Regional conduction velocities determined by noninvasive mapping are associated with arrhythmia-free survival after atrial fibrillation ablation.

BACKGROUND: Atrial arrhythmogenic substrate is a key determinant of atrial fibrillation (AF) recurrence after pulmonary vein isolation (PVI), and reduced conduction velocities have been linked to adverse outcome. However, a noninvasive method to assess such electrophysiologic substrate is not available to date. OBJECTIVE: This study aimed to noninvasively assess regional conduction velocities and their association with arrhythmia-free survival after PVI. METHODS: A consecutive 52 patients scheduled for AF ablation (PVI only) and 19 healthy controls were prospectively included and received electrocardiographic imaging (ECGi) to noninvasively determine regional atrial conduction velocities in sinus rhythm. A novel ECGi technology obviating the need of additional computed tomography or cardiac magnetic resonance imaging was applied and validated by invasive mapping. RESULTS: Mean ECGi-determined atrial conduction velocities were significantly lower in AF patients than in healthy controls (1.45 ± 0.15 m/s vs 1.64 ± 0.15 m/s; P < .0001). Differences were particularly pronounced in a regional analysis considering only the segment with the lowest average conduction velocity in each patient (0.8 ± 0.22 m/s vs 1.08 ± 0.26 m/s; P < .0001). This average conduction velocity of the "slowest" segment was independently associated with arrhythmia recurrence and better discriminated between PVI responders and nonresponders than previously proposed predictors, including left atrial size and late gadolinium enhancement (magnetic resonance imaging). Patients without slow-conduction areas (mean conduction velocity <0.78 m/s) showed significantly higher 12-month arrhythmia-free survival than those with 1 or more slow-conduction areas (88.9% vs 48.0%; P = .002). CONCLUSION: This is the first study to investigate regional atrial conduction velocities noninvasively. The absence of ECGi-determined slow-conduction areas well discriminates PVI responders from nonresponders. Such noninvasive assessment of electrical arrhythmogenic substrate may guide treatment strategies and be a step toward personalized AF therapy.

Standardized 2D atrial mapping and its clinical applications.

The visualization and comparison of electrophysiological information in the atrium among different patients could be facilitated by a standardized 2D atrial mapping. However, due to the complexity of the atrial anatomy, unfolding the 3D geometry into a 2D atrial mapping is challenging. In this study, we aim to develop a standardized approach to achieve a 2D atrial mapping that connects the left and right atria, while maintaining fixed positions and sizes of atrial segments across individuals. Atrial segmentation is a prerequisite for the process. Segmentation includes 19 different segments with 12 segments from the left atrium, 5 segments from the right atrium, and two segments for the atrial septum. To ensure consistent and physiologically meaningful segment connections, an automated procedure is applied to open up the atrial surfaces and project the 3D information into 2D. The corresponding 2D atrial mapping can then be utilized to visualize different electrophysiological information of a patient, such as activation time patterns or phase maps. This can in turn provide useful information for guiding catheter ablation. The proposed standardized 2D maps can also be used to compare more easily structural information like fibrosis distribution with rotor presence and location. We show several examples of visualization of different electrophysiological properties for both healthy subjects and patients affected by atrial fibrillation. These examples show that the proposed maps provide an easy way to visualize and interpret intra-subject information and perform inter-subject comparison, which may provide a reference framework for the analysis of the atrial fibrillation substrate before treatment, and during a catheter ablation procedure.

Conduction System Pacing vs Biventricular Pacing in Heart Failure and Wide QRS Patients: LEVEL-AT Trial.

BACKGROUND: Conduction system pacing (CSP) has emerged as an alternative to biventricular pacing (BiVP). Randomized studies comparing both therapies are scarce and do not include left bundle branch pacing. OBJECTIVES: This study aims to compare ventricular resynchronization achieved by CSP vs BiVP in patients with cardiac resynchronization therapy indication. METHODS: LEVEL-AT (Left Ventricular Activation Time Shortening with Conduction System Pacing vs Biventricular Resynchronization Therapy) was a randomized, parallel, controlled, noninferiority trial. Seventy patients with cardiac resynchronization therapy indication were randomized 1:1 to BiVP or CSP, and followed up for 6 months. Crossover was allowed when primary allocation procedure failed. Primary endpoint was the change in left ventricular activation time, measured using electrocardiographic imaging. Secondary endpoints were left ventricular reverse remodeling and the combined endpoint of heart failure hospitalization or death at 6-month follow-up. RESULTS: Thirty-five patients were allocated to each group. Eight (23%) patients crossed over from CSP to BiVP; 2 patients (6%) crossed over from BiVP to CSP. Electrocardiographic imaging could not be performed in 2 patients in each group. A similar decrease in left ventricular activation time was achieved by CSP and BiVP (-28 ± 26 ms vs -21 ± 20 ms, respectively; mean difference -6.8 ms; 95% CI: -18.3 ms to 4.6 ms; P < 0.001 for noninferiority). Both groups showed a similar change in left ventricular end-systolic volume (-37 ± 59 mL CSP vs -30 ± 41 mL BiVP; mean difference: -8 mL; 95% CI: -33 mL to 17 mL; P = 0.04 for noninferiority) and similar rates of mortality or heart failure hospitalizations (2.9% vs 11.4%, respectively) (P = 0.002 for noninferiority). CONCLUSIONS: Similar degrees of cardiac resynchronization, ventricular reverse remodeling, and clinical outcomes were attained by CSP as compared to BiVP. CSP could be a feasible alternative to BiVP. (LEVEL-AT [Left Ventricular Activation Time Shortening With Conduction System Pacing vs Biventricular Resynchronization Therapy]; NCT04054895).

Atrial fibrosis identification with unipolar electrogram eigenvalue distribution analysis in multi-electrode arrays.

Atrial fibrosis plays a key role in the initiation and progression of atrial fibrillation (AF). Atrial fibrosis is typically identified by a peak-to-peak amplitude of bipolar electrograms (b-EGMs) lower than 0.5 mV, which may be considered as ablation targets. Nevertheless, this approach disregards signal spatiotemporal information and b-EGM sensitivity to catheter orientation. To overcome these limitations, we propose the dominant-to-remaining eigenvalue dominance ratio (EIGDR) of unipolar electrograms (u-EGMs) within neighbor electrode cliques as a waveform dispersion measure, hypothesizing that it is correlated with the presence of fibrosis. A simulated 2D tissue with a fibrosis patch was used for validation. We computed EIGDR maps from both original and time-aligned u-EGMs, denoted as [Formula: see text] and [Formula: see text], respectively, also mapping the gain in eigenvalue concentration obtained by the alignment, [Formula: see text]. The performance of each map in detecting fibrosis was evaluated in scenarios including noise and variable electrode-tissue distance. Best results were achieved by [Formula: see text], reaching 94% detection accuracy, versus the 86% of b-EGMs voltage maps. The proposed strategy was also tested in real u-EGMs from fibrotic and non-fibrotic areas over 3D electroanatomical maps, supporting the ability of the EIGDRs as fibrosis markers, encouraging further studies to confirm their translation to clinical settings. Upper panels: map of [Formula: see text] from 3×3 cliques for Ψ= 0∘ and bipolar voltage map Vb-m, performed assuming a variable electrode-to-tissue distance and noisy u-EGMs (noise level σv = 46.4 µV ). Lower panels: detected fibrotic areas (brown), using the thresholds that maximize detection accuracy of each map.