Current hot potatoes in atrial fibrillation ablation

Machine Learning to Identify Patients at Risk of Developing New-Onset Atrial Fibrillation after Coronary Artery Bypass

BACKGROUND

This study aims to get an effective machine learning (ML) prediction model of new-onset postoperative atrial fibrillation (POAF) following coronary artery bypass grafting (CABG) and to highlight the most relevant clinical factors.

METHODS

Four ML algorithms were employed to analyze 394 patients undergoing CABG, and their performances were compared: Multivariate Adaptive Regression Spline, Neural Network, Random Forest, and Support Vector Machine. Each algorithm was applied to the training data set to choose the most important features and to build a predictive model. The better performance for each model was obtained by a hyperparameters search, and the Receiver Operating Characteristic Area Under the Curve metric was selected to choose the best model. The best instances of each model were fed with the test data set, and some metrics were generated to assess the performance of the models on the unseen data set. A traditional logistic regression was also performed to be compared with the machine learning models.

RESULTS

Random Forest model showed the best performance, and the top five predictive features included age, preoperative creatinine values, time of aortic cross-clamping, body surface area, and Logistic Euro-Score.

CONCLUSIONS

The use of ML for clinical predictions requires an accurate evaluation of the models and their hyperparameters. Random Forest outperformed all other models in the clinical prediction of POAF following CABG.

Practical Considerations for the Application of Nonlinear Indices Characterizing the Atrial Substrate in Atrial Fibrillation

Atrial fibrillation (AF) is the most common cardiac arrhythmia, and in response to increasing clinical demand, a variety of signals and indices have been utilized for its analysis, which include complex fractionated atrial electrograms (CFAEs). New methodologies have been developed to characterize the atrial substrate, along with straightforward classification models to discriminate between paroxysmal and persistent AF (ParAF vs. PerAF). Yet, most previous works have missed the mark for the assessment of CFAE signal quality, as well as for studying their stability over time and between different recording locations. As a consequence, an atrial substrate assessment may be unreliable or inaccurate. The objectives of this work are, on the one hand, to make use of a reduced set of nonlinear indices that have been applied to CFAEs recorded from ParAF and PerAF patients to assess intra-recording and intra-patient stability and, on the other hand, to generate a simple classification model to discriminate between them. The dominant frequency (DF), AF cycle length, sample entropy (SE), and determinism (DET) of the Recurrence Quantification Analysis are the analyzed indices, along with the coefficient of variation (CV) which is utilized to indicate the corresponding alterations. The analysis of the intra-recording stability revealed that discarding noisy or artifacted CFAE segments provoked a significant variation in the CV(%) in any segment length for the DET and SE, with deeper decreases for longer segments. The intra-patient stability provided large variations in the CV(%) for the DET and even larger for the SE at any segment length. To discern ParAF versus PerAF, correlation matrix filters and Random Forests were employed, respectively, to remove redundant information and to rank the variables by relevance, while coarse tree models were built, optimally combining high-ranked indices, and tested with leave-one-out cross-validation. The best classification performance combined the SE and DF, with an accuracy (Acc) of 88.3%, to discriminate ParAF versus PerAF, while the highest single Acc was provided by the DET, reaching 82.2%. This work has demonstrated that due to the high variability of CFAEs data averaging from one recording place or among different recording places, as is traditionally made, it may lead to an unfair oversimplification of the CFAE-based atrial substrate characterization. Furthermore, a careful selection of reduced sets of features input to simple classification models is helpful to accurately discern the CFAEs of ParAF versus PerAF.

Identifying locations of re-entrant drivers from patient-specific distribution of fibrosis in the left atrium

Clinical evidence suggests a link between fibrosis in the left atrium (LA) and atrial fibrillation (AF), the most common sustained arrhythmia. Image-derived fibrosis is increasingly used for patient stratification and therapy guidance. However, locations of re-entrant drivers (RDs) sustaining AF are unknown and therapy success rates remain suboptimal. This study used image-derived LA models to explore the dynamics of RD stabilization in fibrotic regions and generate maps of RD locations. LA models with patient-specific geometry and fibrosis distribution were derived from late gadolinium enhanced magnetic resonance imaging of 6 AF patients. In each model, RDs were initiated at multiple locations, and their trajectories were tracked and overlaid on the LA fibrosis distributions to identify the most likely regions where the RDs stabilized. The simulations showed that the RD dynamics were strongly influenced by the amount and spatial distribution of fibrosis. In patients with fibrosis burden greater than 25%, RDs anchored to specific locations near large fibrotic patches. In patients with fibrosis burden below 25%, RDs either moved near small fibrotic patches or anchored to anatomical features. The patient-specific maps of RD locations showed that areas that harboured the RDs were much smaller than the entire fibrotic areas, indicating potential targets for ablation therapy. Ablating the predicted locations and connecting them to the existing pulmonary vein ablation lesions was the most effective in-silico ablation strategy.

