A Complex Automata approach for in-stent restenosis: Two-dimensional multiscale modelling and simulations (original) (raw)
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Towards a Complex Automata Multiscale Model of In-Stent Restenosis
In-stent restenosis, the maladaptive response of a blood vessel to injury caused by the deployment of a stent, is a multiscale problem involving a large number of processes. We describe a Complex Automata Model for in-stent restenosis, coupling a bulk flow, drug diffusion, and smooth muscle cell model, all operating on different time scales. Details of the single scale models and of the coupling interfaces are described, together with first simulation results, obtained with a dedicated software environment for Complex Automata simulations. The results show that the model can reproduce growth trends observed in experimental studies.
Journal of the Royal Society Interface, 2022
In-stent restenosis (ISR) is a maladaptive inflammatory-driven response of femoral arteries to percutaneous transluminal angioplasty and stent deployment, leading to lumen re-narrowing as consequence of excessive cellular proliferative and synthetic activities. A thorough understanding of the underlying mechanobiological factors contributing to ISR is still lacking. Computational multiscale models integrating both continuous-and agent-based approaches have been identified as promising tools to capture key aspects of the complex network of events encompassing molecular, cellular and tissue response to the intervention. In this regard, this work presents a multiscale framework integrating the effects of local hemodynamics and monocyte gene expression data on cellular dynamics to simulate ISR mechanobiological processes in a patient-specific model of stented superficial femoral artery. The framework is based on the coupling of computational fluid dynamics simulations (hemodynamics module) with an agent-based model (ABM) of cellular activities (tissue remodeling module). Sensitivity analysis and surrogate modeling combined with genetic algorithm optimization were adopted to explore the model behavior and calibrate the ABM parameters. The proposed framework successfully described the patient lumen area reduction from baseline to 1-month follow-up, demonstrating the potential capabilities of this approach in predicting the short-term arterial response to the endovascular procedure.
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2010
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.
Interface focus, 2011
Neointimal hyperplasia, a process of smooth muscle cell re-growth, is the result of a natural wound healing response of the injured artery after stent deployment. Excessive neointimal hyperplasia following coronary artery stenting results in in-stent restenosis (ISR). Regardless of recent developments in the field of coronary stent design, ISR remains a significant complication of this interventional therapy. The influence of stent design parameters such as strut thickness, shape and the depth of strut deployment within the vessel wall on the severity of restenosis has already been highlighted but the detail of this influence is unclear. These factors impact on local haemodynamics and vessel structure and affect the rate of neointima formation. This paper presents the first results of a multi-scale model of ISR. The development of the simulated restenosis as a function of stent deployment depth is compared with an in vivo porcine dataset. Moreover, the influence of strut size and sh...
International Journal of Design & Nature and Ecodynamics, 2013
Restenosis remains a signifi cant problem in coronary intervention. Additionally, concerns have recently been raised that drug eluting stents (DES) are linked to long-term thrombosis. For carotid artery stenting, the most serious complication is ipsilateral neurologic events due to an acute embolus from fragmentation of the lesion during stent deployment. While much attention has focused on biocompatibility solutions to these problems, less attention has been given to matching stents to the infl ation balloon, atherosclerotic plaque mechanical properties, and lesion shape. Results show that the risk of arterial damage or plaque fractures is dependent on plaque morphology and material properties. Computational modeling results also indicate that it may be possible to use numerical simulations to estimate stress distributions in atherosclerotic lesions in vivo during and after stent deployment. This may help provide clinical indicators in stenting to reduce vascular injury and plaque rupture, which can cause acute and long-term post-procedural lumen loss in coronary artery stenting or stroke in carotid artery stenting. Results also indicate that while a complex model for plaque morphology is necessary to determine the stress distribution within the lesion, a more simple homogeneous plaque model will allow for reasonably accurate predictions of arterial stresses.
Ecology and the Environment, 2012
Restenosis remains a significant problem in coronary intervention. Additionally, concerns have recently been raised that Drug Eluting Stents (DES) are linked to long term thrombosis. For carotid artery stenting, the most serious complication is ipsilateral neurologic events due to an acute embolus from fragmentation of the lesion during stent deployment. While much attention has focused on biocompatibility solutions to these problems, less attention has been given to matching stents to the inflation balloon, atherosclerotic plaque mechanical properties, and lesion shape. Results show that risk of arterial damage or plaque fractures are dependent on plaque morphology and material properties. Computational modeling results also indicate that it may be possible to use numerical simulations to estimate stress distributions in atherosclerotic lesions in vivo during and after stent deployment. This may help provide clinical indicators in stenting to reduce vascular injury and plaque rupture which can cause acute and long term postprocedural lumen loss in coronary artery stenting or stroke in carotid artery stenting. Results also indicate that while a complex model for plaque morphology is necessary to determine the stress distribution within the lesion, a more simple homogeneous plaque model will allow for reasonably accurate predictions of arterial stresses.
