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  • Title: 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.
    Author: Ito Y, Shiga K, Yoshida K, Ogata K, Kandori A, Inaba T, Nakazawa Y, Sekiguchi Y, Tada H, Sekihara K, Aonuma K.
    Journal: Heart Rhythm; 2014 Sep; 11(9):1605-12. PubMed ID: 24887136.
    Abstract:
    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/m(2); P < .01) and farther from the sinus node (55 ± 9 mm/m2 vs. 41 ± 9 mm/m(2); 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.
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