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休闲体育活动从业者流出道室性心律失常的磁心动图分类及无创电解剖成像

Magnetocardiographic classification and non-invasive electro-anatomical imaging of outflow tract ventricular arrhythmias in recreational sport activity practitioners.

作者信息

Lombardi Gianmarco, Sorbo Anna Rita, Guida Gianluigi, La Brocca Lara, Fenici Riccardo, Brisinda Donatella

机构信息

Biomagnetism and Clinical Physiology International Center, Catholic University of Sacred Heart, Largo Agostino Gemelli 8, 00168 Rome, Italy.

Biomagnetism and Clinical Physiology International Center, Catholic University of Sacred Heart, Largo Agostino Gemelli 8, 00168 Rome, Italy.

出版信息

J Electrocardiol. 2018 May-Jun;51(3):433-439. doi: 10.1016/j.jelectrocard.2018.02.004. Epub 2018 Feb 16.

DOI:10.1016/j.jelectrocard.2018.02.004
PMID:29486898
Abstract

Ventricular arrhythmias (VAs) with left bundle-branch-block and inferior axis morphology (LBBB-IA), suggestive of outflow tract (OT) origin, are a challenge in sports medicine because they can be benign or expression of a silent cardiomyopathy. Non-invasive classification is essential to plan ablation strategy if required. We aimed to evaluating magnetocardiographic (MCG) discrimination of OT-VAs site of origin (SoO). MCG and ECG data of 26 sports activity practitioners, with OT-VAs were analyzed. OT-VAs-SoO was classified with discriminant analysis (DA) of 8 MCG parameters and with invasively-validated ECG algorithms. MCG inverse source-localization merged with magnetic resonance (CMR) provided three-dimensional electro-anatomical imaging (MCG 3D-EAI). ECG classification was univocal in 73%. MCG-DA differentiated right ventricular OT from aortic sinus cusp VAs, with 94.7% accuracy. MCG 3D-EAI confirmed OT-VAs-SoO in CMR images. In cases undergoing ablation, MCG 3D-EAI was confirmed by CARTO 3D-EAI. MCG-DA improves non-invasive classification of OT-VAs-SoO. Further comparison with interventional results is required.

摘要

伴有左束支传导阻滞及下轴形态(LBBB-IA)的室性心律失常(VA),提示起源于流出道(OT),在运动医学中是一个挑战,因为它们可能是良性的,也可能是隐匿性心肌病的表现。如果需要,非侵入性分类对于制定消融策略至关重要。我们旨在评估心磁图(MCG)对OT-VA起源部位(SoO)的鉴别能力。分析了26名患有OT-VA的体育活动从业者的MCG和心电图数据。通过对8个MCG参数的判别分析(DA)以及经过侵入性验证的心电图算法对OT-VA-SoO进行分类。MCG逆源定位与磁共振(CMR)相结合提供了三维电解剖成像(MCG 3D-EAI)。心电图分类在73%的病例中是明确的。MCG-DA区分了右心室OT与主动脉窦瓣VA,准确率为94.7%。MCG 3D-EAI在CMR图像中证实了OT-VA-SoO。在接受消融的病例中,CARTO 3D-EAI证实了MCG 3D-EAI。MCG-DA改善了OT-VA-SoO的非侵入性分类。需要进一步与介入结果进行比较。

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