Prospective Multicenter Assessment of a New Intraprocedural Automated System for Localizing Idiopathic Ventricular Arrhythmia Origins

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

BACKGROUND

The Automated Arrhythmia Origin Localization (AAOL) algorithm was developed for real-time prediction of early ventricular activation origins on a patient-specific electroanatomic (EAM) surface using a 3-lead electrocardiogram (AAOL-Surface). It has not been evaluated in 3-dimensional (3D) space (AAOL-3D), however, which may be important for predicting the arrhythmia origin from intramural or intracavity sites.

OBJECTIVES

This study sought to assess the accuracy of AAOL for localizing earliest ventricular activation in 3D space.

METHODS

This was a retrospective study of 3 datasets (BWH [Brigham and Women's Hospital], JHH [Johns Hopkins Hospital], and QEII [Queen Elizabeth II Health Sciences Centre]) involving 47 patients and 48 procedures, with an average of 19 ± 10 pacing sites each. In each patient, individual pacing sites were identified as target sites; the remaining pacing sites served as a training set (including QRS integrals from leads III, V2, and V6 with associated 3D coordinates). The AAOL-3D was then used to predict 3D coordinates of the pacing site. Localization error was assessed as the distance between known and predicted site coordinates, considering different EAM resolutions.

RESULTS

The AAOL-3D achieved a localization accuracy of 7.2 ± 3.1 mm, outperforming the AAOL-Surface (7.2 vs 7.8 mm; P < 0.05), with greater localization error for epicardial than endocardial pacing sites (8.7 vs 7.1 mm; P < 0.05). Cohort-specific analysis consistently favored AAOL-3D over AAOL-Surface in terms of accuracy. Exploration of AAOL-Surface accuracy across varying EAM resolutions showed optimal performance at the original and 75% resolution, with performance declining as resolution decreased.

CONCLUSIONS

The AAOL approach accurately identifies early ventricular activation origins in 3D and on EAM surfaces, potentially useful for identifying intramural arrhythmia origins.

An Automata-Based Cardiac Electrophysiology Simulator to Assess Arrhythmia Inducibility

Personalized cardiac electrophysiology simulations have demonstrated great potential to study cardiac arrhythmias and help in therapy planning of radio-frequency ablation. Its application to analyze vulnerability to ventricular tachycardia and sudden cardiac death in infarcted patients has been recently explored. However, the detailed multi-scale biophysical simulations used in these studies are very demanding in terms of memory and computational resources, which prevents their clinical translation. In this work, we present a fast phenomenological system based on cellular automata (CA) to simulate personalized cardiac electrophysiology. The system is trained on biophysical simulations to reproduce cellular and tissue dynamics in healthy and pathological conditions, including action potential restitution, conduction velocity restitution and cell safety factor. We show that a full ventricular simulation can be performed in the order of seconds, emulate the results of a biophysical simulation and reproduce a patient’s ventricular tachycardia in a model that includes a heterogeneous scar region. The system could be used to study the risk of arrhythmia in infarcted patients for a large number of scenarios.

Assessment of an ECG-Based System for Localizing Ventricular Arrhythmias in Patients With Structural Heart Disease

Background

We have previously developed an intraprocedural automatic arrhythmia‐origin localization (AAOL) system to identify idiopathic ventricular arrhythmia origins in real time using a 3‐lead ECG. The objective was to assess the localization accuracy of ventricular tachycardia (VT) exit and premature ventricular contraction (PVC) origin sites in patients with structural heart disease using the AAOL system.

Methods and Results

In retrospective and prospective case series studies, a total of 42 patients who underwent VT/PVC ablation in the setting of structural heart disease were recruited at 2 different centers. The AAOL system combines 120‐ms QRS integrals of 3 leads (III, V2, V6) with pace mapping to predict VT exit/PVC origin site and projects that site onto the patient‐specific electroanatomic mapping surface. VT exit/PVC origin sites were clinically identified by activation mapping and/or pace mapping. The localization error of the VT exit/PVC origin site was assessed by the distance between the clinically identified site and the estimated site. In the retrospective study of 19 patients with structural heart disease, the AAOL system achieved a mean localization accuracy of 6.5±2.6 mm for 25 induced VTs. In the prospective study with 23 patients, mean localization accuracy was 5.9±2.6 mm for 26 VT exit and PVC origin sites. There was no difference in mean localization error in epicardial sites compared with endocardial sites using the AAOL system (6.0 versus 5.8 mm, P=0.895).

Conclusions

The AAOL system achieved accurate localization of VT exit/PVC origin sites in patients with structural heart disease; its performance is superior to current systems, and thus, it promises to have potential clinical utility.