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Related Experiment Video

Updated: Jun 27, 2026

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Assessment of Intraprocedural Automated Arrhythmia Origin Localization System for Localizing Pacing Sites in 3D

Shijie Zhou1, John Whitaker2, Stanislav Goldberg3

  • 1Department of Chemical, Paper, and Biomedical Engineering, Miami University, Oxford, Ohio, USA; Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, Massachusetts, USA.

JACC. Clinical Electrophysiology
|February 3, 2025
PubMed
Summary

The Automated Arrhythmia Origin Localization in 3D (AAOL-3D) algorithm accurately predicts ventricular activation origins in three-dimensional space, outperforming its 2D surface-based counterpart. This advancement is crucial for pinpointing intramural arrhythmia sources.

Keywords:
3D localizationECG mappingelectrophysiologypace-mappingradiofrequency ablationventricular tachycardia

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Area of Science:

  • Cardiology
  • Medical Imaging
  • Computational Biology

Background:

  • The Automated Arrhythmia Origin Localization (AAOL) algorithm predicts ventricular activation origins on electroanatomic (EAM) surfaces using a 3-lead ECG (AAOL-Surface).
  • AAOL has not been evaluated in 3D space (AAOL-3D), which is critical for intramural or intracavity arrhythmia origins.

Purpose of the Study:

  • To assess the accuracy of the AAOL algorithm for localizing earliest ventricular activation in 3D space.

Main Methods:

  • Retrospective analysis of 3 datasets (47 patients, 48 procedures).
  • AAOL-3D used QRS integrals from leads III, V2, and V6 with 3D coordinates for training and prediction.
  • Localization error measured as distance between known and predicted pacing sites.

Main Results:

  • AAOL-3D achieved localization accuracy of 7.2 ± 3.1 mm, outperforming AAOL-Surface (7.2 vs 7.8 mm).
  • Localization error was greater for epicardial than endocardial pacing sites (8.7 vs 7.1 mm).
  • AAOL-3D demonstrated consistent accuracy advantages across all cohorts and EAM resolutions.

Conclusions:

  • The AAOL approach accurately identifies early ventricular activation origins in both 3D and EAM surfaces.
  • AAOL-3D shows potential utility for identifying intramural arrhythmia origins.