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注意间隙:使用最小路径搜索量化肺静脉隔离后的不完全消融模式。

Mind the gap: Quantification of incomplete ablation patterns after pulmonary vein isolation using minimum path search.

机构信息

Physense, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.

Physense, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.

出版信息

Med Image Anal. 2019 Jan;51:1-12. doi: 10.1016/j.media.2018.10.001. Epub 2018 Oct 10.

Abstract

Pulmonary vein isolation (PVI) is a common procedure for the treatment of atrial fibrillation (AF) since the initial trigger for AF frequently originates in the pulmonary veins. A successful isolation produces a continuous lesion (scar) completely encircling the veins that stops activation waves from propagating to the atrial body. Unfortunately, the encircling lesion is often incomplete, becoming a combination of scar and gaps of healthy tissue. These gaps are potential causes of AF recurrence, which requires a redo of the isolation procedure. Late-gadolinium enhanced cardiac magnetic resonance (LGE-CMR) is a non-invasive method that may also be used to detect gaps, but it is currently a time-consuming process, prone to high inter-observer variability. In this paper, we present a method to semi-automatically identify and quantify ablation gaps. Gap quantification is performed through minimum path search in a graph where every node is a scar patch and the edges are the geodesic distances between patches. We propose the Relative Gap Measure (RGM) to estimate the percentage of gap around a vein, which is defined as the ratio of the overall gap length and the total length of the path that encircles the vein. Additionally, an advanced version of the RGM has been developed to integrate gap quantification estimates from different scar segmentation techniques into a single figure-of-merit. Population-based statistical and regional analysis of gap distribution was performed using a standardised parcellation of the left atrium. We have evaluated our method on synthetic and clinical data from 50 AF patients who underwent PVI with radiofrequency ablation. The population-based analysis concluded that the left superior PV is more prone to lesion gaps while the left inferior PV tends to have less gaps (p < .05 in both cases), in the processed data. This type of information can be very useful for the optimization and objective assessment of PVI interventions.

摘要

肺静脉隔离(PVI)是治疗心房颤动(AF)的常用方法,因为 AF 的初始触发通常源自肺静脉。成功的隔离会产生一个连续的病变(疤痕),完全环绕静脉,阻止激活波传播到心房体。不幸的是,环绕的病变通常是不完整的,形成疤痕和健康组织间隙的组合。这些间隙是 AF 复发的潜在原因,需要重新进行隔离程序。晚期钆增强心脏磁共振(LGE-CMR)是一种非侵入性方法,也可用于检测间隙,但目前该方法耗时且易受观察者间差异的影响。在本文中,我们提出了一种半自动识别和量化消融间隙的方法。通过在图中进行最小路径搜索来进行间隙量化,其中每个节点都是一个疤痕斑块,边缘是斑块之间的测地线距离。我们提出相对间隙度量(RGM)来估计静脉周围的间隙百分比,该百分比定义为总间隙长度与环绕静脉的总路径长度的比值。此外,还开发了 RGM 的高级版本,将不同疤痕分割技术的间隙量化估计值整合到单个度量中。使用左心房的标准化分割对基于人群的间隙分布进行了统计和区域分析。我们已经在接受射频消融 PVI 的 50 名 AF 患者的合成和临床数据上评估了我们的方法。基于人群的分析得出的结论是,左上肺静脉更容易出现病变间隙,而左下肺静脉的间隙较少(两种情况下均为 p < .05),在处理数据中。这种类型的信息对于 PVI 干预的优化和客观评估非常有用。

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