Low-Voltage Zones as the Atrial Fibrillation Substrates: Relationship With Initiation, Perpetuation, and Termination

The impact of atrial voltage and conduction velocity phenotypes on atrial fibrillation recurrence

Introduction

Low atrial voltage and slow conduction velocity (CV) have been associated with atrial fibrillation (AF); however, their interaction and relative importance as early disease markers remain incompletely understood. We aimed to elucidate the relationship between atrial voltage and CV using high-density electroanatomic (HDE) maps of patients with AF.

Methods

HDE maps obtained during sinus rhythm in 52 patients with AF and five healthy controls were analysed. Atrial voltage and CV maps were generated, and their correlations were assessed. Subgroup analyses were performed based on clinically relevant factors such as AF type, CV, and voltage levels. Finally, cluster analysis was conducted to identify distinct phenotypes within the population, reflecting different patterns of conduction and voltage.

Results

A moderate positive correlation was found between the mean atrial voltage and CV (r = 0.570). Subgroup analysis revealed differences in voltage (p = 0.0044) but not in global CV (p = 0.42), with no significant differences between AF types. Three distinct phenotypes emerged: normal voltage/normal CV, normal voltage/low CV, and low voltage/low CV, with distinct recurrence rates, suggesting different disease progression paths. Slower atrial CV was identified as a significant predictor of arrhythmia recurrence at 12 and 24 months after AF ablation, surpassing the predictive potential of atrial voltage.

Conclusion

Atrial voltage and CV analyses revealed distinct phenotypes. Lower atrial CV emerged as a significant predictor of AF recurrence, exceeding the predictive significance of atrial voltage. These findings emphasise the importance of considering CV and voltage in managing AF and offer potential insights for personalised strategies.

Automatic Echocardiographic Assessment of Left Atrial Function for Prediction of Low-Voltage Areas in Non-Valvular Atrial Fibrillation

Purpose

Left atrial low-voltage areas (LA-LVAs) identified by 3D-electroanatomical mapping are crucial for determining treatment strategies and prognosis in patients with atrial fibrillation (AF). However, convenient and accurate prediction of LA-LVAs remains challenging. This study aimed to assess the viability of utilizing automatically obtained echocardiographic parameters to predict the presence of LA-LVAs in patients with non-valvular atrial fibrillation (NVAF).

Patients and Methods

This retrospective study included 190 NVAF patients who underwent initial catheter ablation. Before ablation, echocardiographic data were obtained, left atrial volume and strain were automatically calculated using advanced software (Dynamic-HeartModel and AutoStrain). Electroanatomic mapping (EAM) was also performed. Results were compared between patients with LA-LVAs ≥5% (LVAs group) and <5% (non-LVAs group).

Results

LA-LVAs were observed in 81 patients (42.6%), with a significantly higher incidence in those with persistent AF than paroxysmal AF (55.6% vs 19.3%, P <0.001). Compared with the non-LVAs group, the LVAs group included significantly older patients, lower left ventricular ejection fraction, higher heart rate, and higher E/e' ratio (P <0.05). The LVAs group exhibited higher left atrial volumemax index (LAVimax) and lower left atrial reservoir strain (LASr) (P <0.001). In multivariate analysis, both LAVimax and LASr emerged as independent indicators of LVAs (OR 0.85; 95% CI 0.80-0.90, P<0.001) and (OR 1.15, 95% CI 1.02-1.29, P =0.021). ROC analysis demonstrated good predictive capacity for LA-LVAs, with an AUC of 0.733 (95% CI 0.650-0.794, P <0.001) for LAVimax and 0.839 (95% CI 0.779-0.898, P <0.001) for LASr.

Conclusion

Automatic assessment of LAVimax and LASr presents a promising non-invasive modality for predicting the presence of LA-LVAs and evaluating significant atrial remodeling in NVAF patients. This approach holds potential for aiding in risk stratification and treatment decision-making, ultimately improving clinical outcomes in patients.

Atrial Fibrillation and Underlying Structural and Electrophysiological Heterogeneity

As atrial fibrillation (AF) progresses from initial paroxysmal episodes to the persistent phase, maintaining sinus rhythm for an extended period through pharmacotherapy and catheter ablation becomes difficult. A major cause of the deteriorated treatment outcome is the atrial structural and electrophysiological heterogeneity, which AF itself can exacerbate. This heterogeneity exists or manifests in various dimensions, including anatomically segmental structural features, the distribution of histological fibrosis and the autonomic nervous system, sarcolemmal ion channels, and electrophysiological properties. All these types of heterogeneity are closely related to the development of AF. Recognizing the heterogeneity provides a valuable approach to comprehending the underlying mechanisms in the complex excitatory patterns of AF and the determining factors that govern the seemingly chaotic propagation. Furthermore, substrate modification based on heterogeneity is a potential therapeutic strategy. This review aims to consolidate the current knowledge on structural and electrophysiological atrial heterogeneity and its relation to the pathogenesis of AF, drawing insights from clinical studies, animal and cell experiments, molecular basis, and computer-based approaches, to advance our understanding of the pathophysiology and management of AF.

Structural and electrophysiological determinants of atrial cardiomyopathy identify remodeling discrepancies between paroxysmal and persistent atrial fibrillation

Background

Progressive atrial fibrotic remodeling has been reported to be associated with atrial cardiomyopathy (ACM) and the transition from paroxysmal to persistent atrial fibrillation (AF). We sought to identify the anatomical/structural and electrophysiological factors involved in atrial remodeling that promote AF persistency.

Methods

Consecutive patients with paroxysmal (n = 134) or persistent (n = 136) AF who presented for their first AF ablation procedure were included. Patients underwent left atrial (LA) high-definition mapping (1,835 ± 421 sites/map) during sinus rhythm (SR) and were randomized to training and validation sets for model development and evaluation. A total of 62 parameters from both electro-anatomical mapping and non-invasive baseline data were extracted encompassing four main categories: (1) LA size, (2) extent of low-voltage-substrate (LVS), (3) LA voltages and (4) bi-atrial conduction time as identified by the duration of amplified P-wave (APWD) in a digital 12-lead-ECG. Least absolute shrinkage and selection operator (LASSO) and logistic regression were performed to identify the factors that are most relevant to AF persistency in each category alone and all categories combined. The performance of the developed models for diagnosis of AF persistency was validated regarding discrimination, calibration and clinical usefulness. In addition, HATCH score and C2HEST score were also evaluated for their performance in identification of AF persistency.

Results

In training and validation sets, APWD (threshold 151 ms), LA volume (LAV, threshold 94 mL), bipolar LVS area < 1.0 mV (threshold 4.55 cm²) and LA global mean voltage (GMV, threshold 1.66 mV) were identified as best determinants for AF persistency in the respective category. Moreover, APWD (AUC 0.851 and 0.801) and LA volume (AUC 0.788 and 0.741) achieved better discrimination between AF types than LVS extent (AUC 0.783 and 0.682) and GMV (AUC 0.751 and 0.707). The integrated model (combining APWD and LAV) yielded the best discrimination performance between AF types (AUC 0.876 in training set and 0.830 in validation set). In contrast, HATCH score and C2HEST score only achieved AUC < 0.60 in identifying individuals with persistent AF in current study.

Conclusion

Among 62 electro-anatomical parameters, we identified APWD, LA volume, LVS extent, and mean LA voltage as the four determinant electrophysiological and structural factors that are most relevant for AF persistency. Notably, the combination of APWD with LA volume enabled discrimination between paroxysmal and persistent AF with high accuracy, emphasizing their importance as underlying substrate of persistent AF.