Application of a mechanobiological simulation technique to stents used clinically

An intricate interplay between stent drug dose and release rate dictates arterial restenosis

Since the introduction of percutaneous coronary intervention (PCI) for the treatment of obstructive coronary artery disease (CAD), patient outcomes have progressively improved. Drug eluting stents (DES) that employ anti-proliferative drugs to limit excess tissue growth following stent deployment have proved revolutionary. However, restenosis and a need for repeat revascularisation still occurs after DES use. Over the last few years, computational models have emerged that detail restenosis following the deployment of a bare metal stent (BMS), focusing primarily on contributions from mechanics and fluid dynamics. However, none of the existing models adequately account for spatiotemporal delivery of drug and the influence of this on the cellular processes that drive restenosis. In an attempt to fill this void, a novel continuum restenosis model coupled with spatiotemporal drug delivery is presented. Our results indicate that the severity and time-course of restenosis is critically dependent on the drug delivery strategy. Specifically, we uncover an intricate interplay between initial drug loading, drug release rate and restenosis, indicating that it is not sufficient to simply ramp-up the drug dose or prolong the time course of drug release to improve stent efficacy. Our model also shows that the level of stent over-expansion and stent design features, such as inter-strut spacing and strut thickness, influence restenosis development, in agreement with trends observed in experimental and clinical studies. Moreover, other critical aspects of the model which dictate restenosis, including the drug binding site density are investigated, where comparisons are made between approaches which assume this to be either constant or proportional to the number of smooth muscle cells (SMCs). Taken together, our results highlight the necessity of incorporating these aspects of drug delivery in the pursuit of optimal DES design.

Mechano-chemo-biological Computational Models for Arteries in Health, Disease and Healing: From Tissue Remodelling to Drug-eluting Devices

This review aims to highlight urgent priorities for the computational biomechanics community in the framework of mechano-chemo-biological models. Recent approaches, promising directions and open challenges on the computational modelling of arterial tissues in health and disease are introduced and investigated, together with in silico approaches for the analysis of drug-eluting stents that promote pharmacological-induced healing. The paper addresses a number of chemo-biological phenomena that are generally neglected in biomechanical engineering models but are most likely instrumental for the onset and the progression of arterial diseases. An interdisciplinary effort is thus encouraged for providing the tools for an effective in silico insight into medical problems. An integrated mechano-chemo-biological perspective is believed to be a fundamental missing piece for crossing the bridge between computational engineering and life sciences, and for bringing computational biomechanics into medical research and clinical practice.

Computational and experimental mechanical performance of a new everolimus-eluting stent purpose-built for left main interventions

Left main (LM) coronary artery bifurcation stenting is a challenging topic due to the distinct anatomy and wall structure of LM. In this work, we investigated computationally and experimentally the mechanical performance of a novel everolimus-eluting stent (SYNERGY MEGATRON) purpose-built for interventions to large proximal coronary segments, including LM. MEGATRON stent has been purposefully designed to sustain its structural integrity at higher expansion diameters and to provide optimal lumen coverage. Four patient-specific LM geometries were 3D reconstructed and stented computationally with finite element analysis in a well-validated computational stent simulation platform under different homogeneous and heterogeneous plaque conditions. Four different everolimus-eluting stent designs (9-peak prototype MEGATRON, 10-peak prototype MEGATRON, 12-peak MEGATRON, and SYNERGY) were deployed computationally in all bifurcation geometries at three different diameters (i.e., 3.5, 4.5, and 5.0 mm). The stent designs were also expanded experimentally from 3.5 to 5.0 mm (blind analysis). Stent morphometric and biomechanical indices were calculated in the computational and experimental studies. In the computational studies the 12-peak MEGATRON exhibited significantly greater expansion, better scaffolding, smaller vessel prolapse, and greater radial strength (expressed as normalized hoop force) than the 9-peak MEGATRON, 10-peak MEGATRON, or SYNERGY (p < 0.05). Larger stent expansion diameters had significantly better radial strength and worse scaffolding than smaller stent diameters (p < 0.001). Computational stenting showed comparable scaffolding and radial strength with experimental stenting. 12-peak MEGATRON exhibited better mechanical performance than the 9-peak MEGATRON, 10-peak MEGATRON, or SYNERGY. Patient-specific computational LM stenting simulations can accurately reproduce experimental stent testing, providing an attractive framework for cost- and time-effective stent research and development.

