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Publication
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Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
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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