Computer Modeling of Stent Deployment and Plaque Progression in the Coronary Arteries
Contemporary Materials, 2018
In this study stent deployment modeling with plaque formation and pro- gression for specific patient in the coronary arteries are described. State of the art method for the reported investigations of blood flow in the stented arteries is described. In the met- hod section, image segmentation method for arteries with stent is shortly described. Blood flow simulation is described with Navier-Stokes and continuity equation. Blood vessel tis- sue is modeled with nonlinear viscoelastic material properties. The coupling of fluid dynamics and solute dynamics at the endothelium was achieved by the Kedem-Katchalsky equations. The inflammatory process is modeled using three additional reaction-diffusion partial differential equations. Coupled method with mixed finite element and DPD (Dissi- pative Particle Dynamics) method is presented. In the results section, the examples with rigid and deformable arterial wall with stented and unstented arteries are presented. Effecti- ve stress analysis re...
Computer Methods in Biomechanics and Biomedical Engineering, 2014
Since their first introduction, stents have revolutionised the treatment of atherosclerosis, however the development of in-stent restenosis still remains the Achilles' heel of stent deployment procedures. Computational modelling can be used as a means to model the biological response of arteries to different stent designs using mechanobiological models whereby the mechanical environment may be used to dictate the growth and remodelling of vascular cells. Changes occurring within the arterial wall due to stent induced mechanical injury, specifically changes within the extracellular matrix have been postulated to be a major cause of activation of vascular smooth muscle cells and the subsequent development of in-stent restenosis. In this study a mechanistic multiscale mechanobiological model of in-stent restenosis using finite element models and agent based modelling is presented which allows quantitative evaluation of the collagen matrix turnover following stent induced arterial injury and the subsequent development of in-stent restenosis. The model is specifically used to study the influence of stent deployment diameter and stent strut thickness on the level of in-stent restenosis. The model demonstrates that there exists a direct correlation between the stent deployment diameter and the level of in-stent restenosis. In addition, investigating the influence of stent strut thickness using the mechanobiological model reveals that thicker strut stents induce a higher level of in-stent restenosis due to a higher extent of arterial injury. The presented mechanobiological modelling framework provides a robust platform for testing hypotheses on the mechanisms underlying the development of in-stent restenosis and lends itself for use as a tool for optimization of the mechanical parameters involved in stent design. Keywords: In-stent restenosis, Multi-scale Mechanobiological Modelling, Agent Based Model (ABM), Finite Element Method (FEM), Matrix metalloproteinase (MMP), Extracellular matrix (ECM) 10.1016/j.biosystems.2004.05.025 Wang WQ, Liang DK, Yang DZ, Qi M. 2006. Analysis of the transient expansion behavior and design optimization of coronary stents by finite element method.
PLoS ONE, 2014
Purpose: While animal models are widely used to investigate the development of restenosis in blood vessels following an intervention, computational models offer another means for investigating this phenomenon. A computational model of the response of a treated vessel would allow investigators to assess the effects of altering certain vessel-and stent-related variables. The authors aimed to develop a novel computational model of restenosis development following an angioplasty and bare-metal stent implantation in an atherosclerotic vessel using agent-based modeling techniques. The presented model is intended to demonstrate the body's response to the intervention and to explore how different vessel geometries or stent arrangements may affect restenosis development. Methods: The model was created on a two-dimensional grid space. It utilizes the post-procedural vessel lumen diameter and stent information as its input parameters. The simulation starting point of the model is an atherosclerotic vessel after an angioplasty and stent implantation procedure. The model subsequently generates the final lumen diameter, percent change in lumen cross-sectional area, time to lumen diameter stabilization, and local concentrations of inflammatory cytokines upon simulation completion. Simulation results were directly compared with the results from serial imaging studies and cytokine levels studies in atherosclerotic patients from the relevant literature. Results: The final lumen diameter results were all within one standard deviation of the mean lumen diameters reported in the comparison studies. The overlapping-stent simulations yielded results that matched published trends. The cytokine levels remained within the range of physiological levels throughout the simulations. Conclusion: We developed a novel computational model that successfully simulated the development of restenosis in a blood vessel following an angioplasty and bare-metal stent deployment based on the characteristics of the vessel crosssection and stent. A further development of this model could ultimately be used as a predictive tool to depict patient outcomes and inform treatment options.