Computational simulation methodologies for mechanobiological modelling: a cell-centred approach to neointima development in stents

The design of medical devices could be very much improved if robust tools were available for computational simulation of tissue response to the presence of the implant. Such tools require algorithms to simulate the response of tissues to mechanical and chemical stimuli. Available methodologies include those based on the principle of mechanical homeostasis, those which use continuum models to simulate biological constituents, and the cell-centred approach, which models cells as autonomous agents. In the latter approach, cell behaviour is governed by rules based on the state of the local environment around the cell; and informed by experiment. Tissue growth and differentiation requires simulating many of these cells together. In this paper, the methodology and applications of cell-centred techniques-with particular application to mechanobiology-are reviewed, and a cell-centred model of tissue formation in the lumen of an artery in response to the deployment of a stent is presented. The method is capable of capturing some of the most important aspects of restenosis, including nonlinear lesion growth with time. The approach taken in this paper provides a framework for simulating restenosis; the next step will be to couple it with more patient-specific geometries and quantitative parameter data.

In Silico Prediction of the Mechanobiological Response of Arterial Tissue: Application to Angioplasty and Stenting

One way to restore physiological blood flow to occluded arteries involves the deformation of plaque using an intravascular balloon and preventing elastic recoil using a stent. Angioplasty and stent implantation cause unphysiological loading of the arterial tissue, which may lead to tissue in-growth and reblockage; termed “restenosis.” In this paper, a computational methodology for predicting the time-course of restenosis is presented. Stress-induced damage, computed using a remaining life approach, stimulates inflammation (production of matrix degrading factors and growth stimuli). This, in turn, induces a change in smooth muscle cell phenotype from contractile (as exists in the quiescent tissue) to synthetic (as exists in the growing tissue). In this paper, smooth muscle cell activity (migration, proliferation, and differentiation) is simulated in a lattice using a stochastic approach to model individual cell activity. The inflammation equations are examined under simplified loading cases. The mechanobiological parameters of the model were estimated by calibrating the model response to the results of a balloon angioplasty study in humans. The simulation method was then used to simulate restenosis in a two dimensional model of a stented artery. Cell activity predictions were similar to those observed during neointimal hyperplasia, culminating in the growth of restenosis. Similar to experiment, the amount of neointima produced increased with the degree of expansion of the stent, and this relationship was found to be highly dependant on the prescribed inflammatory response. It was found that the duration of inflammation affected the amount of restenosis produced, and that this effect was most pronounced with large stent expansions. In conclusion, the paper shows that the arterial tissue response to mechanical stimulation can be predicted using a stochastic cell modeling approach, and that the simulation captures features of restenosis development observed with real stents. The modeling approach is proposed for application in three dimensional models of cardiovascular stenting procedures.

Application of a mechanobiological simulation technique to stents used clinically

Many cardiovascular diseases are characterised by the restriction of blood flow through arteries. Stents can be expanded within arteries to remove such restrictions; however, tissue in-growth into the stent can lead to restenosis. In order to predict the long-term efficacy of stenting, a mechanobiological model of the arterial tissue reaction to stress is required. In this study, a computational model of arterial tissue response to stenting is applied to three clinically relevant stent designs. We ask the question whether such a mechanobiological model can differentiate between stents used clinically, and we compare these predictions to a purely mechanical analysis. In doing so, we are testing the hypothesis that a mechanobiological model of arterial tissue response to injury could predict the long-term outcomes of stent design. Finite element analysis of the expansion of three different stent types was performed in an idealised, 3D artery. Injury was calculated in the arterial tissue using a remaining-life damage mechanics approach. The inflammatory response to this initial injury was modelled using equations governing variables which represented tissue-degrading species and growth factors. Three levels of inflammation response were modelled to account for inter-patient variability. A lattice-based model of smooth muscle cell behaviour was implemented, treating cells as discrete agents governed by local rules. The simulations predicted differences between stent designs similar to those found in vivo. It showed that the volume of neointima produced could be quantified, providing a quantitative comparison of stents. In contrast, the differences between stents based on stress alone were highly dependent on the choice of comparison criteria. These results show that the choice of stress criteria for stent comparisons is critical. This study shows that mechanobiological modelling may provide a valuable tool in stent design, allowing predictions of their long-term efficacy. The level of inflammation was shown to affect the sensitivity of the model to stent design. If this finding was verified in patients, this could suggest that high-inflammation patients may require alternative treatments to stenting.

Epigenetics in Vascular Disease - Therapeutic Potential of New Agents

Vascular diseases, including atherosclerosis, angioplasty-induced restenosis, vessel graft arteriosclerosis and hypertension-related stenosis, remain the most prevalent cause of death in the developed world. The aetiology of vascular diseases is multifactorial with both genetic and environmental factors. Recently, some of the most promising research identifies the epigenetic modification of the genome to play a major role in the disease development, linking the environmental insults with gene regulation. In this process, modification of DNA by methylation, and histone modification by acetylation, methylation, phosphorylation and/or SUMOylation are reported. Importantly, recent studies demonstrated that histone deacetylase (HDAC) enzymes are crucial in endothelial integrity, smooth muscle proliferation and in the formation of arteriosclerosis in animal models. The study of HDACs has shown remarkable specificity of HDAC family members in vascular cell growth/death that influences the disease process. Interestingly, the effects of HDACs on arteriosclerosis development in animal models have been observed after HDAC inhibition using specific inhibitors. This provides a new approach for the treatment of vascular disease using the agents that influence the epigenetic process in vascular cells. This review updates the rapid advances in epigenetics of vascular diseases focusing on the role of HDAC family in atherosclerosis. It will also discuss the underlying mechanisms of histone acetylation in vascular cells and highlight the therapeutic potential of such agents.

Sirolimus Stimulates Vascular Stem/Progenitor Cell Migration and Differentiation Into Smooth Muscle Cells via Epidermal Growth Factor Receptor/Extracellular Signal-Regulated Kinase/β-Catenin Signaling Pathway

Sirolimus-eluting stent therapy has achieved considerable success in overcoming coronary artery restenosis. However, there remain a large number of patients presenting with restenosis after the treatment, and the source of its persistence remains unclarified. Although recent evidence supports the contribution of vascular stem/progenitor cells in restenosis formation, their functional and molecular responses to sirolimus are largely unknown.