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首页> 外文期刊>Heart rhythm: the official journal of the Heart Rhythm Society >Development of a magnetocardiography-based algorithm for discrimination between ventricular arrhythmias originating from the right ventricular outflow tract and those originating from the aortic sinus cusp: A pilot study
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Development of a magnetocardiography-based algorithm for discrimination between ventricular arrhythmias originating from the right ventricular outflow tract and those originating from the aortic sinus cusp: A pilot study

机译:从右心间流出道的心间心律失常辨别算法的发展,源自主动脉窦尖 - 尖塔:试验研究

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Background Although several reports address characteristic 12-lead electrocardiographic findings of outflow tract ventricular arrhythmias (OT-VAs), the accuracy of electrocardiogram-based algorithms to predict the OT-VA origin is sometimes limited. Objective This study aimed to develop a magnetocardiography (MCG)-based algorithm using a novel adaptive spatial filter to differentiate between VAs originating from the aortic sinus cusp (ASC-VAs) and those originating from the right ventricular outflow tract (RVOT-VAs). Methods This study comprised 51 patients with an OT-VA as the target of catheter ablation. An algorithm was developed by correlating MCG findings with the successful ablation site. The arrhythmias were classified as RVOT-VAs or ASC-VAs. Three parameters were obtained from 3-dimensional MCG imaging: depth of the origin of the OT-VA in the anteroposterior direction; distance between the earliest atrial activation site, that is, sinus node, and the origin of the OT-VA; and orientation of the arrhythmia propagation at the QRS peak. The distance was indexed to the patient's body surface area (in mm/m2). Results Origins of ASC-VAs were significantly deeper (81 ± 6 mm/m 2 vs 68 ± 8 mm/m2; P .01) and farther from the sinus node (55 ± 9 mm/m2 vs 41 ± 9 mm/m2; P .01) than those of RVOT-VAs. ASC-VA propagation had a tendency toward rightward axis. Receiver operating characteristic analyses determined that the depth of the origin was the most powerful predictor, with a sensitivity of 90% and a specificity of 73% (area under the curve = 0.90; P .01). Discriminant analysis combining all 3 parameters revealed the accuracy of the localization to be 94%. Conclusion This MCG-based algorithm appeared to precisely discriminate ASC-VAs from RVOT-VAs. Further investigation is required to validate the clinical value of this technique.
机译:背景技术虽然几个报告地址特征性12-铅心电图发现流出截道室性心律失常(OT-VAS),但基于心电图的算法预测OT-VA原点的准确性有时是有限的。目的本研究旨在使用新型自适应空间滤波器开发磁插片(MCG)基础算法,以区分源自主动脉窦(ASC-VAS)的VAS和源自右心室流出道(RVOT-VAS)的VAS。方法本研究包括51名患者OT-VA作为导管消融的目标。通过将MCG调查结果与成功的消融部位相关联开发了一种算法。心律失常被归类为RVOT-VAS或ASC-VAS。从三维MCG成像获得三个参数:前后方向上的OT-VA的原点深度;最早的心房激活网站之间的距离,即窦节点和OT-VA的起源;在QRS峰值时心律失常传播的方向。距离被索引到患者的体表面积(mm / m2)。结果ASC-VAS的起源显着更深(81±6mm / m 2与68±8 mm / m2; p <.01),并且从鼻窦节点(55±9 mm / m2 vs 41±9 mm / m2; p& 01)比Rvot-vas。 ASC-VA传播对向右轴的倾向。接收器操作特征分析确定原点的深度是最强大的预测因子,灵敏度为90%,特异性为73%(曲线下的面积= 0.90; p <.01)。结合所有3个参数的判别分析显示了定位的准确性为94%。结论该基于MCG的算法似乎精确地区分RVOT-VAS的ASC-VAS。需要进一步调查来验证该技术的临床价值。

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