Noninvasive Assessment of Atrial Fibrillation Complexity in Relation to Ablation Characteristics and Outcome

Manifold analysis of the P-wave changes induced by pulmonary vein isolation during cryoballoon procedure

BACKGROUND/AIM

In atrial fibrillation (AF) ablation procedures, it is desirable to know whether a proper disconnection of the pulmonary veins (PVs) was achieved. We hypothesize that information about their isolation could be provided by analyzing changes in P-wave after ablation. Thus, we present a method to detect PV disconnection using P-wave signal analysis.

METHODS

Conventional P-wave feature extraction was compared to an automatic feature extraction procedure based on creating low-dimensional latent spaces for cardiac signals with the Uniform Manifold Approximation and Projection (UMAP) method. A database of patients (19 controls and 16 AF individuals who underwent a PV ablation procedure) was collected. Standard 12-lead ECG was recorded, and P-waves were segmented and averaged to extract conventional features (duration, amplitude, and area) and their manifold representations provided by UMAP on a 3-dimensional latent space. A virtual patient was used to validate these results further and study the spatial distribution of the extracted characteristics over the whole torso surface.

RESULTS

Both methods showed differences between P-wave before and after ablation. Conventional methods were more prone to noise, P-wave delineation errors, and inter-patient variability. P-wave differences were observed in the standard leads recordings. However, higher differences appeared in the torso region over the precordial leads. Recordings near the left scapula also yielded noticeable differences.

CONCLUSIONS

P-wave analysis based on UMAP parameters detects PV disconnection after ablation in AF patients and is more robust than heuristic parameterization. Moreover, additional leads different from the standard 12-lead ECG should be used to detect PV isolation and possible future reconnections better.

A 3D-CNN with temporal-attention block to predict the recurrence of atrial fibrillation based on body-surface potential mapping signals

Catheter ablation has become an important treatment for atrial fibrillation (AF), but its recurrence rate is still high. The aim of this study was to predict AF recurrence using a three-dimensional (3D) network model based on body-surface potential mapping signals (BSPMs). BSPMs were recorded with a 128-lead vest in 14 persistent AF patients before undergoing catheter ablation (Maze-IV). The torso geometry was acquired and meshed by point cloud technology, and the BSPM was interpolated into the torso geometry by the inverse distance weighted (IDW) method to generate the isopotential map. Experiments show that the isopotential map of BSPMs can reflect the propagation of the electrical wavefronts. The 3D isopotential sequence map was established by combining the spatial–temporal information of the isopotential map; a 3D convolutional neural network (3D-CNN) model with temporal attention was established to predict AF recurrence. Our study proposes a novel attention block that focuses the characteristics of atrial activations to improve sampling accuracy. In our experiment, accuracy (ACC) in the intra-patient evaluation for predicting the recurrence of AF was 99.38%. In the inter-patient evaluation, ACC of 3D-CNN was 81.48%, and the area under the curve (AUC) was 0.88. It can be concluded that the dynamic rendering of multiple isopotential maps can not only comprehensively display the conduction of cardiac electrical activity on the body surface but also successfully predict the recurrence of AF after CA by using 3D isopotential sequence maps.

Novel spatiotemporal processing tools for body-surface potential map signals for the prediction of catheter ablation outcome in persistent atrial fibrillation

Background: Signal processing tools are required to efficiently analyze data collected in body-surface-potential map (BSPM) recordings. A limited number of such tools exist for studying persistent atrial fibrillation (persAF). We propose two novel, spatiotemporal indices for processing BSPM data and test their clinical applicability through a comparison with the recently proposed non-dipolar component index (NDI) for prediction of single-procedure catheter ablation (CA) success rate in persAF patients.

