Investigating the effect of drug release on in-stent restenosis: A hybrid continuum - agent-based modelling approach

Physiological consequences of half-embedded drug-eluting stent on coronary drug-transport: A two-species drug delivery simulation

Drug-eluting stent (DES) is commonly utilized to open blocked arteries and reduce in-stent restenosis (ISR) brought on by the implantation of bare-metal stent (BMS). The current mathematical model sheds light on investigating the physiological effects of different clinical parameters on drug distribution and retention within the artery wall. A two-dimensional (2D) axisymmetric cylindrical model of a typical Palmaz stent having circular struts coated with a bio-durable polymer is half-embedded in the tissue. This investigation considers two distinct drug phases - the unbound and bound phases - in the artery wall. The artery wall is considered a porous medium, and the Brinkman equation governs the interstitial fluid (ISF) flow within it. An unsteady convection-diffusion-reaction mechanism governs unbound drug transport, while that of bound drug is solely controlled by an unsteady chemical reaction. The drug delivery system also includes a reversible equilibrium mechanism to maintain the chemical reaction between the drug molecules and the receptors. Drug and momentum transport equations are solved using the Marker-and-Cell (MAC) method in staggered grid setups with appropriate initial and boundary conditions. According to simulations, there is going to be a bi-phasic decrease in unbound drug in the artery wall with a larger binding-on constant (ψ), and the concentration of both drug forms and the area under concentration decrease as the Peclet number (Pe) increases. Additionally, as the equilibrium association constant (keq) increases, the concentration of the unbound drug decreases, but the tendency for the bound drug is reversed. The sensitivity of some significant parameters has been examined in a thorough sensitivity study. Our results are in excellent agreement with the findings available in the literature.

Drug coated balloons in percutaneous coronary intervention: how can computational modelling help inform evolving clinical practice?

Drug-coated balloons (DCB) represent an emerging therapeutic alternative to drug-eluting stents (DES) for the treatment of coronary artery disease (CAD). Among the key advantages of DCB over DES are the absence of a permanent structure in the vessel and the potential for fast and homogeneous drug delivery. While DCB were first introduced for treatment of in-stent restenosis (ISR), their potential wider use in percutaneous coronary intervention (PCI) has recently been explored in several randomized clinical trials, including for treatment of de novo lesions. Moreover, new hybrid techniques that combine DES and DCB are being investigated to more effectively tackle complex cases. Despite the growing interest in DCB within the clinical community, the mechanisms of drug exchange and the interactions between the balloon, the polymeric coating and the vessel wall are yet to be fully understood. It is, therefore, perhaps surprising that the number of computational (in silico) models developed to study interventions involving these devices is small, especially given the mechanistic understanding that has been gained from computational studies of DES procedures over the last two decades. In this paper, we discuss the current and emerging clinical approaches for DCB use in PCI and review the computational models that have been developed thus far, underlining the potential challenges and opportunities in integrating in silico models of DCB into clinical practice.

A Numerical Study on the Drug Release Process of Biodegradable Polymer Drug-Loaded Vascular Stents

Biodegradable polymer drug-loaded vascular stents are a typical and promising application in the field of invasive interventional therapy. The drug release process of drug-loaded vascular stents, as well as the drug concentration in the vascular wall and its change process, will affect the therapeutic effect of vascular stents on vascular stenosis. As a drug carrier, the degradation properties of the polymer will affect the drug release process. In this study, the drug release process from the biodegradable polymer stent and the drug delivery process in vascular lumens and intravascular walls were studied by using 3D finite element method, with the effect of the biodegradation behavior of polymer on the drug release process being considered. The effects of the initial drug concentration, stent geometry, and polymer degradation rate on the drug release and delivery process were investigated. The results showed that the initial drug concentration and the thickness of the polymer stent significantly affected the drug concentration in the middle layer of the vessel wall, but the initial drug concentration had no effect on the drug release duration. The degradation of the polymer causes its porosity to change with time, which affects the drug diffusion in polymer, and further affects the drug concentration in the vessel wall. The three-dimensional structure of the stent can affect the blood flow in the blood vessel, resulting in drug deposition near the struts, especially near the intersection of the support struts and the bridge struts.

