An in-silico approach to analyse the influence of carotid haemodynamics on cardiovascular events using 3D tomographic ultrasound and computational fluid dynamics

Analysing the haemodynamics of flow in carotid artery disease serves as a means to better understand the development and progression of associated complex diseases. Carotid artery disease can predispose people to major adverse cardiovascular events. Understanding the nature of carotid blood flow using in silico methods enables the extraction of relevant metrics that are not accessible in vivo. This study develops computationally efficient means of modelling patient-specific flow, utilising 3D tomographic ultrasound to generate anatomically faithful reconstructions including atherosclerotic plaque, and computational fluid dynamics to simulate flow in these arteries. A computationally efficient model has been proposed here, which has been used to conduct simulations for a large dataset, the results of which where statistically analysed to test the association of relevant haemodynamic metrics with cardiovascular events. The incidence of major cardiovascular diseases in carotid artery disease patients has been shown to have an association with flow vorticity in the region of interest, and less so with the absolute magnitudes of wall shear stress.