Contributing factors concerning inconsistencies in persistent atrial fibrillation ablation outcomes

Background: We investigated current clinical methods for complex fractionated atrial electrogram (CFAE) classification during persistent atrial fibrillation (persAF). In particular, factors that directly influence the low reproducibility of CFAE-guided ablation outcomes in persAF therapy, such as inconsistencies in automated CFAE classification performed by different systems, the co-existence of different types of atrial electrograms (AEGs), and insufficient AEG duration for CFAE detection. Methods: 797 bipolar AEGs were exported from NavX (St. Jude Medical) from 18 persAF patients undergoing pulmonary vein isolation and roof line ablation (PVI+RL). CFE-Mean, CFE-StdDev and peak-to-peak were exported from NavX, while the interval confidence level, average and shortest complex interval – as defined by CARTO (Biosense Webster) – were calculated offline using a validated MATLAB script. Sample entropy, dominant frequency and organization index were also calculated offline. Results: First, we show that CFAE classification varies for the same individual, depending on the commercial system being used. Revised thresholds were found for the indices calculated by each system to minimize the differences in automated CFAE detection performed independently by them. Second, our results show that some AEGs are affected by PVI+RL in persAF, while others remain unaffected by it. Different types of AEGs might correlate with distinct underlying persAF mechanisms. Multivariate analysis using the multiple descriptors measured from the AEGs effectively discriminated the different types of AEGs. Finally, we show that consecutive AEGs with 2.5 s resulted in different ablation target identification using the CARTO criterion, which would affect the ablation strategy and contribute to conflicting outcomes in AEGguided ablation in persAF. Our results suggest that CARTO should consider AEGs with longer duration to measure CFAEs. Conclusions: A thorough re-evaluation of the definition of CFAE is necessary in order to refine the identification of critical atrial regions responsible for the perpetuation of the arrhythmia in patients with persAF

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

Characterization of Density of High Dominant Frequency Sites in Persistent Atrial Fibrillation Patients

Characterization of Density of High Dominant Frequency Sites in Persistent Atrial Fibrillation Patient

Dynamic Behavior of Rotors during Human Persistent Atrial Fibrillation as observed using Non-Contact Mapping

Rotors have been related to atrial fibrillation (AF) maintenance. We analyzed the behavior of rotors in persistent AF (persAF) utilizing a novel non-contact methodology and compared this to real time dominant frequency (DF) analysis. 2048 noncontact virtual unipolar atrial electrograms (VEGMs) were collected simultaneously (EnSite Array, St. Jude Medical) from 10 persAF patients (duration: 34 ± 25 months) undergoing left atrial (LA) ablation. After QRST-removal, FFT was used to identify the global DF of the LA (range 4 - 10 Hz; 1 s time-window; 50 % overlap; highest DF (HDF) (DF -0.25 Hz); up to 20 s/patient). The organization index (OI) was measured and phase was found via Hilbert-transform. Phase singularities (PSs) were tracked and were categorized according to their lifespan into short (lifespan <100 ms) and long lived (rotors) (lifespan ≥100 ms). A total of 4578 PSs were tracked. 5.05 % (IQR: 2.75 ~ 30.25 %) of the tracked PSs were long-lived and were observed in 11 % (IQR: 2.75 ~ 17.5 %) of the windows. The windows with rotors showed significantly higher HDF (mean ± SD, 8.0 ± 0.43 Hz vs 7.71 ± 0.50 Hz, p< 0.0001) and lower OI (0.76 ± 0.04 vs 0.79 ± 0.03, p< 0.0001) when compared with the short-lived PSs windows. During persAF, the LA showed distinct behaviors as characterized by rotors. Often, no rotors were observed during sustained AF and, when present, the rotors continually switched between organized and disorganized behaviors. Long-lived rotors correlated with higher atrial rates. Our results suggest that rotors are not the sole perpetuating mechanism in persAF

Evaluating spatial disparities of rotor sites and high dominant frequency regions during catheter ablation for PersAF patients targeting high dominant frequency sites using non-contacting mapping

