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Introduction: Strategies beyond pulmonary vein isolation (PVI) in persistent atrial fibrillation (persAF) are debated. A novel mapping tool provides algorithmic detection of ablation targets based on electrogram (EGM) properties specific to stable localized rotational activations., Methods: The mapping tool was used on 31 patients (20 de novo). The algorithm was used to optimize PVI line placement and guide additional ablations. Targets were detected by calculating local cycle length (L-CL) and local spread of activation within that L-CL (Duty Cycle; DC) for EGMs with consistent morphology and activation. At least two left atrial (LA) maps (pre-PVI and post-PVI) were acquired in atrial fibrillation (AF) in all patients (except those with AF termination during PVI). Extra-pulmonary vein (PV) targets were compared between the two LA maps in each patient. Follow-up included Holter monitoring every 3 months., Results: Patients had a median of 3 extra-PV drivers/targets. The majority (81%) were localized in the same areas between the two LA maps. All patients had progressive AF organization demonstrated by global activation slowing: histogram peak L-CL increased from 162 to 171 ms (post-PVI; p = .0003) than to 175 ms (posttarget ablation; p = .04). Moreover, L-CL dispersion was reduced by ablation; in 50% their values tended to cluster around two dominant cycles. In de novo patients AF terminated to sinus rhythm or atrial tachycardia (AT) within 48 h postprocedure in 88% of cases, and at 18 months mean follow-up recurrence occurred in only five (25%) patients (three persAF, two AT). There were no complications., Conclusion: The algorithmic detection of EGMs consistent with localized reentry during sequential mapping of persAF provided reproducible targets for ablation. This allowed personalized PVI and limited, highly-selective, extra-PV ablation. Results of this initial experience included progressive organization of AF with ablation and a low recurrence rate after a single procedure., (© 2024 Wiley Periodicals LLC.)

Background: Bipolar voltage is widely used to characterize the atrial substrate but has been poorly validated, particularly during clinical tachycardias., Objective: The purpose of this study was to evaluate the diagnostic performance of voltage thresholds for identifying regions of slow conduction during reentrant atrial tachycardias (ATs)., Methods: Thirty bipolar voltage and activation maps created during reentrant ATs were analyzed to (1) examine the relationship between voltage amplitude and conduction velocity (CV), (2) measure the diagnostic ability of voltage thresholds to predict CV, and (3) identify determinants of AT circuit dimensions. Voltage amplitude was categorized as "normal" (>0.50 mV), "abnormal" (0.05-0.50 mV), or "scar" (<0.05 mV); slow conduction was defined as <30 cm/s., Results: A total of 266,457 corresponding voltage and CV data points were included for analysis. Voltage and CV were moderately correlated (r = 0.407; P < .001). Bipolar voltage predicted regions of slow conduction with an area under the receiver operating characteristic curve of 0.733 (95% confidence interval 0.731-0.735). A threshold of 0.50 mV had 91% sensitivity and 35% specificity for identifying slow conduction, whereas 0.05 mV had 36% sensitivity and 87% specificity, with an optimal voltage threshold of 0.15 mV. Analyses restricted to the AT circuits identified weaker associations between voltage and CV and an optimal voltage threshold of 0.25 mV., Conclusion: Widely used bipolar voltage amplitude thresholds to define "abnormal" and "scar" tissue in the atria are, respectively, sensitive and specific for identifying regions of slow conduction during reentrant ATs. However, overall, the association of voltage with CV is modest. No clinical predictors of AT circuit dimensions were identified., (Copyright © 2022 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)

Background: An understanding of normal atrial activation during sinus rhythm can inform catheter ablation strategies to avoid deleterious impacts of ablation lesions on atrial conduction and mechanics., Objective: The purpose of this study was to describe how the sinus node impulse originates, propagates, and collides in right and left atria with normal voltage., Methods: Fifty consecutive patients undergoing catheter ablation of atrial fibrillation with endocardial atrial voltage >0.5 mV during high-density 3-dimensional mapping were studied., Results: Sinus node exits varied among patients along a lateral oblique arc extending from the anterior aspect of the superior vena cava (SVC) to the mid-posterior wall of the right atrium (RA). Conduction slowing or block at one of the smooth components that faces the crista terminalis was observed in 54% of cases, including complete block at the SVC musculature and systemic venous sinus in 6% of cases. Depending on these 2 key features of RA activation, interatrial conduction was mediated by the Bachmann bundle (64%) and posterior bundles (54%), with an overlap of the resulting left atrial breakthrough location. Wavefront collision was consistently observed at 3 sites: the septal aspect of the cavotricuspid isthmus, and the lower aspects of the dome and of the mitral isthmus., Conclusion: During sinus rhythm, atrial activation occurs via distinct sequences mediated by a complex interaction of anatomic factors., (Copyright © 2022 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)

