Gavin S. Chu

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 30s of 2048 non-contact AEGs (EnSite Array, St. Jude Medical) were collected and analyzed per patient. After QRST removal, the AEGs were divided into 4s windows with a 50% overlap. Fast Fourier transform was used for DF identification. HDF areas were identified as the maximum DF to 0.25Hz 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 ± 1.5min, which is adequate comparing to the normal electrophysiological (EP) procedure time (120∼180min). 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.

Investigation on recurrent high dominant frequency spatiotemporal patterns during persistent atrial fibrillation

Atrial regions hosting dominant frequency (DF) may represent potential drivers of persistent atrial fibrillation (persAF). Previous work showed that DF can exhibit cyclic behaviour. This study aims to better understand the spatiotemporal behaviours of persAF over longer time periods. 10 patients undergoing persAF ablation targeted at DF were included. Left atrial (LA) non-contact virtual electrograms (VEGMs, Ensite Array, St Jude Medical) were collected for up to 5 min pre-/post- ablation. DF was identified as the peak from 4-10 Hz, in 4 s windows (50 % overlap). High DF (HDF) map was created and automated pattern recognition algorithm was applied to look for recurring HDF spatial patterns within each patient. Recurring HDF patterns were found in all patients. Patients who changed rhythm to atrial flutter after ablation demonstrated single dominant pattern (DP) among the recorded time period, which might consistent with the higher level of regularity during flutter. Ablation regularized AF as demonstrated by increased DP recurrence after ablation. The time interval (median [IQR]) of DP recurrence for the patients still in atrial fibrillation(AF) after ablation (7 patients) decreased from 21.1 s [11.8~49.7 s] to 15.7s [6.5~18.2 s]. The proposed method quantifies the spatiotemporal regularity of HDF DPs over long time periods and may offer a more comprehensive dynamic overview of persAF behaviour and the impact of ablation.

Atrial Electrogram Fractionation Distribution before and after Pulmonary Vein Isolation in Human Persistent Atrial Fibrillation—A Retrospective Multivariate Statistical Analysis

Purpose: Complex fractionated atrial electrograms (CFAE)-guided ablation after pulmonary vein isolation (PVI) has been used for persistent atrial fibrillation (persAF) therapy. This strategy has shown suboptimal outcomes due to, among other factors, undetected changes in the atrial tissue following PVI. In the present work, we investigate CFAE distribution before and after PVI in patients with persAF using a multivariate statistical model. Methods: 207 pairs of atrial electrograms (AEGs) were collected before and after PVI respectively, from corresponding LA regions in 18 persAF patients. Twelve attributes were measured from the AEGs, before and after PVI. Statistical models based on multivariate analysis of variance (MANOVA) and linear discriminant analysis (LDA) have been used to characterize the atrial regions and AEGs. Results: PVI significantly reduced CFAEs in the LA (70 vs. 40%; P < 0.0001). Four types of LA regions were identified, based on the AEGs characteristics: (i) fractionated before PVI that remained fractionated after PVI (31% of the collected points); (ii) fractionated that converted to normal (39%); (iii) normal prior to PVI that became fractionated (9%) and; (iv) normal that remained normal (21%). Individually, the attributes failed to distinguish these LA regions, but multivariate statistical models were effective in their discrimination (P < 0.0001). Conclusion: Our results have unveiled that there are LA regions resistant to PVI, while others are affected by it. Although, traditional methods were unable to identify these different regions, the proposed multivariate statistical model discriminated LA regions resistant to PVI from those affected by it without prior ablation information.

Drifting rotor prevalence is associated with dominant frequency reduction after persistent atrial fibrillation ablation

Identification and targeting of arrhythmogenic atrial regions remains an evident challenge in persistent atrial fibrillation patients. Frequency and phase analysis have shown their usefulness for better understanding the arrhythmia. This study aimed to investigate the spatio-temporal association between dominant frequency (DF) and re-entrant phase activation areas. For this, eight persistent AF patients were enrolled and 2048 left atrial AF electrograms (AEG) were acquired from each for up to 15 seconds following ventricular far-field cancellation. DF and phase singularity (PS) points were automatically identified and tracked over consecutive frames for spatio-temporal analysis. As result, simultaneous not spatio-temporally stable PS points were identified drifting throughout the left atrium. After pulmonary vein isolation PS incidence reduced (90.8±59.8 vs. 23.8±31.6, p<;0.05), concomitantly, DF decreased (DFmax from 7.3±0.4 Hz to 7.1±0.8 Hz, p=0.26 and DFmin from 5.1±1.2 Hz to 4.2±1.1 Hz, p<;0.05). Higher concentrations of PS areas seem to have a certain degree of co-localisation with HDF regions. Both frequency and phase analyses seem to have a role in identifying atrial regions that might be perpetuating persistent AF. Concatenated DF/PS mapping may contribute as an auxiliary tool for AF ablation.

Unifying automated fractionated atrial electrogram classification using electroanatomical mapping systems in persistent atrial fibrillation studies

Ablation targeting complex fractionated atrial electrograms (CFAE) for treating persistent atrial fibrillation (persAF) has shown conflicting results. Differences in automated algorithms embedded in NavX (St Jude Medical) and CARTO (Biosense Webster) could influence CFAE target identification for ablation, potentially affecting ablation outcomes. To evaluate this effect, automated CFAE classification performed by NavX and CARTO on the same bipolar electrograms from 18 persAF patients undergoing ablation was compared. Using the default thresholds, NavX classified 69±5% of the electrograms as CFAEs, while CARTO detected 35±5%% (Cohens kappa κ≈0.3, P<;0.0001). Both primary and complementary metrics for each system were optimized to balance CFAE detection for both systems. Using revised thresholds found from receiver operating characteristic curves, NavX classified 45±4%, while CARTO detected 42±5% (κ≈0.5, P<;0.0001). Our work takes a first step towards the optimization of CFAE detection between NavX and CARTO by providing revised thresholds to reduce differences in CFAE classification. This would facilitate direct comparisons of persAF CFAE-guided ablation outcome guided by NavX or CARTO.

Successful Ablation of Atrial Fibrillation by Targeting Fractionation in a Left‐Sided Superior Vena Cava

Successful Ablation of Atrial Fibrillation by Targeting Fractionation in a Left-Sided Superior Vena Cava GAVIN S. CHU, M.B.B.Chir.,∗,† ILARIA COVIELLO, M.D.,† ROBERTO MOLLO, M.D.,† and G. ANDRÉ NG, M.B.Ch.B., Ph.D.∗,†,‡ From the ∗Department of Cardiovascular Sciences, University of Leicester, Leicester, UK; †Department of Cardiology; and ‡Leicester NIHR Biomedical Research Unit in Cardiovascular Disease, Glenfield Hospital, Leicester, UK