Effects of local coronary blood flow dynamics on the predictions of a model of in-stent restenosis

Computational models are increasingly used to study cardiovascular disease. However, models of coronary vessel remodelling usually make some strong assumptions about the effects of a local narrowing on the flow through the narrowed vessel. Here, we test the effects of local flow dynamics on the predictions of an in-stent restenosis (ISR) model. A previously developed 2D model of ISR is coupled to a 1D model of coronary blood flow. Then, two different assumptions are tested. The first assumption is that the vasculature is always able to adapt, and the volumetric flow rate through the narrowed vessel is kept constant. The second, alternative, assumption is that the vasculature does not adapt at all, and the ratio of the pressure drop to the flow rate (hydrodynamic resistance) stays the same throughout the whole process for all vessels unaffected by the stenosis, and aortic or venous blood pressure does not change either. Then, the dynamics are compared for different locations in coronary tree for two different reendothelization scenarios. The assumptions of constant volumetric flow rate (absolute vascular adaptation) versus constant aortic pressure drop and no adaptation do not significantly affect the growth dynamics for most locations in the coronary tree, and the differences can only be observed at the locations where a strong alternative flow pathway is present. On the other hand, the difference between locations is significant, which is consistent with small vessel size being a risk factor for restenosis. These results suggest that the assumption of a constant flow is a good approximation for ISR models dealing with the typical progression of ISR in the most often stented locations such as the proximal parts of left anterior descending (LAD) and left circumflex (LCX) arteries.

Mechanistic evaluation of long-term in-stent restenosis based on models of tissue damage and growth

Development and application of advanced mechanical models of soft tissues and their growth represent one of the main directions in modern mechanics of solids. Such models are increasingly used to deal with complex biomedical problems. Prediction of in-stent restenosis for patients treated with coronary stents remains a highly challenging task. Using a finite element method, this paper presents a mechanistic approach to evaluate the development of in-stent restenosis in an artery following stent implantation. Hyperelastic models with damage, verified with experimental results, are used to describe the level of tissue damage in arterial layers and plaque caused by such intervention. A tissue-growth model, associated with vessel damage, is adopted to describe the growth behaviour of a media layer after stent implantation. Narrowing of lumen diameter with time is used to quantify the development of in-stent restenosis in the vessel after stenting. It is demonstrated that stent designs and materials strongly affect the stenting-induced damage in the media layer and the subsequent development of in-stent restenosis. The larger the artery expansion achieved during balloon inflation, the higher the damage introduced to the media layer, leading to an increased level of in-stent restenosis. In addition, the development of in-stent restenosis is directly correlated with the artery expansion during the stent deployment. The correlation is further used to predict the effect of a complex clinical procedure, such as stent overlapping, on the level of in-stent restenosis developed after percutaneous coronary intervention.

Location-Specific Comparison Between a 3D In-Stent Restenosis Model and Micro-CT and Histology Data from Porcine In Vivo Experiments

BACKGROUND

Coronary artery restenosis is an important side effect of percutaneous coronary intervention. Computational models can be used to better understand this process. We report on an approach for validation of an in silico 3D model of in-stent restenosis in porcine coronary arteries and illustrate this approach by comparing the modelling results to in vivo data for 14 and 28 days post-stenting.

METHODS

This multiscale model includes single-scale models for stent deployment, blood flow and tissue growth in the stented vessel, including smooth muscle cell (SMC) proliferation and extracellular matrix (ECM) production. The validation procedure uses data from porcine in vivo experiments, by simulating stent deployment using stent geometry obtained from micro computed tomography (micro-CT) of the stented vessel and directly comparing the simulation results of neointimal growth to histological sections taken at the same locations.

RESULTS

Metrics for comparison are per-strut neointimal thickness and per-section neointimal area. The neointimal area predicted by the model demonstrates a good agreement with the detailed experimental data. For 14 days post-stenting the relative neointimal area, averaged over all vessel sections considered, was 20 ± 3% in vivo and 22 ± 4% in silico. For 28 days, the area was 42 ± 3% in vivo and 41 ± 3% in silico.

CONCLUSIONS

The approach presented here provides a very detailed, location-specific, validation methodology for in silico restenosis models. The model was able to closely match both histology datasets with a single set of parameters. Good agreement was obtained for both the overall amount of neointima produced and the local distribution. It should be noted that including vessel curvature and ECM production in the model was paramount to obtain a good agreement with the experimental data.