Methods: BSPM recordings were obtained with a 252-lead vest in 13 persAF patients (8 men, 63 ± 8 years, 11 ± 13 months sustained AF duration) before undergoing CA. Each recording was divided into seven 1-min segments of high signal quality. Spatiotemporal ventricular activity (VA) cancellation was applied to each segment to isolate atrial activity (AA). The two novel indices, called error-ratio, normalized root-mean-square error (ERNRMSE) and error-ratio, mean-absolute error (ERABSE), were calculated. These indices quantify the capacity of a subset of BSPM vest electrodes to accurately represent the AA, and AA dominant frequency (DF), respectively, on all BSPM electrodes over time, compared to the optimal principal component analysis (PCA) representation. The NDI, quantifying the fraction of energy retained after removal of the three largest PCs, was also calculated. The two novel indices and the NDI were statistically compared between patient groups based on single-procedure clinical CA outcome. Finally, their predictive power for univariate CA outcome classification was assessed using receiver operating characteristic (ROC) analysis with cross-validation for a logistic regression classifier.

Results: Patient clinical outcomes were recorded 6 months following procedures, and those who had an arrhythmia recurrence at least 2 months post-CA were defined as having a negative outcome. Clinical outcome information was available for 11 patients, 6 with arrhythmia recurrence. Therefore, a total of 77 1-min AA-BSPM segments were available for analysis. Significant differences were found in the values of the novel indices and NDI between patients with arrhythmia recurrence post-ablation and those without. ROC analysis showed the best CA outcome predictive performance for ERNRMSE (AUC = 0.77 ± 0.08, sensitivity = 76.2%, specificity = 84.8%).

Conclusion: Significant association was found between the novel indices and CA success or failure. The novel index ERNRMSE additionally shows good predictive power for single-procedure CA outcome.

Bi‐atrial characterization of the electrical substrate in patients with atrial fibrillation

Background

Methods

Results

Conclusion

Extended ECG Improves Classification of Paroxysmal and Persistent Atrial Fibrillation Based on P- and f-Waves

Background

The standard 12-lead ECG has been shown to be of value in characterizing atrial conduction properties. The added value of extended ECG recordings (longer recordings from more sites) has not been systematically explored yet.

Objective

The aim of this study is to employ an extended ECG to identify characteristics of atrial electrical activity related to paroxysmal vs. persistent atrial fibrillation (AF).

Methods

In 247 participants scheduled for AF ablation, an extended ECG was recorded (12 standard plus 3 additional leads, 5 min recording, no filtering). For patients presenting in sinus rhythm (SR), the signal-averaged P-wave and the spatiotemporal P-wave variability was analyzed. For patients presenting in AF, f-wave properties in the QRST (the amplitude complex of the ventricular electrical activity: Q-, R-, S-, and T-wave)-canceled ECG were determined.

Results

Significant differences between paroxysmal (N = 152) and persistent patients with AF (N = 95) were found in several P-wave and f-wave parameters, including parameters that can only be calculated from an extended ECG. Furthermore, a moderate, but significant correlation was found between echocardiographic parameters and P-wave and f-wave parameters. There was a moderate correlation of left atrial (LA) diameter with P-wave energy duration (r = 0.317, p < 0.001) and f-wave amplitude in lead A3 (r = -0.389, p = 0.002). The AF-type classification performance significantly improved when parameters calculated from the extended ECG were taken into account [area under the curve (AUC) = 0.58, interquartile range (IQR) 0.50-0.64 for standard ECG parameters only vs. AUC = 0.76, IQR 0.70-0.80 for extended ECG parameters, p < 0.001].

Conclusion

The P- and f-wave analysis of extended ECG configurations identified specific ECG features allowing improved classification of paroxysmal vs. persistent AF. The extended ECG significantly improved AF-type classification in our analyzed data as compared to a standard 10-s 12-lead ECG. Whether this can result in a better clinical AF type classification warrants further prospective study.

