Advancing Risk Stratification of Coronary Artery Aneurysms Caused by Kawasaki Disease Using Hemodynamics Analysis and Computational Fluid Dynamics

Abstract

This article reviews previous studies on the risk assessment of coronary artery aneurysms (CAA) caused by Kawasaki disease (KD) using the computational fluid dynamics (CFD) simulation. Patient-specific CFD is an emerging tool that provides detailed three-dimensional hemodynamic information, not available from current standard imaging techniques or invasive measures. The reviewed CFD studies on KD CAA used Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) images to reconstruct the three-dimensional anatomical geometry consisting of the aorta and coronary arteries. On the inlet and outlet of the anatomical model, physiologic boundary conditions were prescribed to match the measured patient-specific blood pressure or flow data, supplemented by physiologic rules informed by population studies. Hemodynamic variables such as the blood velocity, wall shear stress, oscillatory shear index, fractional flow reserve, and particle residence time, were then quantified from the simulation results. The studies reviewed revealed strong correlations between these hemodynamic parameters and clinical outcomes, suggesting that hemodynamic metrics could be useful for treatment planning for KD patients. We discuss the limitations of the reviewed studies including small sample sizes, a narrow focus on thrombosis, and the use of different imaging modalities. The article suggests future research directions for CFD studies of KD that address these limitations.