An enhanced version of a bone-remodelling model based on the continuum damage mechanics theory

Bone remodelling prediction using mechanical stimulus with bone connectivity theory in porous implants

Strain energy density (SED) is considered to be the primary remodelling stimulus influencing the process of bone growth into porous implants. A bone remodelling algorithm incorporating the concept of bone connectivity, that newly formed bone should only grow from existing bone, was developed to provide a more biologically realistic simulation of bone growth. Results showed that the new algorithm prevented the occurrence of unconnected mature bone within porous implants, an unrealistic phenomenon observed using conventional adaptive elasticity theories. The bone connectivity algorithm had minimal effect (0.67% difference) on the final bone density distribution for standard bending and torsional moment cases. For a porous implant model, both algorithms, with and without bone connectivity implementation, reached the same final stiffness, with a difference of less than 0.01%. The bone connectivity algorithm predicted a slower and more gradual bone remodelling process, requiring at least 50% additional time for full remodelling compared to the conventional adaptive elasticity algorithm, which should be accounted for in the planning of rehabilitation strategies. The developed modelling can be employed to improve porous implant designs to achieve better clinical outcomes.

Modeling Progressive Damage Accumulation in Bone Remodeling Explains the Thermodynamic Basis of Bone Resorption by Overloading

Computational modeling of skeletal tissue seeks to predict the structural adaptation of bone in response to mechanical loading. The theory of continuum damage-repair, a mathematical description of structural adaptation based on principles of damage mechanics, continues to be developed and utilized for the prediction of long-term peri-implant outcomes. Despite its technical soundness, CDR does not account for the accumulation of mechanical damage and irreversible deformation. In this work, a nonlinear mathematical model of independent damage accumulation and plastic deformation is developed in terms of the CDR formulation. The proposed model incorporates empirical correlations from uniaxial experiments. Supporting elements of the model are derived, including damage and yielding criteria, corresponding consistency conditions, and the basic, necessary forms for integration during loading. Positivity of mechanical dissipation due to damage is proved, while strain-based, associative plastic flow and linear hardening describe post-yield behavior. Calibration of model parameters to the empirical correlations from which the model was derived is then accomplished. Results of numerical experiments on a point-wise specimen show that damage and plasticity inhibit bone formation by dissipation of energy available to biological processes, leading to material failure that would otherwise be predicted to experience a net gain of bone.

Analysis of Damage Models for Cortical Bone

Bone tissue is a material with a complex structure and mechanical properties. Diseases or even normal repetitive loads may cause microfractures to appear in the bone structure, leading to a deterioration of its properties. A better understanding of this phenomenon will lead to better predictions of bone fracture or bone-implant performance. In this work, the model proposed by Frémond and Nedjar in 1996 (initially for concrete structures) is numerically analyzed and compared against a bone specific mechanical model proposed by García et al. in 2009. The objective is to evaluate both models implemented with a finite element method. This will allow us to determine if the modified Frémond–Nedjar model is adequate for this purpose. We show that, in one dimension, both models show similar results, reproducing the qualitative behaviour of bone subjected to typical engineering tests. In particular, the Frémond–Nedjar model with the introduced modifications shows good agreement with experimental data. Finally, some two-dimensional results are also provided for the Frémond–Nedjar model to show its behaviour in the simulation of a real tensile test.

On the Use of Bone Remodelling Models to Estimate the Density Distribution of Bones. Uniqueness of the Solution

Bone remodelling models are widely used in a phenomenological manner to estimate numerically the distribution of apparent density in bones from the loads they are daily subjected to. These simulations start from an arbitrary initial distribution, usually homogeneous, and the density changes locally until a bone remodelling equilibrium is achieved. The bone response to mechanical stimulus is traditionally formulated with a mathematical relation that considers the existence of a range of stimulus, called dead or lazy zone, for which no net bone mass change occurs. Implementing a relation like that leads to different solutions depending on the starting density. The non-uniqueness of the solution has been shown in this paper using two different bone remodelling models: one isotropic and another anisotropic. It has also been shown that the problem of non-uniqueness is only mitigated by removing the dead zone, but it is not completely solved unless the bone formation and bone resorption rates are limited to certain maximum values.

A biomechanical evaluation of CNT-grown bone

Beside their biochemical properties, the exceptional mechanical characteristics of carbon nanotubes (CNTs) suggested growing a reinforced composite material very similar to natural bone in structure and chemical composition, but significantly stronger and stiffer. This is where biomechanical considerations portray themselves to justify the need for further investigations, in order to verify the applicability of CNTs as scaffolds that may ease bone regeneration and simultaneously raise its mechanical strength and durability. This research, using several modeling approaches, attempts to look at some of the mechanical changes likely to take place in the promised artificial tissue, while considering the relationships between mechanical and living functions of bone, particularly the remodeling process. Results suggest that notwithstanding the significant improvements induced to the mechanical behavior of the artificial tissue, applications of such stiff inclusions as CNTs in reinforcing the material of bone may detrimentally change the thresholds of mechanical stimuli that are essential for the initiation and resumption of the bone remodeling process.

Discrete Element Framework for Modelling Extracellular Matrix, Deformable Cells and Subcellular Components

This paper presents a framework for modelling biological tissues based on discrete particles. Cell components (e.g. cell membranes, cell cytoskeleton, cell nucleus) and extracellular matrix (e.g. collagen) are represented using collections of particles. Simple particle to particle interaction laws are used to simulate and control complex physical interaction types (e.g. cell-cell adhesion via cadherins, integrin basement membrane attachment, cytoskeletal mechanical properties). Particles may be given the capacity to change their properties and behaviours in response to changes in the cellular microenvironment (e.g., in response to cell-cell signalling or mechanical loadings). Each particle is in effect an ‘agent’, meaning that the agent can sense local environmental information and respond according to pre-determined or stochastic events. The behaviour of the proposed framework is exemplified through several biological problems of ongoing interest. These examples illustrate how the modelling framework allows enormous flexibility for representing the mechanical behaviour of different tissues, and we argue this is a more intuitive approach than perhaps offered by traditional continuum methods. Because of this flexibility, we believe the discrete modelling framework provides an avenue for biologists and bioengineers to explore the behaviour of tissue systems in a computational laboratory.

Modelling is an important tool in understanding the behaviour of biological tissues. In this paper we advocate a new modelling framework in which cells and tissues are represented by a collection of particles with associated properties. The particles interact with each other and can change their behaviour in response to changes in their environment. We demonstrate how the propose framework can be used to represent the mechanical behaviour of different tissues with much greater flexibility as compared to traditional continuum based methods.

Regenerative orthopaedics: in vitro, in vivo...in silico

In silico, defined in analogy to in vitro and in vivo as those studies that are performed on a computer, is an essential step in problem-solving and product development in classical engineering fields. The use of in silico models is now slowly easing its way into medicine. In silico models are already used in orthopaedics for the planning of complicated surgeries, personalised implant design and the analysis of gait measurements. However, these in silico models often lack the simulation of the response of the biological system over time. In silico models focusing on the response of the biological systems are in full development. This review starts with an introduction into in silico models of orthopaedic processes. Special attention is paid to the classification of models according to their spatiotemporal scale (gene/protein to population) and the information they were built on (data vs hypotheses). Subsequently, the review focuses on the in silico models used in regenerative orthopaedics research. Contributions of in silico models to an enhanced understanding and optimisation of four key elements-cells, carriers, culture and clinics-are illustrated. Finally, a number of challenges are identified, related to the computational aspects but also to the integration of in silico tools into clinical practice.