Success rates for catheter ablation of persistent atrial fibrillation patients are currently low; however, there is a subset of patients for whom electrical isolation of the pulmonary veins alone is a successful treatment strategy. It is difficult to identify these patients because there are a multitude of factors affecting arrhythmia susceptibility and maintenance, and the individual contributions of these factors are difficult to determine clinically. We hypothesised that the combination of pulmonary vein (PV) electrophysiology and atrial body fibrosis determine driver location and effectiveness of pulmonary vein isolation (PVI). We used bilayer biatrial computer models based on patient geometries to investigate the effects of PV properties and atrial fibrosis on arrhythmia inducibility, maintenance mechanisms, and the outcome of PVI. Short PV action potential duration (APD) increased arrhythmia susceptibility, while longer PV APD was found to be protective. Arrhythmia inducibility increased with slower conduction velocity (CV) at the LA/PV junction, but not for cases with homogeneous CV changes or slower CV at the distal PV. Phase singularity (PS) density in the PV region for cases with PV fibrosis was increased. Arrhythmia dynamics depend on both PV properties and fibrosis distribution, varying from meandering rotors to PV reentry (in cases with baseline or long APD), to stable rotors at regions of high fibrosis density. Measurement of fibrosis and PV properties may indicate patient specific susceptibility to AF initiation and maintenance. PV PS density before PVI was higher for cases in which AF terminated or converted to a macroreentry; thus, high PV PS density may indicate likelihood of PVI success., Competing Interests: The authors have declared that no competing interests exist.

With the increasing prevalence of atrial fibrillation (AF), there is a strong clinical interest in determining whether a patient suffering from persistent AF will benefit from catheter ablation (CA) therapy at long term. This work presents several regression models based on noninvasive measures automatically computed from the standard 12-lead electrocardiogram (ECG) such as AF dominant frequency (DF), spectral concentration and spatiotemporal variability (STV). Sixty-two AF patients referred to CA were enrolled in this study. Forty-seven of them had no recurrence after CA during an average follow-up of 14 ± 8 months. The ECG features were extracted from an ECG recorded before the CA intervention and they were combined by means of logistic regression. The combination of DF and STV values from different precordial leads reached AUC = 0.939, outperforming the best results by using only one kind of features, such as DF (AUC = 0.801), and yielding a global accuracy of 93.5% for discriminating the best long-term responders to CA. These results point out the need to take into consideration the spatial variation of spectral ECG parameters to build predictive models dealing with AF., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Background: Catheter ablation (CA) of persistent atrial fibrillation (AF) is challenging, and reported results are capable of improvement. A better patient selection for the procedure could enhance its success rate while avoiding the risks associated with ablation, especially for patients with low odds of favorable outcome. CA outcome can be predicted non-invasively by atrial fibrillatory wave (f-wave) amplitude, but previous works focused mostly on manual measures in single electrocardiogram (ECG) leads only., Aim: To assess the long-term prediction ability of f-wave amplitude when computed in multiple ECG leads., Methods: Sixty-two patients with persistent AF (52 men; mean age 61.5±10.4years) referred for CA were enrolled. A standard 1-minute 12-lead ECG was acquired before the ablation procedure for each patient. F-wave amplitudes in different ECG leads were computed by a non-invasive signal processing algorithm, and combined into a mutivariate prediction model based on logistic regression., Results: During an average follow-up of 13.9±8.3months, 47 patients had no AF recurrence after ablation. A lead selection approach relying on the Wald index pointed to I, V1, V2 and V5 as the most relevant ECG leads to predict jointly CA outcome using f-wave amplitudes, reaching an area under the curve of 0.854, and improving on single-lead amplitude-based predictors., Conclusion: Analysing the f-wave amplitude in several ECG leads simultaneously can significantly improve CA long-term outcome prediction in persistent AF compared with predictors based on single-lead measures., (Copyright © 2016 Elsevier Masson SAS. All rights reserved.)

