Computational Modeling of Passive Micronanoplastic Transport in an Image-Based Model of the Right Coronary Artery.

Micro- and nanoplastics (MNPs) are polymeric pollutants receiving growing attention for their persistence, widespread distribution and potential health risks. Based on the origin, they are classified as primary MNPs, industrially produced, or secondary MNPs, formed by degradation of larger plastic debris. Due to their small size, MNPs can spread in the environment and enter the human body through ingestion and inhalation, crossing biological barriers to reach the circulatory system. Recently, polyethylene and polyvinyl chloride MNP particles have been detected within atherosclerotic plaques in carotid arteries of patients undergoing atherectomy. Furthermore, patients with MNPs in their atherosclerotic plaques exhibited significantly increased risk of myocardial infarction, stroke, or all-cause mortality, indicating a possible role in cardiovascular diseases worsening. These findings provide direct evidence that MNPs can accumulate in the vascular system, suggesting a potential role in the worsening of cardiovascular diseases. Understanding MNP distribution in the vascular system requires tools capable to replicate complex hemodynamics and particle transport/transfer to the vascular wall. Computational Fluid Dynamics (CFD) offers an effective in silico approach for high-resolution simulations of blood flow and particle transport in patient-specific vascular geometries. In this context, this thesis aims to develop a CFD model to simulate passive transport of MNP particles within a 3D model of a right coronary artery segment reconstructed from angiographic images, investigating the impact of (i) flow rate, (ii) MNP particle size, and (iii) stenosis severity on MNPs’ luminal distribution. CFD simulations were performed under steady-state flow conditions using the finite-volume software Fluent (Ansys Inc.). MNPs transport was modeled by solving the advection-diffusion equation for a passive scalar, coupled with the Navier-Stokes equations governing blood flow. This approach builds upon frameworks used for low-density lipoprotein transport, adapted to MNP dynamics. Particle-wall interactions were introduced through a user-defined function. Diffusivity for 1µm-diameter MNPs was calculated using the Stokes-Einstein equation. A mesh independence study was conducted to determine the appropriate number of boundary layers, identifying 30 layers as the optimal balance between accurate near-wall resolution and computational efficiency. Using this mesh configuration, three sensitivity analyses were performed, focusing on flow rate, particle size and geometry. Flow rate variation (±50% from baseline) showed that reduced flow promotes particle accumulation at the luminal wall, while increased flow enhances particle clearance. Particle size investigation across the 1 nm to 10 µm range revealed an inverse relationship between diameter and wall deposition, with the smallest particles exhibiting the highest accumulation due to enhanced diffusivity. Geometric analysis with progressively increasing stenosis showed that lumen narrowing substantially modifies MNP distribution patterns along the luminal wall. This work presents a first computational model for simulating vascular transport of MNPs, laying foundation for advanced in silico analyses. Integrating CFD with anatomically accurate vascular geometries offers valuable insights into near-wall particle dynamics, supporting future studies aiming to identify vascular regions prone to MNP accumulation and assess their role in atherosclerosis progression.