Electrocardiographic Imaging for Atrial Fibrillation: A Perspective From Computer Models and Animal Experiments to Clinical Value

Electrocardiographic imaging (ECGI) is a technique to reconstruct non-invasively the electrical activity on the heart surface from body-surface potential recordings and geometric information of the torso and the heart. ECGI has shown scientific and clinical value when used to characterize and treat both atrial and ventricular arrhythmias. Regarding atrial fibrillation (AF), the characterization of the electrical propagation and the underlying substrate favoring AF is inherently more challenging than for ventricular arrhythmias, due to the progressive and heterogeneous nature of the disease and its manifestation, the small volume and wall thickness of the atria, and the relatively large role of microstructural abnormalities in AF. At the same time, ECGI has the advantage over other mapping technologies of allowing a global characterization of atrial electrical activity at every atrial beat and non-invasively. However, since ECGI is time-consuming and costly and the use of electrical mapping to guide AF ablation is still not fully established, the clinical value of ECGI for AF is still under assessment. Nonetheless, AF is known to be the manifestation of a complex interaction between electrical and structural abnormalities and therefore, true electro-anatomical-structural imaging may elucidate important key factors of AF development, progression, and treatment. Therefore, it is paramount to identify which clinical questions could be successfully addressed by ECGI when it comes to AF characterization and treatment, and which questions may be beyond its technical limitations. In this manuscript we review the questions that researchers have tried to address on the use of ECGI for AF characterization and treatment guidance (for example, localization of AF triggers and sustaining mechanisms), and we discuss the technological requirements and validation. We address experimental and clinical results, limitations, and future challenges for fruitful application of ECGI for AF understanding and management. We pay attention to existing techniques and clinical application, to computer models and (animal or human) experiments, to challenges of methodological and clinical validation. The overall objective of the study is to provide a consensus on valuable directions that ECGI research may take to provide future improvements in AF characterization and treatment guidance.

Insights Into the Spatiotemporal Patterns of Complexity of Ventricular Fibrillation by Multilead Analysis of Body Surface Potential Maps

BACKGROUND

Ventricular fibrillation (VF) is the main cause of sudden cardiac death, but its mechanisms are still unclear. We propose a noninvasive approach to describe the progression of VF complexity from body surface potential maps (BSPMs).

METHODS

We mapped 252 VF episodes (16 ± 10 s) with a 252-electrode vest in 110 patients (89 male, 47 ± 18 years): 50 terminated spontaneously, otherwise by electrical cardioversion (DCC). Changes in complexity were assessed between the onset ("VF start") and the end ("VF end") of VF by the nondipolar component index (N D I B S P M ), measuring the fraction of energy nonpreserved by an equivalent 3D dipole from BSPMs. Higher NDI reflected lower VF organization. We also examined other standard body surface markers of VF dynamics, including fibrillatory wave amplitude (A BSPM ), surface cycle length (BsCL BSPM ) and Shannon entropy (S h E n B S P M ). Differences between patients with and without structural heart diseases (SHD, 32 vs. NSHD, 78) were also tested at those stages. Electrocardiographic features were validated with simultaneous endocardium cycle length (CL) in a subset of 30 patients.

RESULTS

All BSPM markers measure an increase in electrical complexity during VF (p < 0.0001), and more significantly in NSHD patients. Complexity is significantly higher at the end of sustained VF episodes requiring DCC. Intraepisode intracardiac CL shortening (VF start 197 ± 24 vs. VF end 169 ± 20 ms; p < 0.0001) correlates with an increase in NDI, and decline in surface CL, f-wave amplitude, and entropy (p < 0.0001). In SHD patients VF is initially more complex than in NSHD patients (N D I B S P M , p = 0.0007; S h E n B S P M , p < 0.0001), with moderately slower (BsCL BSPM , p = 0.06), low-amplitude f-waves (A BSPM , p < 0.0001). In this population, lower NDI (p = 0.004) and slower surface CL (p = 0.008) at early stage of VF predict self-termination. In the NSHD group, a more abrupt increase in VF complexity is quantified by all BSPM parameters during sustained VF (p < 0.0001), whereas arrhythmia evolution is stable during self-terminating episodes, hinting at additional mechanisms driving VF dynamics.

