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.