Real-Time Localization of Ventricular Tachycardia Origin From the 12-Lead Electrocardiogram

John L. Sapp, Meir Bar-Tal, Adam J. Howes, Jonathan E. Toma, Ahmed El-Damaty, James W. Warren, Paul J. MacInnis, Shijie Zhou, B. Milan Horáček

Résultat de recherche: Articleexamen par les pairs

52 Citations (Scopus)

Résumé

Objectives The aim of this study was to develop rapid computational methods for identifying the site of origin of ventricular activation from the 12-lead electrocardiogram. Background Catheter ablation of ventricular tachycardia in patients with structural heart disease frequently relies on a substrate-based approach, which may use pace mapping guided by body-surface electrocardiography to identify culprit exit sites. Methods Patients undergoing ablation of scar-related VT (n = 38) had 12-lead electrocardiograms recorded during pacing at left ventricular endocardial sites (n = 1,012) identified on 3-dimensional electroanatomic maps and registered to a generic left ventricular endocardial surface divided into 16 segments and tessellated into 238 triangles; electrocardiographic data were reduced for each lead to 1 variable, consisting of QRS time integral. Two methods for estimating the origin of activation were developed: 1) a discrete method, estimating segment of activation origin using template matching; and 2) a continuous method, using population-based multiple linear regression to estimate triangle of activation origin. A variant of the latter method was derived, using patient-specific multiple linear regression. Results The optimal QRS time integral included the first 120 ms of the QRS interval. The mean localization error of population-based regressions was 12 ± 8 mm. Patient-specific regressions can achieve localization accuracy better than 5 mm when at least 10 training-set pacing sites are used; this accuracy further increases with each added pacing site. Conclusions Computational intraprocedure methods can automatically identify the segment and site of left ventricular activation using novel algorithms, with accuracy within <10 mm.

Langue d'origineEnglish
Pages (de-à)687-699
Nombre de pages13
JournalJACC: Clinical Electrophysiology
Volume3
Numéro de publication7
DOI
Statut de publicationPublished - juill. 2017

Note bibliographique

Publisher Copyright:
© 2017 American College of Cardiology Foundation

ASJC Scopus Subject Areas

  • Cardiology and Cardiovascular Medicine
  • Physiology (medical)

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