Ablation pattern guided by approximate entropy maps to prevent chronic atrial fibrillation: A simulation study

Abstract

Atrial fibrillation (AF) is the most prevalent car-diac arrhythmia. Experimental and clinical evidence suggest that AF are maintained by rotors, which are targets for ablation. Some studies suggest that complex fractionated atrial electrograms (CFAE) are generated by rotor tips. Approxi-mate entropy (ApEn) can be used as a measurement that quantifies the complexity of a signal. It has been demonstrated that the ApEn can locate rotors. We hypothesized that simple ablation patterns guided by high ApEn regions can prevent and/or terminate chronic AF. An episode of chronic AF was simulated in a 3D human atrial model, in which 2 rotors were observed. Dynamic approximate entropy maps were calculated using electrogram signals generated over the whole surface of the model. ApEn map localized the tips from stable rotors. The ablation pattern developed in this work and guided by ApEn map, was able to convert AF into atrial tachycardia (AT) when it was applied during AF episode; moreover, when it was ap-plied during sinus rhythm, AF could not be generated. The results suggest that simple ablation pattern guided by ApEn maps could prevent chronic AF or convert it into a more regu-lar and less chaotic arrhythmia as atrial tachyarrhythmia.