Computational modelling of magnesium stent mechanical performance in a remodelling artery: Effects of multiple remodelling stimuli

Significant research has been conducted in the area of coronary stents/scaffolds made from resorbable metallic and polymeric biomaterials. These next-generation bioabsorbable stents have the potential to completely revolutionise the treatment of coronary artery disease. The primary advantage of resorbable devices over permanent stents is their temporary presence which, from a theoretical point of view, means only a healed coronary artery will be left behind following degradation of the stent potentially eliminating long-term clinical problems associated with permanent stents. The healing of the artery following coronary stent/scaffold implantation is crucial for the long-term safety of these devices. Computational modelling can be used to evaluate the performance of complex stent devices in silico and assist in the design and development and understanding of the next-generation resorbable stents. What is lacking in computational modelling literature is the representation of the active response of the arterial tissue in the weeks and months following stent implantation, ie, neointimal remodelling, in particular for the case of biodegradable stents. In this paper, a computational modelling framework is developed, which accounts for two major physiological stimuli responsible for neointimal remodelling and combined with a magnesium corrosion model that is capable of simulating localised pitting (realistic) stent corrosion. The framework is used to simulate different neointimal growth patterns and to explore the effects the neointimal remodelling has on the mechanical performance (scaffolding support) of the bioabsorbable magnesium stent.

Mathematical modelling of the restenosis process after stent implantation

The stenting procedure has evolved to become a highly successful technique for the clinical treatment of advanced atherosclerotic lesions in arteries. However, the development of in-stent restenosis remains a key problem. In this work, a novel two-dimensional continuum mathematical model is proposed to describe the complex restenosis process following the insertion of a stent into a coronary artery. The biological species considered to play a key role in restenosis development are growth factors, matrix metalloproteinases, extracellular matrix, smooth muscle cells and endothelial cells. Diffusion-reaction equations are used for modelling the mass balance between species in the arterial wall. Experimental data from the literature have been used in order to estimate model parameters. Moreover, a sensitivity analysis has been performed to study the impact of varying the parameters of the model on the evolution of the biological species. The results demonstrate that this computational model qualitatively captures the key characteristics of the lesion growth and the healing process within an artery subjected to non-physiological mechanical forces. Our results suggest that the arterial wall response is driven by the damage area, smooth muscle cell proliferation and the collagen turnover among other factors.

Uncertainty Quantification of a Multiscale Model for In-Stent Restenosis

Purpose

Coronary artery stenosis, or abnormal narrowing, is a widespread and potentially fatal cardiac disease. After treatment by balloon angioplasty and stenting, restenosis may occur inside the stent due to excessive neointima formation. Simulations of in-stent restenosis can provide new insight into this process. However, uncertainties due to variability in patient-specific parameters must be taken into account.

Methods

We performed an uncertainty quantification (UQ) study on a complex two-dimensional in-stent restenosis model. We used a quasi-Monte Carlo method for UQ of the neointimal area, and the Sobol sensitivity analysis (SA) to estimate the proportions of aleatory and epistemic uncertainties and to determine the most important input parameters.

Results

We observe approximately 30% uncertainty in the mean neointimal area as simulated by the model. Depending on whether a fast initial endothelium recovery occurs, the proportion of the model variance due to natural variability ranges from 15 to 35%. The endothelium regeneration time is identified as the most influential model parameter.

Conclusion

The model output contains a moderate quantity of uncertainty, and the model precision can be increased by obtaining a more certain value on the endothelium regeneration time. We conclude that the quasi-Monte Carlo UQ and the Sobol SA are reliable methods for estimating uncertainties in the response of complicated multiscale cardiovascular models.

A chemo-mechano-biological formulation for the effects of biochemical alterations on arterial mechanics: the role of molecular transport and multiscale tissue remodelling

This paper presents a chemo-mechano-biological framework for arterial physiopathology. The model accounts for the fine remodelling in the multiscale hierarchical arrangement of tissue constituents and for the diffusion of molecular species involved in cell-cell signalling pathways. Effects in terms of alterations in arterial compliance are obtained. A simple instructive example is introduced. Although oversimplified with respect to realistic case studies, the proposed application mimics the biochemical activity of matrix metalloproteinases, transforming growth factors beta and interleukins on tissue remodelling. Effects of macrophage infiltration, of intimal thickening and of a healing phase are investigated, highlighting the corresponding influence on arterial compliance. The obtained results show that the present approach is able to capture changes in arterial mechanics as a consequence of the alterations in tissue biochemical environment and cellular activity, as well as to incorporate the protective role of both autoimmune responses and pharmacological treatments.

