Phase- and Frequency- Domain Analysis of the Intracardiac Signals of Persistent Atrial Fibrillation in Humans

Identification of critical areas for successful ablation in persistent atrial fibrillation (persAF) patients remains a challenge. Atrial electrograms (AEGs) with high dominant frequency (HDF) are believed to represent atrial substrates with periodic activation responsible for maintaining persAF. Phase is a descriptor that tracks the progression of the action potential through atria and has been demonstrated to be effective in analysing spatiotemporal changes during persAF. DF has been used as a way to express local atrial activation rate of the AEGs during AF. HDF sites were analysed consecutively to produce HDF density maps and its spatiotemporal behaviour during persAF was investigated. An algorithm based on topological charge index was also implemented to obtain phase singularity points (PSs). This algorithm’s performance was compared with two other PS detection techniques for detecting PSs and has been demonstrated to have more accurate results with reduced processing time (near-real time) to calculate targets. Additionally, the effect of varying filter type and settings on the detection of PSs was also studied, From this it is understood that filter settings could affect PS detections, which result in misleading identification of the atrial substrate and hence ablation targets. Furthermore, the spatiotemporal dynamics of the PSs was also investigated by tracking them in space and time to identify ‘rotors’. Rotors were not seen very often and were associated with higher atrial rate as well as disorganised AEGs. Finally, the combination of frequency and phase analysis was studied to elucidate the mechanism of wave propagation and to identify potential drivers perpetuating persAF. There is some evidence of a cause-effect relationship between the HDF and PS density maps which leads to the spatiotemporal organization in the activation patterns during sustained A. Consequently, analysing the behaviour of the two parameters can help clinicians to develop strategies for ablation.