Haemodynamic mechanism of formation and distribution of coronary atherosclerosis: A lesion-specific model. (November 2020) - Feng, Jiling; Wang, Nannan; Wang, Yiliang; Tang, Xiaoxian; Yuan, Jie
Coronary arterial disease, as the most devastated cardiovascular disease, is caused by the atherosclerosis in the coronary arteries, which blocks the blood flow to the heart, resulting in the deficient supply of oxygen and nutrition to the heart, and eventually leading to heart failure. To date, haemodynamic mechanisms for atherosclerosis development are not fully understood although it is believed that the haemodynamic disturbance at the region of the arterial bifurcation, particular, bifurcation angle, plays an important role in the atherosclerosis development. In this study, two types of computational fluid dynamics models, lesion-specific and idealized models, combined with the computer tomography imaging techniques, are used to explore the mechanism of formation and distribution of the atherosclerosis around the bifurcation of left coronary artery and its association with the bifurcation angle. The lesion-specific model is used to characterize the effect of personalized features on the haemodynamic performance, while the idealized model is focusing on the effect of single factor, bifurcation angle, on the haemodynamic performance. The simulated results from both types of the models, combined with the clinical observation, revealed that the three key areas around the bifurcations are prone to formation of the atherosclerosis. Unlike the idealized models, lesion-specific modelling results did not show the significant correlation between the wall shear stress and bifurcation angle, although the mean value of the wall shear stress in smaller bifurcation angles (less than 90°) is higher than that with larger bifurcation angles (greater than 90°). In conclusion, lesion-specific computational fluid dynamics modelling is an efficient and convenient way to predict the haemodynamic performance around the bifurcation region, allowing the comprehensive information for the clinicians to predict the atherosclerosis development. The idealized models, which only focus on single parameter, may not provide the sufficient and reliable information for the clinical application. A novel multi-parameters modelling technique, therefore, is suggested to be developed in future, allowing the effects of many parameters on the haemodynamic performance to be evaluated.