Direct comparison of coronary bare metal vs. drug-eluting stents: same platform, different mechanics?

Background

Drug-eluting stents (DES) compared to bare metal stents (BMS) have shown superior clinical performance, but are considered less suitable in complex cases. Most studies do not distinguish between DES and BMS with respect to their mechanical performance. The objective was to obtain mechanical parameters for direct comparison of BMS and DES.

Methods

In vitro bench tests evaluated crimped stent profiles, crossability in stenosis models, elastic recoil, bending stiffness (crimped and expanded), and scaffolding properties. The study included five pairs of BMS and DES each with the same stent platforms (all n = 5; PRO-Kinetic Energy, Orsiro: BIOTRONIK AG, Bülach, Switzerland; MULTI-LINK 8, XIENCE Xpedition: Abbott Vascular, Temecula, CA; REBEL Monorail, Promus PREMIER, Boston Scientific, Marlborough, MA; Integrity, Resolute Integrity, Medtronic, Minneapolis, MN; Kaname, Ultimaster: Terumo Corporation, Tokyo, Japan). Statistical analysis used pooled variance t tests for pairwise comparison of BMS with DES.

Results

Crimped profiles in BMS groups ranged from 0.97 ± 0.01 mm (PRO-Kinetic Energy) to 1.13 ± 0.01 mm (Kaname) and in DES groups from 1.02 ± 0.01 mm (Orsiro) to 1.13 ± 0.01 mm (Ultimaster). Crossability was best for low profile stent systems. Elastic recoil ranged from 4.07 ± 0.22% (Orsiro) to 5.87 ± 0.54% (REBEL Monorail) including both BMS and DES. The bending stiffness of crimped and expanded stents showed no systematic differences between BMS and DES neither did the scaffolding.

Conclusions

Based on in vitro measurements BMS appear superior to DES in some aspects of mechanical performance, yet the differences are small and not class uniform. The data provide assistance in selecting the optimal system for treatment and assessment of new generations of bioresorbable scaffolds.

Trial registration: not applicable

Mechanobiological model of arterial growth and remodeling

A coupled agent-based model (ABM) and finite element analysis (FEA) computational framework is developed to study the interplay of bio-chemo-mechanical factors in blood vessels and their role in maintaining homeostasis. The agent-based model implements the power of REPAST Simphony libraries and adapts its environment for biological simulations. Coupling a continuum-level model (FEA) to a cellular-level model (ABM) has enabled this computational framework to capture the response of blood vessels to increased or decreased levels of growth factors, proteases and other signaling molecules (on the micro scale) as well as altered blood pressure. Performance of the model is assessed by simulating porcine left anterior descending artery under normotensive conditions and transient increases in blood pressure and by analyzing sensitivity of the model to variations in the rule parameters of the ABM. These simulations proved that the model is stable under normotensive conditions and can recover from transient increases in blood pressure. Sensitivity studies revealed that the model is most sensitive to variations in the concentration of growth factors that affect cellular proliferation and regulate extracellular matrix composition (mainly collagen).

A Comparison of Fully-Coupled 3D In-Stent Restenosis Simulations to In-vivo Data

We describe our fully-coupled 3D multiscale model of in-stent restenosis, with blood flow simulations coupled to smooth muscle cell proliferation, and report results of numerical simulations performed with this model. This novel model is based on several previously reported 2D models. We study the effects of various parameters on the process of restenosis and compare with in vivo porcine data where we observe good qualitative agreement. We study the effects of stent deployment depth (and related injury score), reendothelization speed, and simulate the effect of stent width. Also we demonstrate that we are now capable to simulate restenosis in real-sized (18 mm long, 2.8 mm wide) vessel geometries.

