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射频和冷冻球囊引导下肺静脉隔离的自动验证

Automated verification of pulmonary vein isolation in radiofrequency- and cryoballoon-guided ablation.

作者信息

De Pooter Jan, Phlips Thomas, El Haddad Milad, Van Heuverswyn Frederic, Timmers Liesbeth, Tavernier René, Knecht Sebastien, Vandekerckhove Yves, Duytschaever Mattias

机构信息

Ghent University Hospital, Heart Center, Ghent, Belgium.

Department of Cardiology, Sint-Jan Hospital, Bruges, Belgium.

出版信息

Pacing Clin Electrophysiol. 2017 Jul;40(7):779-787. doi: 10.1111/pace.13121. Epub 2017 Jun 16.

Abstract

BACKGROUND

Verification of pulmonary vein isolation (PVI) can be challenging due to the coexistence of pulmonary vein potentials and far-field potentials. This study aimed to prospectively validate a novel algorithm for automated verification of PVI in radiofrequency (RF)-guided and cryoballoon (CB)-guided ablation strategies.

METHODS

A data set of 620 (RF: 516 EGMs and CB: 104 EGMs) bipolar electrograms (EGM), recorded by circular mapping catheter placed at the left atrium-pulmonary vein (PV) junction, were prospectively analyzed by a two-step algorithm. The algorithm differentiates isolated from nonisolated EGMs based on typology and specific parameters of the bipolar EGMs. EGMs were recorded at baseline and after proven isolation in RF- and CB-guided procedures. Additionally, in the RF group, EGMs during encircling of the PVs were analyzed.

RESULTS

In the RF and CB group, the algorithm correctly identifies EGMs as isolated or nonisolated with respectively 93% and 96% sensitivity and 86% and 90% specificity. In the RF subgroups of (1) baseline and proven isolated EGMs, (2) EGMs during encircling, and (3) EGMs in redo procedures sensitivity was 96%, 88%, and 100%, respectively, with specificity of 81%, 91%, and 100%. Fourteen out of 14 (100%) reconnected PVs were correctly identified as containing PVPs. Eleven out of 12 (92%) failed freeze attempts were correctly identified as being nonisolated.

CONCLUSION

We validated a two-step algorithm for automated PVI verification, applicable both for RF- and CB-guided PVI. The algorithm automatically differentiates isolated from nonisolated PVs with high accuracy and without the need for pacing maneuvers.

摘要

背景

由于肺静脉电位和远场电位共存,肺静脉隔离(PVI)的验证可能具有挑战性。本研究旨在前瞻性验证一种用于在射频(RF)引导和冷冻球囊(CB)引导的消融策略中自动验证PVI的新算法。

方法

通过放置在左心房 - 肺静脉(PV)交界处的环形标测导管记录的620个(RF:516个心内电图和CB:104个心内电图)双极心内电图(EGM)数据集,采用两步算法进行前瞻性分析。该算法根据双极EGM的类型和特定参数区分隔离的和未隔离的EGM。在RF和CB引导的手术中,在基线和证实隔离后记录EGM。此外,在RF组中,分析了肺静脉环绕期间的EGM。

结果

在RF组和CB组中,该算法分别以93%和96%的灵敏度以及86%和90%的特异性正确识别EGM为隔离或未隔离。在RF亚组中,(1)基线和证实隔离的EGM,(2)环绕期间的EGM,以及(3)再次手术中的EGM,灵敏度分别为96%、88%和100%,特异性分别为81%、91%和100%。14个重新连接的肺静脉中的14个(100%)被正确识别为含有肺静脉电位。12次冷冻尝试失败中的11次(92%)被正确识别为未隔离。

结论

我们验证了一种用于自动PVI验证的两步算法,适用于RF和CB引导的PVI。该算法无需起搏操作即可高精度地自动区分隔离的和未隔离的肺静脉。

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