ultrasound signal loss across a long bone fracture

The effect on the signal amplitude of ultrasonic waves propagating along cortical bone plates was modelled using a 2D Finite Difference code. Different healing stages, represented by modified fracture geometries were introduced to the plate model. A simple transverse and oblique fracture filled with water was introduced to simulate the inflammatory stage. Subsequently, a symmetric external callus surrounding a transverse fracture was modelled to represent an advanced stage of healing. In comparison to the baseline (intact plate) data, a large net loss in signal amplitude was produced for the simple transverse and oblique cases. Changing the geometry to an external callus with different mechanical properties caused the net loss in signal amplitude to reduce significantly. This relative change in signal amplitude as the geometry and mechanical properties of the fracture site change could potentially be used to monitor the healing process.     

Computational simulation of fracture healing: influence of interfragmentary movement on the callus growth

Bone fractures heal through a complex process involving several cellular events. This healing process can serve to study factors that control tissue growth and differentiation from mesenchymal stem cells. The mechanical environment at the fracture site is one of the factors influencing the healing process and controls size and differentiation patterns in the newly formed tissue. Mathematical models can be useful to unravel the complex relation between mechanical environment and tissue formation. In this study, we present a mathematical model that predicts tissue growth and differentiation patterns from local mechanical signals. Our aim was to investigate whether mechanical stimuli, through their influence on stem cell proliferation and chondrocyte hypertrophy, predict characteristic features of callus size and geometry. We found that the model predicted several geometric features of fracture calluses. For instance, callus size was predicted to increase with increasing movement. Also, increases in size were predicted to occur through increase in callus diameter but not callus length. These features agree with experimental observations. In addition, spatial and temporal tissue differentiation patterns were in qualitative agreement with well-known experimental results. We therefore conclude that local mechanical signals can probably explain the shape and size of fracture calluses.