Hemodynamic-Based Evaluation on Thrombosis Risk of Fusiform Coronary Artery Aneurysms Using Computational Fluid Dynamic Simulation Method

Abstract EN

Coronary artery aneurysms (CAAs) have been reported to associate with an increased risk for thrombosis.

Distinct to the brain aneurysm, which can cause a rupture, CAA’s threat is more about its potential to induce thrombosis, leading to myocardial infarction.

Case reports suggest that thrombosis risk varied with the different CAA diameters and hemodynamics effects (usually wall shear stress (WSS), oscillatory shear index (OSI), and relative residence time (RRT)) may relate to the thrombosis risk.

However, currently, due to the rareness of the disease, there is limited knowledge of the hemodynamics effects of CAA.

The aim of the study was to estimate the relationship between hemodynamic effects and different diameters of CAAs.

Computational fluid dynamics (CFD) provides a noninvasive means of hemodynamic research.

Four three-dimensional models were constructed, representing coronary arteries with a normal diameter (1x) and CAAs with diameters two (2x), three (3x), and five times (5x) that of the normal diameter.

A lumped parameter model (LPM) which can capture the feature of coronary blood flow supplied the boundary conditions.

WSS in the aneurysm decreased 97.7% apparently from 3.51 Pa (1x) to 0.08 Pa (5x).

OSI and RRT in the aneurysm were increased apparently by two orders of magnitude from 0.01 (1x) to 0.30 (5x), and from 0.38 Pa−1 (1x) to 51.59 Pa−1 (5x), separately.

Changes in the local volume of the CAA resulted in dramatic changes in local hemodynamic parameters.

The findings demonstrated that thrombosis risk increased with increasing diameter and was strongly exacerbated at larger diameters of CAA.

The 2x model exhibited the lowest thrombosis risk among the models, suggesting the low-damage (medication) treatment may work.

High-damage (surgery) treatment may need to be considered when CAA diameter is 3 times or higher.

This diameter classification method may be a good example for constructing a more complex hemodynamic-based risk stratification method and could support clinical decision-making in the assessment of CAA.