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.
Masci A., Alessandrini M., Forti D., Menghini F., Dede L., Tomasi C., et al. (2020). A Proof of concept for computational fluid dynamic analysis of the left atrium in atrial fibrillation on a patient-specific basis. JOURNAL OF BIOMECHANICAL ENGINEERING, 142(1), 1-23 [10.1115/1.4044583].
A Proof of concept for computational fluid dynamic analysis of the left atrium in atrial fibrillation on a patient-specific basis
Masci A.
;Alessandrini M.;Corsi C.
2020
Abstract
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.File | Dimensione | Formato | |
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