Mechanistic modelling of Virchows triad to assess thrombogenicity and stroke risk in atrial fibrillation patients

Abstract

Background: Atrial fibrillation (AF) is responsible for almost one third of all strokes, with the left atrial appendage (LAA) being the primary throm-boembolic source due to localised stimulation of prothrombotic mechanisms ; blood stasis, hypercoagulability and endothelial damage, known as Virchow's triad. Aim: We propose an in-silico modelling pipeline that leverages clinical imaging data to mechanistically assess patient thrombogenicity for all aspects of Virchow's triad to improve the prediction and prevention of AF-related stroke. Methods: Two AF patients undergoing Cine magnetic resonance imaging (sinus rhythm (SR) N=1 or AF N=1 during imaging) were selected for 3D left atrial (LA) modelling with patient-specific myocardial deformation prescribed from image-derived wall motion. Blood stasis was quantified by computational fluid dynamics (CFD) simulations of 5 cardiac cycles [1]. Generation of three key coagulation proteins; thrombin, fibrinogen and fib-rin, were modelled to represent thrombus growth and hypercoagulability [2]. Regions prone to thrombogenesis by endothelial damage were identified by the oscillatory shear index (OSI), time averaged wall shear stress (TAWSS) and endothelial cell activation potential (ECAP) metrics in the LAA [3]. Results: Patient-specific LA simulations enabled the assessment of differences between SR and AF conditions, quantified as numerical characteristics of each aspect of Virchow's triad.