CONCLUSION

Multilead BSPM analysis underlines distinct degrees of VF complexity based on substrate characteristics.

Long-Lasting Ventricular Fibrillation in Humans ECG Characteristics and Effect of Radiofrequency Ablation

BACKGROUND

Studies of ventricular fibrillation (VF) in humans are limited because of the short available duration. We sought to study surface ECG waveforms and effect of ablation in long-lasting VF in patients with left assist devices.

METHODS

Continuous 12-lead ECG of 5 episodes of long-lasting VF occurring in 3 patients with left ventricular assist device were analyzed. Spectral analysis (dominant frequency) and quantification of waveform amplitude, regularity (Unbiased Regularity Index), and complexity (Nondipolar Index) were performed over a median of 24 minutes of VF. Radiofrequency ablation was performed during VF in 2 patients.

RESULTS

There was a significant increase in dominant frequency between VF onset and termination but none of the other parameters significantly changed. Some VF parameters varied from patient to patient and from lead to lead. Dominant frequency decreased after radiofrequency ablation in both cases and VF terminated spontaneously shortly after ablation in one case. The previously incessant VFs in these 2 patients did not recur afterward.

CONCLUSIONS

VF rate increases over time in patients with left ventricular assist devices and is lowered by ablation. Long-lasting VF may be modified or even terminated by ablation.

Ranolazine-Mediated Attenuation of Mechanoelectric Feedback in Atrial Myocyte Monolayers

Background

Mechanical stretch increases Na⁺ inflow into myocytes, related to mechanisms including stretch-activated channels or Na⁺/H⁺ exchanger activation, involving Ca²⁺ increase that leads to changes in electrophysiological properties favoring arrhythmia induction. Ranolazine is an antianginal drug with confirmed beneficial effects against cardiac arrhythmias associated with the augmentation of I_NaL current and Ca²⁺ overload.

Objective

This study investigates the effects of mechanical stretch on activation patterns in atrial cell monolayers and its pharmacological response to ranolazine.

Methods

Confluent HL-1 cells were cultured in silicone membrane plates and were stretched to 110% of original length. The characteristics of in vitro fibrillation (dominant frequency, regularity index, density of phase singularities, rotor meandering, and rotor curvature) were analyzed using optical mapping in order to study the mechanoelectric response to stretch under control conditions and ranolazine action.

Results

HL-1 cell stretch increased fibrillatory dominant frequency (3.65 ± 0.69 vs. 4.35 ± 0.74 Hz, p < 0.01) and activation complexity (1.97 ± 0.45 vs. 2.66 ± 0.58 PS/cm², p < 0.01) under control conditions. These effects were related to stretch-induced changes affecting the reentrant patterns, comprising a decrease in rotor meandering (0.72 ± 0.12 vs. 0.62 ± 0.12 cm/s, p < 0.001) and an increase in wavefront curvature (4.90 ± 0.42 vs. 5.68 ± 0.40 rad/cm, p < 0.001). Ranolazine reduced stretch-induced effects, attenuating the activation rate increment (12.8% vs. 19.7%, p < 0.01) and maintaining activation complexity—both parameters being lower during stretch than under control conditions. Moreover, under baseline conditions, ranolazine slowed and regularized the activation patterns (3.04 ± 0.61 vs. 3.65 ± 0.69 Hz, p < 0.01).

Conclusion

Ranolazine attenuates the modifications of activation patterns induced by mechanical stretch in atrial myocyte monolayers.

