Regional left atrial conduction velocity in the anterior wall is associated with clinical recurrence of atrial fibrillation after catheter ablation: efficacy in combination with the ipsilateral low voltage area

Identifying extra pulmonary vein targets for persistent atrial fibrillation ablation: bridging advanced and conventional mapping techniques

AIMS

Advanced technologies such as charge density mapping (CDM) show promise in guiding adjuvant ablation in patients with persistent atrial fibrillation (AF); however, their limited availability restricts widespread adoption. We sought to determine whether regions of the left atrium containing CDM-identified pivoting and rotational propagation patterns during AF could also be reliably identified using more conventional contact mapping techniques.

METHODS AND RESULTS

Twenty-two patients undergoing de novo ablation of persistent AF underwent both CDM and electroanatomic voltage mapping during AF and sinus rhythm with multiple pacing protocols. Through the use of a left atrium statistical shape model, the location of distinctive propagation patterns identified by CDM was compared with low-voltage areas (LVAs) and regions of slow conduction velocity (CV). Neither LVA nor CV mapping during paced rhythms reliably identified regions containing CDM propagation patterns. Conduction velocity mapping during AF did correlate with these regions (ρ = -0.63, P < 0.0001 for pivoting patterns; ρ = -0.54, P < 0.0001 for rotational patterns). These propagation patterns consistently occurred in two specific anatomical regions across patients: the anteroseptal and inferoposterior walls of the left atrium.

CONCLUSION

Mapping techniques during paced rhythms do not reliably correspond with regions of CDM-identified propagation patterns in persistent AF. However, these propagation patterns are consistently observed in two specific anatomical regions, suggesting a predisposition to abnormal electrophysiological properties. While further research is needed, these regions may serve as promising targets for empirical ablation, potentially reducing the reliance on complex mapping techniques.

Multi-modal integration of MRI and global chamber charge density mapping for the evaluation of atrial fibrillation

Atrial fibrillation (AF) is the most prevalent clinical arrhythmia, posing significant mortality and morbidity challenges. Outcomes of current catheter ablation treatment strategies are suboptimal, highlighting the need for innovative approaches. A major obstacle lies in the inability to comprehensively assess both structural and functional remodelling in AF. Combining magnetic resonance imaging (MRI)'s detailed structural insights with global chamber charge density mapping (CDM)'s functional mapping capabilities holds promise for advancing AF management. Our research introduces a novel tool for three-dimensional reconstruction of left atrial geometries from MRI, facilitating integration into CDM systems. We comprehensively assess our tool by generating three-dimensional left atrial meshes from MRIs of eight patients with AF and compare them with the established CDM intra-chamber ultrasound approach utilizing both geometric and clinical parameters. We apply the CDM inverse algorithm to both sets of reconstructions in order to compare derived conductions across various heart rhythms and AF conduction patterns. Finally, we explore the potential utility of our integrated pipeline through an exploration of the relationship between AF conduction patterns and their proximity to adjacent thoracic structures. Ultimately, this multifaceted approach aims to unveil insights into AF mechanisms, potentially improving treatment outcomes through personalized ablation strategies targeting arrhythmogenic atrial substrate.

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.

Leveraging 3D Atrial Geometry for the Evaluation of Atrial Fibrillation: A Comprehensive Review

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia associated with significant morbidity and mortality. Managing risk of stroke and AF burden are pillars of AF management. Atrial geometry has long been recognized as a useful measure in achieving these goals. However, traditional diagnostic approaches often overlook the complex spatial dynamics of the atria. This review explores the emerging role of three-dimensional (3D) atrial geometry in the evaluation and management of AF. Advancements in imaging technologies and computational modeling have enabled detailed reconstructions of atrial anatomy, providing insights into the pathophysiology of AF that were previously unattainable. We examine current methodologies for interpreting 3D atrial data, including qualitative, basic quantitative, global quantitative, and statistical shape modeling approaches. We discuss their integration into clinical practice, highlighting potential benefits such as personalized treatment strategies, improved outcome prediction, and informed treatment approaches. Additionally, we discuss the challenges and limitations associated with current approaches, including technical constraints and variable interpretations, and propose future directions for research and clinical applications. This comprehensive review underscores the transformative potential of leveraging 3D atrial geometry in the evaluation and management of AF, advocating for its broader adoption in clinical practice.

Quantitative analysis of fractionated electrogram area of left atrium during right atrial pacing as an indicator of left atrial electrical remodeling in patients with atrial fibrillation

Background

The clinical significance of left atrial local electrogram fractionation after restoration of sinus rhythm in patients with atrial fibrillation (AF) has not been elucidated.

Methods

We evaluated ultrahigh-resolution maps of the left atrium (LA) during RA pacing acquired after pulmonary vein isolation in 40 patients with AF. The association between low-voltage area (LVA, <0.5 mV), fractionated electrogram area (FEA, the highlighted area with LUMIPOINT™ Complex Activation), the interval from onset of LA activation to wavefront collision at the mitral isthmus (LA activation time), and wave propagation velocity (WPV) was evaluated quantitatively.

Results

The total LVA, total FEA with ≥5.0 peaks or ≥7.0 peaks were 7.0 ± 7.9 cm2, 15.9 ± 12.9 cm2, and 5.2 ± 7.5 cm2, respectively. These areas were predominantly observed in the anteroseptal region. Total LVA, total FEA with ≥5.0 peaks, and total FEA with ≥5.0 peaks in the normal voltage area (NVA: ≥0.5 mV) correlated with LA activation time (R = 0.69, 0.75, and 0.71; each p < .0001). In the anterior wall, these areas correlated with regional mean WPV (R = -0.75, -0.83, and - 0.55; each p < .0001) and the extent of slow conduction area (SCA) with WPV <0.3 m/s (R = 0.89, 0.84, 0.33; p < .0001 for LVA and FEA, p < .05 for FEA located in NVA). The anterior wall FEA with ≥7.0 peaks and that in the NVA showed a better correlation in predicting anterior wall SCA (R = 0.92 and 0.86, each p < .0001).