Aims: Catheter ablation is an effective technique for terminating atrial arrhythmia. However, given a high atrial fibrillation (AF) recurrence rate, optimal ablation strategies have yet to be defined. Computer modelling can be a powerful aid but modelling of fibrosis, a major factor associated with AF, is an open question. Several groups have proposed methodologies based on imaging data, but no comparison to determine which methodology best corroborates clinically observed reentrant behaviour has been performed. We examined several methodologies to determine the best method for capturing fibrillation dynamics., Methods and Results: Patient late gadolinium-enhanced magnetic resonance imaging data were transferred onto a bilayer atrial computer model and used to assign fibrosis distributions. Fibrosis was modelled as conduction disturbances (lower conductivity, edge splitting, or percolation), transforming growth factor-β1 ionic channel effects, myocyte-fibroblast coupling, and combinations of the preceding. Reentry was induced through pulmonary vein ectopy and the ensuing rotor dynamics characterized. Non-invasive electrocardiographic imaging data of the patients in AF was used for comparison. Electrograms were computed and the fractionation durations measured over the surface. Edge splitting produced more phase singularities from wavebreaks than the other representations. The number of phase singularities seen with percolation was closer to the clinical values. Addition of fibroblast coupling had an organizing effect on rotor dynamics. Simple tissue conductivity changes with ionic changes localized rotors over fibrosis which was not observed with clinical data., Conclusion: The specific representation of fibrosis has a large effect on rotor dynamics and needs to be carefully considered for patient specific modelling., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2016. For Permissions, please email: journals.permissions@oup.com.)

Catheter ablation (CA) is increasingly employed to treat persistent atrial fibrillation (AF), yet assessment of procedural AF termination is still a subject of debate in the medical community. This has motivated the development of different criteria based on the standard electrocardiogram (ECG) to characterize ablation immediate effectiveness. However, most of conventional descriptors are merely computed in one ECG lead, thus neglecting significant information provided by the other leads. The present study proposes a novel predictor of CA outcome by exploiting a subset of the 12 leads in the standard ECG. Our method predicts the need for electrical cardioversion subsequent to CA by suitably combining two sets of multilead features, namely, a measure of fibrillatory wave amplitude and an index of AF spatio-temporal variability per lead. These features are obtained on a reduced-rank approximation determined by principal component analysis emphasizing the highest-variance components in the multilead atrial activity signal, and are then combined by logistic regression. On a database of over 50 persistent AF patients, our method provides reliable predictive measures and proves more robust and informative than classical AF descriptors.

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia encountered in clinical practice. Radiofrequency catheter ablation (CA) is increasingly employed to treat this disease, yet the selection of persistent AF patients who will benefit from this treatment remains a challenging task. Several parameters of the surface electrocardiogram (ECG) have been analyzed in previous works to predict AF termination by CA, such as fibrillatory wave (f-wave) amplitude. However, they are usually manually computed and only a subset of electrodes is inspected. In this study, a novel perspective of the role of f-wave amplitude as a potential noninvasive predictor of CA outcome is adopted by exploring ECG interlead spatial variability. An automatic procedure for atrial amplitude computation based on cubic Hermite interpolation is first proposed. To describe the global f-wave peak-to-peak amplitude distribution, signal contributions from multiple leads are then combined by condensing the most representative features of the atrial signal in a reduced-rank approximation based on principal component analysis (PCA). We show that exploiting ECG spatial diversity by means of this PCA-based multilead approach does not only increase the robustness to electrode selection, but also substantially improves the predictive power of the amplitude parameter.

Radiofrequency catheter ablation (CA) is increasingly employed to treat persistent atrial fibrillation (AF). Nevertheless, its success is not always guaranteed, as selection of patients who could positively respond to this therapy does not rely on systematic criteria and still remains an open issue. Moreover, very little is known about the quantitative effects of this treatment over AF electrophysiology, so their quantitative evaluation is not a trivial task. In this contribution, ablation impact is quantified by a descriptor of fibrillatory wave (f-wave) amplitude, so far regarded as a predictor of short-term CA outcome. By means of principal component analysis (PCA), surface electrocardiogram (ECG) spatial diversity is exploited and contributions from all leads are combined to describe average f-wave peak-to-peak amplitude, whose value is automatically computed by an algorithm based on cubic spline interpolation. Our work demonstrates how CA influences f-wave amplitude during the procedure as quantified by ECG inter-lead spatial variability. In addition, we show how such variations depend on procedural outcome and the duration of the postoperative blanking period.

Atrial fibrillation (AF) is the most common cardiac arrhythmia encountered in clinical practice. Radiofrequency catheter ablation (CA) is becoming one of the most widely employed therapies. Yet selection of patients who will benefit from this treatment remains a challenging task. Previous works have examined several electrocardiogram (ECG) parameters as potential predictors of CA success, such as fibrillatory wave (f-wave) amplitude. However, they require a manual computation and consider only a subset of electrodes, so inter-lead spatial variability of the 12-lead ECG is not fully exploited. The present study puts forward an automatic procedure for f-wave amplitude computation to non-invasively predict CA outcome. An extension of this quantitative measure to the whole set of leads is also proposed, based on Principal Component Analysis (PCA). We show that exploiting the spatial diversity present in the surface ECG not only improves the robustness to electrode selection but also increases the predictive power of the amplitude parameter.