The impact of the dominant frequency of body surface electrocardiography in patients with persistent atrial fibrillation

The dominant frequency (DF) of atrial fibrillation (AF) reflects atrial electrical activity. However, the relationship between DF measured using surface electrocardiography (ECG) and AF ablation success remains unclear. This study aimed to clarify whether the DF of surface ECG in patients with persistent AF could predict arrhythmia recurrence after catheter ablation. We investigated 125 patients with persistent AF who underwent catheter ablation between January 2009 and December 2016. Thirty-four patients (27%) had arrhythmia recurrence after catheter ablation. These patients showed a significantly high DF value in leads aVL (7.2 ± 0.7 Hz vs 6.6 ± 0.9 Hz, p < 0.001) and V1 (7.4 ± 0.8 Hz vs 6.7 ± 0.7 Hz, p < 0.001). We set the cutoff value of DF as 6.9 Hz in lead aVL (sensitivity, 80%; specificity, 63%) and as 7.1 Hz in lead V1 (sensitivity, 72%; specificity, 67%). Patients with DF < 6.9 Hz in lead aVL showed a significantly higher recurrence-free rate than those with DF ≥ 6.9 Hz (88% vs 45%; p < 0.001). Patients with DF of < 7.1 Hz in lead V1 showed a significantly higher recurrence-free rate than those with DF of  ≥ 7.1 (87% vs 47%; p < 0.001). Patients with a high DF in leads aVL and V1 showed a lower success rate of persistent AF ablation. The DF measured from surface ECG can be a useful marker to predict ablation success.

Locating Atrial Fibrillation Rotor and Focal Sources Using Iterative Navigation of Multipole Diagnostic Catheters

Purpose

Multi-polar diagnostic catheters are used to construct the 3D electro-anatomic mapping of the atrium during atrial fibrillation (AF) ablation procedures; however, it remains unclear how to use the electrograms recorded by these catheters to locate AF-driving sites known as focal and rotor source types. The purpose of this study is to present the first algorithm to iteratively navigate a circular multi-polar catheter to locate AF focal and rotor sources without the need to map the entire atria.

Methods

Starting from an initial location, the algorithm, which was blinded to the location and type of the AF source, iteratively advanced a Lasso catheter based on its electrogram characteristics. The algorithm stopped the catheter when it located of an AF source and identified the type. The efficiency of the algorithm is validated using a set of simulated focal and rotor-driven arrhythmias in fibrotic human 2D and 3D atrial tissue.

Results

Our study shows the feasibility of locating AF sources with a success rate of greater than 95.25% within average 7.56 ± 2.28 placements independently of the initial position of the catheter and the source type.

Conclusions

The algorithm could play a critical role in clinical electrophysiology laboratories for mapping patient-specific ablation of AF sources located outside the pulmonary veins and improving the procedure success.

Electronic supplementary material

The online version of this article (10.1007/s13239-019-00414-5) contains supplementary material, which is available to authorized users.

Iterative navigation of multipole diagnostic catheters to locate repeating-pattern atrial fibrillation drivers

Introduction

Targeting repeating‐pattern atrial fibrillation (AF) sources (reentry or focal drivers) can help in patient‐specific ablation therapy for AF; however, the development of reliable and accurate tools for locating such sources remains a major challenge. We describe iterative catheter navigation (ICAN) algorithm to locate AF drivers using a conventional circular Lasso catheter.

Methods and Results

At each step, the algorithm analyzes 10 bipolar electrograms recoded at a given catheter location and the history of previous catheter movements to determine if the source is inside the catheter loop. If not, it calculates new coordinates and selects a new position for the catheter. The process continues until a source is located. The algorithm was evaluated in a computer model of atrial tissue with various degrees of fibrosis under a broad range of arrhythmia scenarios. The latter included slow and fast reentry, macroreentry, figure‐of‐eight reentry, and fibrillatory conduction. Depending on the initial distance of the catheter from the source and scenario, it took about 3 to 16 steps to localize an AF source. In 94% of cases, the identified location was within 4 mm from the source, independently of the initial position of the catheter. The algorithm worked equally well in the presence of patchy fibrosis, low‐voltage areas, fragmented electrograms, and dominant‐frequency gradients.

Conclusions

AF repeating‐pattern sources can be localized using circular catheters without the need to map the entire tissue. The proposed algorithm has the potential to become a useful tool for patient‐specific ablation of AF sources located outside the pulmonary veins.