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Atrial fibrillation (AF) is associated with a fivefold increase in the risk of cerebrovascular events, being responsible of 15–18% of all strokes. The morphological and functional remodeling of the left atrium (LA) caused by AF favors blood stasis and, consequently, stroke risk. In this context, several clinical studies suggest that the stroke risk stratification could be improved by using hemodynamic information on the LA and the left atrial appendage (LAA). The goal of this study was to develop a personalized computational fluid dynamics (CFD) model of the LA which could clarify the hemodynamic implications of AF on a patient-specific basis. In this paper, we present the developed model and its application to two AF patients as a preliminary advancement toward an optimized stroke risk stratification pipeline.

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Atrial fibrillation (AF) is associated to a five-fold increase in the risk of stroke and AF strokes are especially severe. Stroke risk is connected to several AF related morphological and functional remodeling mechanisms which favor blood stasis and clot formation inside the left atrium. The goal of this study was therefore to develop a patientspecific computational fluid dynamics model of the left atrium which could quantify the hemodynamic implications of atrial fibrillation on a patient-specific basis. Hereto, dynamic patient-specific CT imaging was used to derive the 3D anatomical model of the left atrium by applying a specifically designed image segmentation algorithm. The computational model consisted in a fluid governed by the incompressible Navier-Stokes equations written in the Arbitrary Lagrangian Eulerian (ALE) frame of reference. In this paper, we present the developed model as well as its application to two AF patients. These initial results confirmed that morphological and functional remodeling processes associated to AF effectively reduce blood washout in the left atrium, thereby increasing the risk of clot formation. Our analysis is a step forward towards improved patient-specific stroke risk stratification and therapy planning.

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