Conclusion

Quantitative analysis of FEA together with LVA may facilitate the assessment of LA electrical remodeling.

Conduction velocity mapping in atrial fibrillation using omnipolar technology

BACKGROUND

Recent studies have shown that atrial slow conduction velocity (CV) is associated with the perpetuation of atrial fibrillation (AF). However, the criteria of CV measurement have not been standardized. The aim of this study was to evaluate the relationship between the slow CV area (SCVA) measured by novel omnipolar technology (OT) and AF recurrence.

METHODS

This study included 90 patients with AF who underwent initial pulmonary vein isolation (PVI). The segmented surface area of the SCVA was measured by left atrial (LA) electrophysiological mapping using OT before the PVI. The proportion of the SCVA at each cutoff value of CV (from < 0.6 to < 0.9 m/s) was compared between the patients with and without AF recurrence.

RESULTS

During a mean follow-up period of 516 ± 197 days, the recurrence of AF after the initial PVI was observed in 23 (25.5%) patients. In patients with AF recurrence, the proportion of the SCVA in the LA posterior, LA appendage (LAA), and LA anterior were significantly higher than those without AF recurrence. The multivariate analysis indicated that the proportion of the low voltage area and the SCVA in the LA anterior (local CV < 0.7 m/s) were independent predictors of AF recurrence (hazard ratio [HR], 1.07; 95% confidence interval [CI], 1.01-1.14; p = 0.03; HR, 1.40; 95% CI, 1.07-1.83; p = 0.01, respectively).

CONCLUSION

By evaluating the local CV using OT, it was indicated that SCVA with CV < 0.7 m/s in the LA anterior is strongly associated with AF recurrence after PVI.

Twenty-five years of research in cardiac imaging in electrophysiology procedures for atrial and ventricular arrhythmias

Catheter ablation is nowadays considered the treatment of choice for numerous cardiac arrhythmias in different clinical scenarios. Fluoroscopy has traditionally been the primary imaging modality for catheter ablation, providing real-time visualization of catheter navigation. However, its limitations, such as inadequate soft tissue visualization and exposure to ionizing radiation, have prompted the integration of alternative imaging modalities. Over the years, advancements in imaging techniques have played a pivotal role in enhancing the safety, efficacy, and efficiency of catheter ablation procedures. This manuscript aims to explore the utility of imaging, including electroanatomical mapping, cardiac computed tomography, echocardiography, cardiac magnetic resonance, and nuclear cardiology exams, in helping electrophysiology procedures. These techniques enable accurate anatomical guidance, identification of critical structures and substrates, and real-time monitoring of complications, ultimately enhancing procedural safety and success rates. Incorporating advanced imaging technologies into routine clinical practice has the potential to further improve clinical outcomes of catheter ablation procedures and pave the way for more personalized and precise ablation therapies in the future.

Differences in atrial substrate localization using late gadolinium enhancement-magnetic resonance imaging, electrogram voltage, and conduction velocity: a cohort study using a consistent anatomical reference frame in patients with persistent atrial fibrillation

AIMS

Electro-anatomical voltage, conduction velocity (CV) mapping, and late gadolinium enhancement (LGE) magnetic resonance imaging (MRI) have been correlated with atrial cardiomyopathy (ACM). However, the comparability between these modalities remains unclear. This study aims to (i) compare pathological substrate extent and location between current modalities, (ii) establish spatial histograms in a cohort, (iii) develop a new estimated optimized image intensity threshold (EOIIT) for LGE-MRI identifying patients with ACM, (iv) predict rhythm outcome after pulmonary vein isolation (PVI) for persistent atrial fibrillation (AF).

METHODS AND RESULTS

Thirty-six ablation-naive persistent AF patients underwent LGE-MRI and high-definition electro-anatomical mapping in sinus rhythm. Late gadolinium enhancement areas were classified using the UTAH, image intensity ratio (IIR >1.20), and new EOIIT method for comparison to low-voltage substrate (LVS) and slow conduction areas <0.2 m/s. Receiver operating characteristic analysis was used to determine LGE thresholds optimally matching LVS. Atrial cardiomyopathy was defined as LVS extent ≥5% of the left atrium (LA) surface at <0.5 mV. The degree and distribution of detected pathological substrate (percentage of individual LA surface are) varied significantly (P < 0.001) across the mapping modalities: 10% (interquartile range 0-14%) of the LA displayed LVS <0.5 mV vs. 7% (0-12%) slow conduction areas <0.2 m/s vs. 15% (8-23%) LGE with the UTAH method vs. 13% (2-23%) using IIR >1.20, with most discrepancies on the posterior LA. Optimized image intensity thresholds and each patient's mean blood pool intensity correlated linearly (R2 = 0.89, P < 0.001). Concordance between LGE-MRI-based and LVS-based ACM diagnosis improved with the novel EOIIT applied at the anterior LA [83% sensitivity, 79% specificity, area under the curve (AUC): 0.89] in comparison to the UTAH method (67% sensitivity, 75% specificity, AUC: 0.81) and IIR >1.20 (75% sensitivity, 62% specificity, AUC: 0.67).

CONCLUSION

Discordances in detected pathological substrate exist between LVS, CV, and LGE-MRI in the LA, irrespective of the LGE detection method. The new EOIIT method improves concordance of LGE-MRI-based ACM diagnosis with LVS in ablation-naive AF patients but discrepancy remains particularly on the posterior wall. All methods may enable the prediction of rhythm outcomes after PVI in patients with persistent AF.