The mechanisms underlying atrial fibrillation (AF), the most common sustained cardiac rhythm disturbance, remain elusive. Atrial fibrosis plays an important role in the development of AF and rotor dynamics. Both electrical wavelength (WL) and the degree of atrial fibrosis change as AF progresses. However, their combined effect on rotor core location remains unknown. The aim of this study was to analyze the effects of WL change on rotor core location in both fibrotic and non-fibrotic atria. Three patient specific fibrosis distributions (total fibrosis content: 16.6, 22.8, and 19.2%) obtained from clinical imaging data of persistent AF patients were incorporated in a bilayer atrial computational model. Fibrotic effects were modeled as myocyte-fibroblast coupling + conductivity remodeling; structural remodeling; ionic current changes + conductivity remodeling; and combinations of these methods. To change WL, action potential duration (APD) was varied from 120 to 240ms, representing the range of clinically observed AF cycle length, by modifying the inward rectifier potassium current (I K 1) conductance between 80 and 140% of the original value. Phase singularities (PSs) were computed to identify rotor core locations. Our results show that I K 1 conductance variation resulted in a decrease of APD and WL across the atria. For large WL in the absence of fibrosis, PSs anchored to regions with high APD gradient at the center of the left atrium (LA) anterior wall and near the junctions of the inferior pulmonary veins (PVs) with the LA. Decreasing the WL induced more PSs, whose distribution became less clustered. With fibrosis, PS locations depended on the fibrosis distribution and the fibrosis implementation method. The proportion of PSs in fibrotic areas and along the borders varied with both WL and fibrosis modeling method: for patient one, this was 4.2–14.9% as I K 1 varied for the structural remodeling representation, but 12.3–88.4% using the combination of structural remodeling with myocyte-fibroblast coupling. The degree and distribution of fibrosis and the choice of implementation technique had a larger effect on PS locations than the WL variation. Thus, distinguishing the fibrotic mechanisms present in a patient is important for interpreting clinical fibrosis maps to create personalized models. [ABSTRACT FROM AUTHOR]

Background: The use of surface recordings to assess atrial fibrillation (AF) complexity is still limited in clinical practice. We propose a noninvasive tool to quantify AF complexity from body surface potential maps (BSPMs) that could be used to choose patients who are eligible for AF ablation and assess therapy impact. Methods: BSPMs (mean duration: 7 ± 4 s) were recorded with a 252-lead vest in 97 persistent AF patients (80 male, 64 ± 11 years, duration 9.6 ± 10.4 months) before undergoing catheter ablation. Baseline cycle length (CL) was measured in the left atrial appendage. The procedural endpoint was AF termination. The ablation strategy impact was defined in terms of number of regions ablated, radiofrequency delivery time to achieve AF termination, and acute outcome. The atrial fibrillatory wave signal extracted from BSPMs was divided in 0.5-s consecutive segments, each projected on a 3D subspace determined through principal component analysis (PCA) in the current frame. We introduced the nondipolar component index (NDI) that quantifies the fraction of energy retained after subtracting an equivalent PCA dipolar approximation of heart electrical activity. AF complexity was assessed by the NDI averaged over the entire recording and compared to ablation strategy. Results: AF terminated in 77 patients (79%), whose baseline AF CL was 177 ± 40 ms, whereas it was 157 ± 26 ms in patients with unsuccessful ablation outcome (p = 0.0586). Mean radiofrequency emission duration was 35 ± 21 min; 4 ± 2 regions were targeted. Long-lasting AF patients (≥12 months) exhibited higher complexity, with higher NDI values (≥12 months: 0.12 ± 0.04 vs. <12 months: 0.09 ± 0.03, p < 0.01) and short CLs (<160 ms: 0.12 ± 0.03 vs. between 160 and 180 ms: 0.10 ± 0.03 vs. >180 ms: 0.09 ± 0.03, p < 0.01). More organized AF as measured by lower NDI was associated with successful ablation outcome (termination: 0.10 ± 0.03 vs. no termination: 0.12 ± 0.04, p < 0.01), shorter procedures (<30 min: 0.09 ± 0.04 vs. ≥30 min: 0.11 ± 0.03, p < 0.001) and fewer ablation targets (<4: 0.09 ± 0.03 vs. ≥4: 0.11 ± 0.04, p < 0.01). Conclusions: AF complexity can be noninvasively quantified by PCA in BSPMs and correlates with ablation outcome and AF pathophysiology. [ABSTRACT FROM AUTHOR]