Purpose: Several studies have emphasised the significance of high dominant frequency (HDF) and rotors in the perpetuation of AF. However, the co-localisation relationship between both attributes is not completely understood yet. In this study, we aim to evaluate the spatial distributions of HDF regions and rotor sites within the left atrium (LA) pre and post HDF-guided ablation in PersAF.Methods: This study involved 10 PersAF patients undergoing catheter ablation targeting HDF regions in the LA. 2048-channels of atrial electrograms (AEG) were collected pre- and post-ablation using a non-contact array (EnSite, Abbott). The dominant frequency (DF, 4–10 Hz) areas with DF within 0.25 Hz of the maximum out of the 2048 points were defined as “high” DF (HDF). Rotors were defined as PSs that last more than 100 ms and at a similar location through subsequent phase frames over time.Results: The results indicated an extremely poor spatial correlation between the HDF regions and sites of the rotors in pre-versus post-ablation cases for the non-terminated (pre: CORR; 0.05 ± 0.17. vs. post: CORR; −0.030 ± 0.19, and with terminated patients (pre: CORR; −0.016 ± 0.03. post: CORR; −0.022 ± 0.04). Rotors associated with AF terminations had a long-lasting life-span post-ablation (non-terminated vs. terminated 120.7 ± 6.5 ms vs. 139.9 ± 39.8 ms), high core velocity (1.35 ± 1.3 mm/ms vs. 1.32 ± 0.9 mm/ms), and were less meandering (3.4 ± 3.04 mm vs. 1.5 ± 1.2 mm). Although the results suggest a poor spatial overlapping between rotors’ sites and sites of AFCL changes in terminated and non-terminated patients, a higher correlation was determined in terminated patients (spatial overlapping percentage pre: 25 ± 4.2% vs. 17 ± 3.8% vs. post: 8 ± 4.2% vs. 3.7 ± 1.7% p < 0.05, respectively).Conclusion: Using non-contact AEG, it was noted that the correlation is poor between the spatial distribution of HDF regions and sites of rotors. Rotors were longer-lasting, faster and more stationary in patients with AF termination post-ablation. Rotors sites demonstrated poor spatial overlapping with sites of AFCL changes that lead to AF termination

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, however, 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

Contributing Factors Concerning Inconsistencies in Persistent Atrial Fibrillation Ablation Outcomes

Abstract In the present work, we investigated current methods for complex fractionated atrial electrogram (CFAE

Standardising single-frame phase singularity identification algorithms and parameters in phase mapping during human atrial fibrillation

Purpose: Recent investigations failed to reproduce the positive rotor-guided ablation outcomes shown by initial studies for treating persistent atrial fibrillation (persAF). Phase singularity (PS) is an important feature for AF driver detection, but algorithms for automated PS identification differ. We aim to investigate the performance of four different techniques for automated PS detection.Methods: 2048-channel virtual electrogram (VEGM) and electrocardiogram signals were collected for 30 s from ten patients undergoing persAF ablation. QRST-subtraction was performed and VEGMs were processed using sinusoidal wavelet reconstruction. The phase was obtained using Hilbert transform. PSs were detected using four algorithms: 1) 2D image processing based and neighbour-indexing algorithm; 2) 3D neighbour-indexing algorithm; 3) 2D kernel convolutional algorithm estimating topological charge; 4) topological charge estimation on 3D mesh. PS annotations were compared using the structural similarity index (SSIM) and Pearson’s correlation coefficient (CORR). Optimized parameters to improve detection accuracy were found for all four algorithms using Fβ score and 10-fold cross-validation compared with manual annotation. Local clustering with density-based spatial clustering of applications with noise (DBSCAN) was proposed to improve algorithms 3 and 4.Results: The PS density maps created by each algorithm with default parameters were poorly correlated. Phase gradient threshold and search radius (or kernels) were shown to affect PS detections. The processing times for the algorithms were significantly different (pConclusion: AF driver identification is dependent on the PS detection algorithms and their parameters, which could explain some of the inconsistencies in rotor-guided ablation outcomes in different studies. For 3D triangulated meshes, algorithm 4+DBSCAN with optimal parameters was the best solution for real-time, automated PS detection due to accuracy and speed. Similarly, algorithm 3+DBSCAN with optimal parameters is preferred for uniform 2D meshes. Such algorithms – and parameters – should be preferred in future clinical studies for identifying AF drivers and minimising methodological heterogeneities. This would facilitate comparisons in rotor-guided ablation outcomes in future works