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

Research output: Contribution to journalArticlepeer-review

52 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)687-699
Number of pages13
JournalJACC: Clinical Electrophysiology
Volume3
Issue number7
DOIs
Publication statusPublished - Jul 2017

Bibliographical note

Publisher Copyright:
© 2017 American College of Cardiology Foundation

ASJC Scopus Subject Areas

  • Cardiology and Cardiovascular Medicine
  • Physiology (medical)

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