Department of Electrical, Electronic and Information Engineering (DEI), University of Bologna, Bologna 40126, Italy.
Chair of Modelling and Scientific Computing (CMCS), École Polytechnique Fédérale de Lausanne, Lausanne CH-1015, Switzerland.
J Biomech Eng. 2020 Jan 1;142(1). doi: 10.1115/1.4044583.
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.
心房颤动（AF）与脑血管事件风险增加五倍相关，占所有中风的 15-18%。AF 引起的左心房（LA）的形态和功能重构有利于血液淤滞，从而增加中风风险。在这种情况下，多项临床研究表明，通过使用 LA 和左心耳（LAA）的血流动力学信息，可以改善中风风险分层。本研究的目的是开发一个基于患者个体的 LA 的个体化计算流体动力学（CFD）模型，以阐明 AF 的血流动力学影响。本文介绍了所开发的模型及其在两名 AF 患者中的应用，作为优化中风风险分层管道的初步进展。
