A fully coupled computational fluid dynamics – agent-based model of atherosclerotic plaque development: Multiscale modeling framework and parameter sensitivity analysis

Abstract

Background. Peripheral artery disease (PAD) is an atherosclerotic disorder that leads to unpaired lumen patency through intimal hyperplasia and the build-up of plaques, mainly localized in areas of disturbed flow. Computational models can provide valuable insights in the pathogenesis of atherosclerosis and act as a predictive tool to optimize current interventional techniques. Our hypothesis is that a reliable predictive model must include the atherosclerosis development history. Accordingly, we developed a multiscale modeling framework of atherosclerosis that replicates the hemodynamic-driven arterial wall remodeling and plaque formation. Methods. The framework was based on the coupling of Computational Fluid Dynamics (CFD) simulations with an Agent-Based Model (ABM). The CFD simulation computed the hemodynamics in a 3D artery model, while 2D ABMs simulated cell, extracellular matrix (ECM) and lipid dynamics in multiple vessel cross-sections. A sensitivity analysis was also performed to evaluate the oscillation of the ABM output to variations in the inputs and to identify the most influencing ABM parameters.Results. Our multiscale model qualitatively replicated both the physiologic and pathologic arterial configuration, capturing histological-like features. The ABM outputs were mostly driven by cell and ECM dynamics, largely affecting the lumen area. A subset of parameters was found to affect the final lipid core size, without influencing cell/ECM or lumen area trends. Conclusion.The fully coupled CFD-ABM framework described atherosclerotic morphological and compositional changes triggered by a disturbed hemodynamics.

Effects of the Haemodynamic Stimulus on the Location of Carotid Plaques Based on a Patient-Specific Mechanobiological Plaque Atheroma Formation Model

“…Moreover, it is important to highlight the advantages and disadvantages of our model versus agent-based models (Bhui and Hayenga, 2017 ; Corti et al, 2020 ). The main advantage of our model against versus agent-based models is that using a continuum model allows us to simulate the plaque growth in a real complex 3D geometry with an accessible computational cost.…”

Multiscale Computational Modeling of Vascular Adaptation: A Systems Biology Approach Using Agent-Based Models

“…Both approaches were up to 7-fold faster than the Monte Carlo method and provided acceptable estimates of the uncertainties, thus demonstrating their validity and potentiality in case of computationally intensive analyses. Uncertainty and sensitivity analyses can also be performed to identify the most influencing parameters that drive the model response, whose accurate estimation would result in a great improvement of the model prediction reliability and associated uncertainty reduction (Corti et al, 2020). Indeed, ABMs often depend on many parameters, and their calibration in a single-step process may result ineffective, especially if it is based on the evaluation of few outputs.…”

“… Example of agent-based model (ABM) of vascular wall at the cell-tissue scale implemented on a hexagonal lattice, as in Corti et al (2020) . (A) Three-dimensional patient-specific vessel geometry.…”

“…(D) Lattice-based ABM with agents (cells and ECM) occupying more than one lattice site. The lattice-based ABMs shown in (B–D) are implemented on a hexagonal lattice, as in Corti et al (2020) .…”

“…FIGURE 6 | Results of the computational fluid dynamics-agent-based model (CFD-ABM) framework of atherosclerosis byCorti et al (2020). At the top, the idealized 3D geometry of a superficial femoral artery is represented, with the wall shear stress (WSS) luminal distribution computed from steady-state CFD simulation.…”