Design of experiment approach to identify the dominant geometrical feature of left coronary artery influencing atherosclerosis

Abstract

Background and Objective. Coronary artery geometry heavily influences local hemodynamics, potentially leading to atherosclerosis. Consequently, the unique geometrical configuration of an individual by birth can be associated with future risk of atherosclerosis. Although current researches focus on exploring the relationship between local hemodynamics and coronary artery geometry, this study aims to identify the order of influence of the geometrical features through systematic experiments, which can reveal the dominant geometrical feature for future risk assessment. Methods. According to Taguchi’s method of design of experiment (DoE), the left main stem (LMS) length (l LMS), curvature (k LMS), diameter (d LMS) and the bifurcation angle between left anterior descending (LAD) and left circumflex (LCx) artery (α LAD-LCx) of two reconstructed patient-specific left coronary arteries (LCA) were varied in three levels to create L9 orthogonal array. Computational fluid dynamic (CFD) simulations with physiological boundary conditions were performed on the resulting eighteen LCA models. Average helicity intensity (h 2) and relative atheroprone area (RAA) of near-wall hemodynamic descriptors were analyzed. Results. The proximal LAD (LAD proximal) was identified to be the most atheroprone region of the left coronary artery due to higher h 2, large RAA of time averaged wall shear stress (TAWSS < 0.4 Pa), oscillatory shear index (OSI ∼ 0.5) and relative residence time (RRT > 4.17 Pa−1). In both patient-specific cases, based on h 2 and TAWSS, d lms is the dominant geometric parameter while based on OSI and RRT, α LAD-LCx is the dominant one influencing hemodynamic condition in proximal LAD (p < 0.05). Based on RRT, the rank of the geometrical factors is: α LAD-LCx > d LMS > l LMS > k LMS, indicating that α LAD-LCx is the most dominant geometrical factor affecting hemodynamics at proximal LAD which may influence atherosclerosis. Conclusion. The proposed identification of the rank of geometrical features of LCA and the dominant feature may assist clinicians in predicting the possibility of atherosclerosis, of an individual, long before it will occur. This study can further be translated to be used to rank the influence of several arterial geometrical features at different arterial locations to explore detailed relationships between the arterial geometrical features and local hemodynamics.