Computational Modeling of the Mechanical Performance of a Magnesium Stent Undergoing Uniform and Pitting Corrosion in a Remodeling Artery

Coronary stents made from degradable biomaterials such as magnesium alloy are an emerging technology in the treatment of coronary artery disease. Biodegradable stents provide mechanical support to the artery during the initial scaffolding period after which the artery will have remodeled. The subsequent resorption of the stent biomaterial by the body has potential to reduce the risk associated with long-term placement of these devices, such as in-stent restenosis, late stent thrombosis, and fatigue fracture. Computational modeling such as finite-element analysis has proven to be an extremely useful tool in the continued design and development of these medical devices. What is lacking in computational modeling literature is the representation of the active response of the arterial tissue in the weeks and months following stent implantation, i.e., neointimal remodeling. The phenomenon of neointimal remodeling is particularly interesting and significant in the case of biodegradable stents, when both stent degradation and neointimal remodeling can occur simultaneously, presenting the possibility of a mechanical interaction and transfer of load between the degrading stent and the remodeling artery. In this paper, a computational modeling framework is developed that combines magnesium alloy degradation and neointimal remodeling, which is capable of simulating both uniform (best case) and localized pitting (realistic) stent corrosion in a remodeling artery. The framework is used to evaluate the effects of the neointima on the mechanics of the stent, when the stent is undergoing uniform or pitting corrosion, and to assess the effects of the neointimal formation rate relative to the overall stent degradation rate (for both uniform and pitting conditions).

A Multiscale Computational Framework to Understand Vascular Adaptation

The failure rate for vascular interventions (vein bypass grafting, arterial angioplasty/stenting) remains unacceptably high. Over the past two decades, researchers have applied a wide variety of approaches to investigate the primary failure mechanisms, neointimal hyperplasia and aberrant remodeling of the wall, in an effort to identify novel therapeutic strategies. Despite incremental progress, specific cause/effect linkages among the primary drivers of the pathology, (hemodynamic factors, inflammatory biochemical mediators, cellular effectors) and vascular occlusive phenotype remain lacking. We propose a multiscale computational framework of vascular adaptation to develop a bridge between theory and experimental observation and to provide a method for the systematic testing of relevant clinical hypotheses. Cornerstone to our model is a feedback mechanism between environmental conditions and dynamic tissue plasticity described at the cellular level with an agent based model. Our implementation (i) is modular, (ii) starts from basic mechano-biology principle at the cell level and (iii) facilitates the agile development of the model.

DIAGNOSTIC AND THERAPEUTIC TREATMENTS OF PLAQUES IN THE CAROTID BIFURCATION — STUDIES IN MODELS WITH STENTS AND FILTERS

Fluid dynamics, especially forces and velocity distribution, influence the development of plaques. Flow parameters: pulsatility, the non-Newtonian flow behavior of blood and wall elasticity are considered. Flow visualization techniques (dyes and birefringent solution with a photo-elasticity apparatus) and LDA measurements demonstrate the importance of the flow. Accurate in vivo velocity measurements are necessary to calculate shear stresses. Different bifurcation angles and flow rate ratios were tested in true to life artery models. The most important fluid dynamic factors at bifurcations are the flow rate ratio and the geometry which create flow separation regions which are responsible for platelet aggregation and intima damage. It is necessary to measure all three velocity components to calculate the velocity vector. The highest shear stresses in a healthy carotid artery are 16 Pa and are found just at the apex. In artery models with 90% stenosis, shear stresses up to 250 Pa were found. Distally, vortices were created where particles remained over several pulse cycles. Measurements show that stents must be selected carefully and placed precisely. Filters must be closed during the systolic phase before removal, so that no trapped particles can escape.

From Histology and Imaging Data to Models for In-Stent Restenosis

The implantation of stents has been used to treat coronary artery stenosis for several decades. Although stenting is successful in restoring the vessel lumen and is a minimally invasive approach, the long-term outcomes are often compromised by in-stent restenosis (ISR). Animal models have provided insights into the pathophysiology of ISR and are widely used to evaluate candidate drug inhibitors of ISR. Such biological models allow the response of the vessel to stent implantation to be studied without the variation of lesion characteristics encountered in patient studies.

This paper describes the development of complementary in silico models employed to improve the understanding of the biological response to stenting using a porcine model of restenosis. This includes experimental quantification using microCT imaging and histology and the use of this data to establish numerical models of restenosis. Comparison of in silico results with histology is used to examine the relationship between spatial localization of fluid and solid mechanics stimuli immediately post-stenting. Multi-scale simulation methods are employed to study the evolution of neointimal growth over time and the variation in the extent of neointimal hyperplasia within the stented region. Interpretation of model results through direct comparison with the biological response contributes to more detailed understanding of the pathophysiology of ISR, and suggests the focus for follow-up studies.

In conclusion we outline the challenges which remain to both complete our understanding of the mechanisms responsible for restenosis and translate these models to applications in stent design and treatment planning at both population-based and patient-specific levels.