Spatiotemporal behaviour of high dominant frequency during persistent atrial fibrillation

Atrial electrograms (EGMs) with high dominant frequency (DF) are believed to represent atrial substrates with periodic activation responsible for the maintenance of persistent atrial fibrillation (persAF). This study aimed to assess the DF spatiotemporal behavior using high density noncontact mapping in persAF. For 8 patients undergoing left atrial (LA) persAF ablation, 2048 noncontact virtual unipolar EGMs were simultaneously collected and after the removal of ventricular far-field activity, Fourier based spectral analysis was used to identify DF on each EGM. Atrial areas with the highest DF (HDF, DF ± 0.25 Hz) were delimited in each frame for all EGMs, creating HDF `clouds'. Cumulative HDF clouds found at each frame were counted in the 3-D LA representation. To further assess the temporal stability of the cloud, the number of EGMs not hosting any HDF was determined for each window over time. The results show the number of occurrences of HDF clouds in the LA. The temporal behavior was analyzed by counting the number of positions on the 3-D representation of the LA not visited by HDF along time. Our results show HDF in persAF is not temporally stable and spatial distribution throughout the atria suggests the existence of driver regions with very rapid and regular activity maintaining AF. Therefore mapping the cumulative HDF might be an interesting strategy for ablation

Combination of frequency and phase to characterise the spatiotemporal behaviour of cardiac waves during persistent atrial fibrillation in humans

The spatial distribution of atrial dominant frequency (DF), phase and phase singularity points (PSs) may reflect mechanisms driving and maintaining persistent atrial fibrillation (persAF). Here we developed an automatic algorithm that combines the three parameters and depicts the complex spatiotemporal patterns of fibrillation. For 9 patients undergoing left atrial persAF ablation, noncontact virtual unipolar electrograms (VEGMs) were simultaneously collected using a balloon array (Ensite Velocity, St. Jude Medical). After removal of the far field ventricular influence, we used fast Fourier transform and Hilbert transform to detect the DF and phase of each VEGM PSs are detected by finding the curl of the spatial phase gradient. DF along with phase and PSs were plotted for each window and the behaviour of the trajectory of HDF 'clouds' was observed. Our results indicate that spatial and temporal organization correlating HDF and phase exists during persAF. Generating and analysing the maps of HDF and phase may prove helpful in understanding the spatial and temporal activation dynamics during persAF

An interactive platform to guide catheter ablation in human persistent atrial fibrillation using dominant frequency, organization and phase mapping

Background and Objective: Optimal targets for persistent atrial fibrillation (persAF) ablation are still debated. Atrial regions hosting high dominant frequency (HDF) are believed to participate in the initiation and maintenance of persAF and hence are potential targets for ablation, while rotor ablation has shown promising initial results. Currently, no commercially available system offers the capability to automatically identify both these phenomena. This paper describes an integrated 3D software platform combining the mapping of both frequency spectrum and phase from atrial electrograms (AEGs) to help guide persAF ablation in clinical cardiac electrophysiological studies. Methods: 30 s of 2048 non-contact AEGs (EnSite Array, St. Jude Medical) were collected and analyzed per patient. After QRST removal, the AEGs were divided into 4 s windows with a 50% overlap. Fast Fourier transform was used for DF identification. HDF areas were identified as the maximum DF to 0.25 Hz below that, and their centers of gravity (CGs) were used to track their spatiotemporal movement. Spectral organization measurements were estimated. Hilbert transform was used to calculate instantaneous phase. Results: The system was successfully used to guide catheter ablation for 10 persAF patients. The mean processing time was 10.4 ± 1.5 min, which is adequate comparing to the normal electrophysiological (EP) procedure time (120∼180 min). Conclusions: A customized software platform capable of measuring different forms of spatiotemporal AEG analysis was implemented and used in clinical environment to guide persAF ablation. The modular nature of the platform will help electrophysiological studies in understanding of the underlying AF mechanisms