A review of computational methodologies to predict the fractional flow reserve in coronary arteries with stenosis

Computational methodologies for predicting the fractional flow reserve (FFR) in coronary arteries with stenosis have gained significant attention due to their potential impact on healthcare outcomes. Coronary artery disease is a leading cause of mortality worldwide, prompting the need for accurate diagnostic and treatment approaches. The use of medical image-based anatomical vascular geometries in computational fluid dynamics (CFD) simulations to evaluate the hemodynamics has emerged as a promising tool in the medical field. This comprehensive review aims to explore the state-of-the-art computational methodologies focusing on the possible considerations. Key aspects include the rheology of blood, boundary conditions, fluid-structure interaction (FSI) between blood and the arterial wall, and multiscale modelling (MM) of stenosis. Through an in-depth analysis of the literature, the goal is to obtain an overview of the major achievements regarding non-invasive methods to compute FFR and to identify existing gaps and challenges that inform further advances in the field. This research has the major objective of improving the current diagnostic capabilities and enhancing patient care in the context of cardiovascular diseases.

Plaque heterogeneity influences in-stent restenosis following drug-eluting stent implantation: Insights from patient-specific multiscale modelling

In-stent restenosis represents a major cause of failure of percutaneous coronary intervention with drug-eluting stent implantation. Computational multiscale models have recently emerged as powerful tools for investigating the mechanobiological mechanisms underlying vascular adaptation processes during in-stent restenosis. However, to date, the interplay between intervention-induced inflammation, drug delivery and drug retention has been under-investigated. Here, an original patient-specific multiscale agent-based modelling framework was developed to investigate the interplay between drug release, plaque composition and intervention-induced inflammation on in-stent restenosis following drug-eluting stent implantation. The framework integrated a finite element simulation of stent expansion, with a drug transport simulation and an agent-based model of cellular dynamics. A patient-specific coronary cross-section with heterogeneous diseased tissue was considered and rigorously analyzed through a variety of scenarios, including different plaque compositions and different inflammatory responses. The analysis revealed three significant findings: (i) calcifications substantially impeded drug transport, resulting in drug-depleted regions and reduced stent efficacy; (ii) by impacting drug transport, variations in plaque composition influenced arterial wall response, with the fully-calcific scenario showing the greatest lumen area reduction; (iii) the impact of different drug receptor saturation conditions (obtained with different plaque compositions) was particularly evident under conditions of persistent inflammatory state. This study represents a significant advancement in multiscale modelling of in-stent restenosis following drug-eluting stent implantation. The results obtained provided deeper insights into the complex interactions among patient-specific plaque composition, inflammation and drug retention, suggesting a patient-specific management of the intervention, particularly in cases of complex disease.

A quantitative study of the effects of a dual layer coating drug-eluting stent on safety and efficacy

A key strategy for increasing drug mass (DM) while maintaining good safety is to improve the drug release profile (RP). We designed a dual layer coating drug-eluting stent (DES) that exhibited smaller concentration gradients between the coating and the artery wall and significantly impacted the drug RP. However, a detailed understanding of the effects of the DES designed by our team on safety and efficacy is still lacking. The objective of this study was to provide a comprehensive multiscale computational framework that would allow us to probe the safety and efficacy of the DES we designed. This framework consisted of four coupled modules, namely (1) a mechanical stimuli module, simulating mechanical stimuli caused by percutaneous coronary intervention through a finite element analysis, (2) an inflammation module, simulating inflammation of vascular smooth muscle cells (VSMCs) induced by mechanical stimuli through an agent-based model (ABM), (3) a drug transport module, simulating drug transport through a continuum-based approach, and (4) a mitosis module, simulating VSMC mitosis through an ABM. Our results indicated that when the DM increased to two times the initial DM value, the DES we designed had higher safety and lower efficacy values than a conventional DES. When the DM increased to five times the initial DM value, the DES we designed had higher safety than a conventional DES, and negligible differences in efficacy compared with a conventional DES. In summary, the DES we designed exhibited a significant advantage in safety, but a slightly reduced efficacy compared with that of a conventional DES.

Impact of Tissue Damage and Hemodynamics on Restenosis Following Percutaneous Transluminal Angioplasty: A Patient-Specific Multiscale Model

