Patient-Specific Identification of Atrial Flutter Vulnerability-A Computational Approach to Reveal Latent Reentry Pathways
Patient-Specific Identification of Atrial Flutter Vulnerability-A Computational Approach to Reveal Latent Reentry Pathways
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DOI：
10.3389/fphys.2018.01910
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发表时间：
2019-01-14
影响因子：
4
通讯作者：
Doessel, Olaf
中科院分区：
文献类型：
--
作者：
Loewe, Axel;Poremba, Emanuel;Doessel, Olaf
非典型性心房扑动（AFlut）是一种折返性心律失常，患者在房颤（AF）消融术后经常发生。事实上，AF消融期间的基质改变可增加发生AFlut的可能性，并且在临床上无法可靠且灵敏地检测患者是否易发生AFlut。在这里，我们提出了一种基于个性化计算模型的新方法，以确定AFlut可以在个体患者中持续的途径沿着。我们建立了一个个性化的心房兴奋传播模型，考虑到解剖结构以及各向异性传导速度和复极特性的空间分布的基础上，结合先验知识的人口水平和信息，从测量中进行的个别患者。快速行进方案被用来计算心房各部分刺激的激活时间。潜在的颤振路径，然后确定跟踪回路从波前碰撞网站和收缩他们使用几何蛇的方法下考虑的异质波长条件。通过这种方式，确定了AFlut可持续的所有沿着途径。颤振路径可以通过使用eikonal-diffusion相位外推法和动态多波前快速行进模拟来实例化。在这些动态模拟中，初始模式最终变成由主导通路驱动的模式，这是临床上可以观察到的唯一通路。我们评估了扑动通路图对传导速度及其各向异性的敏感性。此外，我们展示了考虑疾病特异性复极特性（健康、AF重构、钾通道突变）的定制模型的应用以及在临床数据集上的适用性。最后，我们测试了这些底物的AFlut脆弱性如何通过示例性抗心律失常药物（胺碘酮、决奈达隆）调节。我们的新方法允许基于个人解剖学、电生理学和药理学特征评估个体患者发展AFlut的脆弱性。与临床电生理研究相比，我们的计算方法提供了识别所有可能的AFlut通路的方法，而不仅仅是目前占主导地位的通路。这允许在定制临床消融治疗时考虑所有相关的AFlut通路，以减少AFlut的发展和复发。
Atypical atrial flutter (AFlut) is a reentrant arrhythmia which patients frequently develop after ablation for atrial fibrillation (AF). Indeed, substrate modifications during AF ablation can increase the likelihood to develop AFlut and it is clinically not feasible to reliably and sensitively test if a patient is vulnerable to AFlut. Here, we present a novel method based on personalized computational models to identify pathways along which AFlut can be sustained in an individual patient. We build a personalized model of atrial excitation propagation considering the anatomy as well as the spatial distribution of anisotropic conduction velocity and repolarization characteristics based on a combination of a priori knowledge on the population level and information derived from measurements performed in the individual patient. The fast marching scheme is employed to compute activation times for stimuli from all parts of the atria. Potential flutter pathways are then identified by tracing loops from wave front collision sites and constricting them using a geometric snake approach under consideration of the heterogeneous wavelength condition. In this way, all pathways along which AFlut can be sustained are identified. Flutter pathways can be instantiated by using an eikonal-diffusion phase extrapolation approach and a dynamic multifront fast marching simulation. In these dynamic simulations, the initial pattern eventually turns into the one driven by the dominant pathway, which is the only pathway that can be observed clinically. We assessed the sensitivity of the flutter pathway maps with respect to conduction velocity and its anisotropy. Moreover, we demonstrate the application of tailored models considering disease-specific repolarization properties (healthy, AF-remodeled, potassium channel mutations) as well as applicabiltiy on a clinical dataset. Finally, we tested how AFlut vulnerability of these substrates is modulated by exemplary antiarrhythmic drugs (amiodarone, dronedarone). Our novel method allows to assess the vulnerability of an individual patient to develop AFlut based on the personal anatomical, electrophysiological, and pharmacological characteristics. In contrast to clinical electrophysiological studies, our computational approach provides the means to identify all possible AFlut pathways and not just the currently dominant one. This allows to consider all relevant AFlut pathways when tailoring clinical ablation therapy in order to reduce the development and recurrence of AFlut.