High density frequency mapping of human intracardiac persistent atrial fibrillation electrograms

Atrial fibrillation (AF) is the most common heart rhythm disturbance. Once AF is initiated, dynamic alterations of atrial electrophysiological properties occur invoking, in turn, AF inducibility. In patients for whom AF persists for long-term periods (persAF), identification of critical areas for successful ablation remains a challenge. Improving our understanding of the underlying AF behaviour is a key factor to contribute towards improving patient outcome. In this research, spectral analysis of simultaneous high density non-contact unipolar intracardiac atrial electrograms (AEGs) recorded from the left atrium (LA) of persAF patients (AF duration 34±25 months) was applied after a coherent strategy of cancellation of the ventricular influence on the AEGs. Three-dimensional dominant frequency (DF) maps with 2048 measurement points from AEGS were generated over consecutive frames of up to 1 minute (windows of 4s with 50% overlap). The results of this thesis showed a lack of DF spatiotemporal stability, demonstrating that AF mapping would be preferable performed using simultaneous multipolar recordings. Although DF is not stable, a certain degree of DF reappearance was observed, mostly within 10 s. The spatiotemporal analysis of areas thought to be playing a role in AF maintenance, highest DF areas (HDFAs), revealed presence of three distinct patterns with predominance of cyclic behaviour (61.2±12.4 % of the time) followed by local (27.0±8.6 %) and irregular behaviour (11.9±9.1 %), mostly concentrated in the LA roof and the pulmonary veins. Independently of the trajectory of the HDFAs, the regions located next to the HDFAs’ core presented higher DF organisation than areas by the HDFAs’ periphery (p=0.0061) providing further insight into the potential mechanisms of persAF. The research has demonstrated the importance of DF mapping as an auxiliary tool contributing to the investigation of persAF patients and would help clinicians to better understand the AF mechanisms. Real-time implementation was shown to be feasible with the use of Graphic Processing Units, where the processing time was 15 times faster than real time, representing an innovation that could have considerable impact on clinical practice, as part of the decision making process for persAF treatment.