INTRODUCTION
Electrophysiologists are increasingly called upon to ablate more complex arrhythmia substrates. These can take the form of multi-site atrial tachycardias (AT), flutters, scar-related substrates in ventricular tachycardia, and nonautomatic focal AT or intra-atrial reentrant tachycardia (IART) in the congenital heart disease population [1, 2]. Areas of discontinuity in ablation lines can lead to proarrhythmic effects [3]. In patients post atrial fibrillation ablation, multiple focal ATs and reentrant flutter circuits can occur [4, 5], with 40% of recurrences attributable to ATs. In complex congenital heart disease such as single ventricle physiology with Fontan palliation, the mean number of inducible ATs/IARTs exceeds 2 per patient [6].
Three-dimensional electroanatomic mapping systems are indispensable tools for complex ablation procedures involving multiple sites of origin or circuits. Separate maps must be created for each arrhythmia which is challenging, particularly when arrhythmias transition from one site to another and/or have similar cycle lengths. Manual mapping can become cumbersome and subject to inaccuracies. The Intra-Cardiac Pattern Matching (ICPM) software (CARTO, Biosense Webster, Irvine, CA) was created to automatically identify tachycardia patterns and classify each to their respective maps. The software instantaneously recognizes changes in activation patterns thereby allowing continuous mapping of different arrhythmogenic foci/circuits. The purpose of this study was to systematically evaluate this algorithm in an animal model by comparing manually acquired and automated maps created by pacing at various atrial sites.