Multiscale agent-based modeling frameworks have recently emerged as promising mechanobiological models to capture the interplay between biomechanical forces, cellular behavior, and molecular pathways underlying restenosis following percutaneous transluminal angioplasty (PTA). However, their applications are mainly limited to idealized scenarios. Herein, a multiscale agent-based modeling framework for investigating restenosis following PTA in a patient-specific superficial femoral artery (SFA) is proposed. The framework replicates the 2-month arterial wall remodeling in response to the PTA-induced injury and altered hemodynamics, by combining three modules: (i) the PTA module, consisting in a finite element structural mechanics simulation of PTA, featuring anisotropic hyperelastic material models coupled with a damage formulation for fibrous soft tissue and the element deletion strategy, providing the arterial wall damage and post-intervention configuration, (ii) the hemodynamics module, quantifying the post-intervention hemodynamics through computational fluid dynamics simulations, and (iii) the tissue remodeling module, based on an agent-based model of cellular dynamics. Two scenarios were explored, considering balloon expansion diameters of 5.2 and 6.2 mm. The framework captured PTA-induced arterial tissue lacerations and the post-PTA arterial wall remodeling. This remodeling process involved rapid cellular migration to the PTA-damaged regions, exacerbated cell proliferation and extracellular matrix production, resulting in lumen area reduction up to 1-month follow-up. After this initial reduction, the growth stabilized, due to the resolution of the inflammatory state and changes in hemodynamics. The similarity of the obtained results to clinical observations in treated SFAs suggests the potential of the framework for capturing patient-specific mechanobiological events occurring after PTA intervention.

A multiscale modeling study of nanoparticle-based targeting therapy against atherosclerosis

Although researches on nanoparticle-based (NP-based) drug delivery system for atherosclerosis treatment have grown rapidly in recent years, there are limited studies in quantifying the effects of targeting drugs on plaque components and microenvironment. The purpose of the present study was to quantitatively assess the targeting therapeutic effects against atherosclerosis by establishing a multiscale mathematical model. The multiscale model involved subcellular, cellular and microenvironmental scales to simulate lipid catabolism, macrophage behaviors and dynamics of microenvironmental components, respectively. In vitro and in vivo experimental data were integrated into the mathematical model according to Bayesian statistics, in order to evaluate the therapeutic effects of a proposed NP-based platform for macrophage-specific delivery to simultaneously deliver SR-A siRNA (to reduce LDL uptake) and LXR-L (to stimulate cholesterol efflux). Dosage variation analysis was then performed to investigate the drug efficacy under varied dosage combinations of SR-A siRNA and LXR-L. The simulation results demonstrated that the dynamics of the microenvironmental components presented different developments in Untreated and Treated groups. We also found that the balance of lipid metabolism between uptake and efflux resulted in the improvement of lipid and inflammatory microenvironment, consequently in the plaque regression. In addition, the model predicted optimized dosage combinations according to the co-effect analysis of the two drugs on the lipid microenvironment. This study suggests that multiscale modeling can be a powerful quantitative tool for estimating the therapeutic effects of targeting drugs for plaque regression and designing the enhanced treatment strategies against atherosclerosis.

An agent-based model of cardiac allograft vasculopathy: toward a better understanding of chronic rejection dynamics

Cardiac allograft vasculopathy (CAV) is a coronary artery disease affecting 50% of heart transplant (HTx) recipients, and it is the major cause of graft loss. CAV is driven by the interplay of immunological and non-immunological factors, setting off a cascade of events promoting endothelial damage and vascular dysfunction. The etiology and evolution of tissue pathology are largely unknown, making disease management challenging. So far, in vivo models, mostly mouse-based, have been widely used to study CAV, but they are resource-consuming, pose many ethical issues, and allow limited investigation of time points and important biomechanical measurements. Recently, agent-based models (ABMs) proved to be valid computational tools for deciphering mechanobiological mechanisms driving vascular adaptation processes at the cell/tissue level, augmenting cost-effective in vivo lab-based experiments, at the same time guaranteeing richness in observation time points and low consumption of resources. We hypothesize that integrating ABMs with lab-based experiments can aid in vivo research by overcoming those limitations. Accordingly, this work proposes a bidimensional ABM of CAV in a mouse coronary artery cross-section, simulating the arterial wall response to two distinct stimuli: inflammation and hemodynamic disturbances, the latter considered in terms of low wall shear stress (WSS). These stimuli trigger i) inflammatory cell activation and ii) exacerbated vascular cell activities. Moreover, an extensive analysis was performed to investigate the ABM sensitivity to the driving parameters and inputs and gain insights into the ABM working mechanisms. The ABM was able to effectively replicate a 4-week CAV initiation and progression, characterized by lumen area decrease due to progressive intimal thickening in regions exposed to high inflammation and low WSS. Moreover, the parameter and input sensitivity analysis highlighted that the inflammatory-related events rather than the WSS predominantly drive CAV, corroborating the inflammatory nature of the vasculopathy. The proof-of-concept model proposed herein demonstrated its potential in deepening the pathology knowledge and supporting the in vivo analysis of CAV.