| Abstract: Atherosclerosis is a local inflammatory disease characterized by maladaptive build-up of lipids, leukocytes, cholesterol, cellular waste products and extracellular matrix inside the artery wall. The described components contribute to plaque development and progression, each of them with proper features and rule-based behavior. Plaque progression is determined by the interaction between these components and the environment in which these components evolve. Agent-based modelling (ABM) is selected as an adequate approach to reproduce the evolution of plaque progression by simulating the behavior of autonomous cellular agents. The agent-based model proved to be a reliable model that is able to predict the history of atherosclerosis development and progression accurately. Our proposed method is based on 2D modelling of cross sections of artery wall and plaque development. Also, our atherosclerosis agent-based model included different characteristics such as behavior of cells and lipid dynamics in a variety of vessel cross-sections. Cell behavior which had a substantial impact on the lumen area, have the highest influence on our model. INTRODUCTION Atherosclerosis is a local inflammatory disease characterized by the recruitment of atheroma (plaques) in the arterial wall. Plaques can be comprised of derived foal cells, lipids, fatty substances, cholesterol, cellular waste products, elastin, collagen, fibrin, calcium and other constituents. The rate of production of these constituents are not identical in different stages of the disease progression. In the beginning, the plaque progression induces artery outwards remodeling to accommodate the volume of the plaque without lumen area reduction. After the initial progression, the remodeling happens towards inside the lumen causing the lumen narrowing which is called stenosis (Figure 1). Figure 1. Different stages of the plaque formation and progression. Depending on the type of the plaque, some can be vulnerable to rupture and cause secondary vascular, sometimes even lethal, outcome for the patient. Initial damages to the endothelium, which is a selective layer, cause an increase in permeability of the layer. Fats integrated into lipoprotein LDL particles are absorbed into the intima by passing the endothelium lining. Some of these LDL particles become oxidized and this attracts monocytes, which differentiate into macrophages that uptake the particles. Due to these activates, cytokines are released, which in turn attract more monocytes. Artery wall is at fatty streak stage now. In some regions of increased macrophage activity, macrophage-induced-enzymes erode the fibrous membrane beneath the endothelium so that the cover separating the plaque from blood flow in the lumen becomes thin and fragile, vulnerable to rupture. The problem stated above describes numerous components contributing to plaque creation and progression, each one with proper characteristics, behavior, and rulesets. The interaction between these components and the environment in which they evolve determines the plaque progression. For this reason, we selected ABM as the proper approach to mimic the evolution of plaque progression and artery reshaping (dynamical system) by simulating the behavior of autonomous cellular components (agents). We hypothesize that ABM model represents a reliable model that can describe properly history of atherosclerosis development. When the response of complex biological systems strictly depends on cellular behaviors, which in turn are influenced by the changes in the micro-environmental factors, a multi-scale modelling approach is preferable. Pappalardo et al. [1] developed agent-based model to describe the very early stage of the atherosclerosis, the stage before formation of a calcified plaque. Deo et al. [2] also used an ABM to simulate inflammatory processes in atherosclerosis, particularly focusing on plaque formation and rupture. Curtin et al. [3] instead developed a two-dimensional grid space ABM to simulate the restenosis development in a blood vessel following an angioplasty and bare-metal stent implantation. They showed the body’s response to the intervention and explored how different vessel geometries or stent arrangements may affect restenosis development. Starting from the post-procedural vessel lumen diameter and stent information, they generated the final lumen diameter, the percent change in lumen cross-sectional area, the time to lumen diameter stabilization, and the local concentrations of inflammatory cytokines. Olivares et al. [4] also developed a 3D ABM to simulate relevant cellular and molecular phenomena involved in the early formation |