Mapping and Investigation of Atrial Electrogram Fractionation in Patients with Persistent Atrial Fibrillation

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia found in clinical practice, and it is a leading cause of stroke. It has been shown that triggers in the pulmonary veins (PVs) are important in the initiation and perpetuation of paroxysmal AF. PV isolation (PVI) by radiofrequency catheter ablation has been proved effective in treating patients with paroxysmal AF. However, the identification of critical areas for successful ablation in patients with persistent AF (persAF) remains a challenge due to an incomplete understanding of the mechanistic interaction between relevant atrial substrate and the initiation and maintenance of AF. Complex fractionated atrial electrograms (CFAEs) are believed to represent remodelled atrial substrate and, therefore, potential targets for persAF ablation. Since its introduction in 2004, CFAEs have been accepted and incorporated as an additional therapy to PV isolation (PVI) to treat patients with persAF by many laboratories. Inconsistent CFAE-guided ablation outcomes have, however, cast doubt on the efficacy of this approach. The majority of the electrophysiological studies rely on automated CFAE detection algorithms embedded in electro-anatomical mapping (EAM) systems to identify CFAEs during persAF ablation. Different companies have developed algorithms based on different aspects of the atrial electrogram (AEG). Differences in these algorithms could lead to discordant CFAE classifications by the available EAM systems, giving rise to potential disparities in CFAE-guided ablation. Additionally, previous studies support the existence of fractionated AEGs not related to AF perpetuation, and fractionated AEGs that represent sources responsible for AF maintenance. Those investigations relied on few AEG descriptors, which can be a limiting factor when describing a complex phenomenon such as AF. Discerning the different types of CFAEs is crucial for AF ablation therapy. Finally, the spatio-temporal behaviour of AEGs collected during persAF remains poorly explored. This study encloses contributions towards the minimization of discordances in automated classification of CFAEs, the characterization of AEGs before and after PVI, and the investigation of the temporal behaviour of consecutive AEGs and the consistency of CFAEs using different AEG segment lengths.