Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, affecting over 1% of the population. It is usually triggered by irregular electrical impulses that cause the atria to contract irregularly and ineffectively. It increases blood stasis and the risk of thrombus formation within the left atrial appendage (LAA) and aggravates adverse atrial remodeling. Despite recent efforts, LAA flow patterns representative of AF conditions and their association with LAA stasis remain poorly characterized. To develop reduced-order data-driven models of LAA flow patterns during atrial remodeling in order to uncover flow disturbances concurrent with LAA stasis that could add granularity to clinical decision criteria. We combined a geometric data augmentation process with projection of results from 180 CFD atrial simulations on a universal LAA coordinate (ULAAC) system. The projection approach enhances data visualization and facilitates direct comparison between different anatomical and functional states. ULAAC projections were used as input for a proper orthogonal decomposition (POD) algorithm to build reduced-order models of hemodynamic metrics, extracting flow characteristics associated with AF and non-AF anatomies. We verified that the ULAAC system provides an adequate representation to visualize data distributions on the LAA surface and to build POD-based reduced-order models. These models revealed significant differences in LAA flow patterns for atrial geometries that underwent adverse atrial remodeling and experienced elevated blood stasis. Together with anatomical morphing-based patient-specific data augmentation, this approach could facilitate data-driven analyses to identify flow features associated with thrombosis risk due to atrial remodeling.

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来自数据增强心房数据库的左心耳壁剪应力模式的降阶模型

心房颤动 (AF) 是最常见的持续性心律失常，影响超过 1% 的人口。它通常由不规则的电脉冲触发，导致心房不规则且无效地收缩。它会增加左心耳（LAA）内的血瘀和血栓形成的风险，并加剧不良的心房重塑。尽管最近做出了努力，但代表 AF 状况的左心耳血流模式及其与左心耳瘀滞的关系仍不清楚。开发心房重构过程中左心耳血流模式的降阶数据驱动模型，以发现与左心耳瘀滞同时发生的血流紊乱，从而增加临床决策标准的粒度。我们将几何数据增强过程与通用左心耳坐标 (ULAAC) 系统上 180 个 CFD 心房模拟结果的投影相结合。投影方法增强了数据可视化，并有助于不同解剖和功能状态之间的直接比较。 ULAAC 投影用作适当正交分解 (POD) 算法的输入，以构建血流动力学指标的降阶模型，提取与 AF 和非 AF 解剖结构相关的血流特征。我们验证了 ULAAC 系统提供了足够的表示来可视化 LAA 表面上的数据分布并构建基于 POD 的降阶模型。这些模型揭示了经历不良心房重塑和血瘀升高的心房几何形状的左心耳血流模式的显着差异。与基于解剖变形的患者特定数据增强相结合，这种方法可以促进数据驱动的分析，以识别与心房重塑引起的血栓形成风险相关的血流特征。