Selective inhibition of electrical conduction within the pulmonary veins by α1-adrenergic receptors activation in the Rat

Pulmonary veins (PV) are involved in the pathophysiology of paroxysmal atrial fibrillation. In the rat, left atrium (LA) and PV cardiomyocytes have different reactions to α1-adrenergic receptor activation. In freely beating atria-PV preparations, we found that electrical field potential (EFP) originated from the sino-atrial node propagated through the LA and the PV. The α1-adrenergic receptor agonist cirazoline induced a progressive loss of EFP conduction in the PV whereas it was maintained in the LA. This could be reproduced in preparations electrically paced at 5 Hz in LA. During pacing at 10 Hz in the PV where high firing rate ectopic foci can occur, cirazoline stopped EFP conduction from the PV to the LA, which allowed the sino-atrial node to resume its pace-making function. Loss of conduction in the PV was associated with depolarization of the diastolic membrane potential of PV cardiomyocytes. Adenosine, which reversed the cirazoline-induced depolarization of the diastolic membrane potential of PV cardiomyocytes, restored full over-shooting action potentials and EFP conduction in the PV. In conclusion, selective activation of α1-adrenergic receptors results in the abolition of electrical conduction within the PV. These results highlight a potentially novel pharmacological approach to treat paroxysmal atrial fibrillation by targeting directly the PV myocardium.

Optimization of wavelength selection for multispectral image acquisition: a case study of atrial ablation lesions

In vivo autofluorescence hyperspectral imaging of moving objects can be challenging due to motion artifacts and to the limited amount of acquired photons. To address both limitations, we selectively reduced the number of spectral bands while maintaining accurate target identification. Several downsampling approaches were applied to data obtained from the atrial tissue of adult pigs with sites of radiofrequency ablation lesions. Standard image qualifiers such as the mean square error, the peak signal-to-noise ratio, the structural similarity index map, and an accuracy index of lesion component images were used to quantify the effects of spectral binning, an increased spectral distance between individual bands, as well as random combinations of spectral bands. Results point to several quantitative strategies for deriving combinations of a small number of spectral bands that can successfully detect target tissue. Insights from our studies can be applied to a wide range of applications.

Anatomical and Optical Properties of Atrial Tissue: Search for a Suitable Animal Model

The purpose of this study was to evaluate structural and optical properties of atrial tissue from common animal models and to compare it with human atria. We aimed to do this in a format that will be useful for development of better ablation tools and/or new means for visualizing atrial lesions. Human atrial tissue from clinically relevant age group was compared and contrasted with atrial tissue of large animal models commonly available for research purposes. These included pigs, sheep, dogs and cows. The presented data include area measurements of smooth atrial surface available for ablation and estimates of thickness of collagen and muscle for five different species. We also described methods to quantify presence of collagen and overall thickness of atrial wall. Provided information enables placement of atrial lesions to locations with clinically relevant atrial wall thickness and macroscopic structure ultimately helping investigators to develop better ablation and imaging tools. It also highlights the impact of collagen thickness on optical measurements and lesion visualization.

Effects of hypothermia on the mechanical behavior of rabbit femoral arteries

The need to better understand the effects of non-physiological temperatures on arterial wall behavior is becoming more important because of the increased clinical use of hypothermal and hyperthermal treatments. The present study was performed to examine the effects of temperature on the mechanical behavior of femoral arteries excised from rabbits. Among 17, 27, 37, and 42°C, there were no significant differences in their diameter, stiffness, and P-D relations under the physiologically normal, control condition, although the arterial diameter was slightly smaller at 42°C than at the other three temperatures. Under the SMC-activated condition, on the other hand, we observed significant effects of temperature. For example, arterial diameter at 100mmHg was significantly larger at 17 and 27°C and smaller at 42°C compared with 37°C. Arterial stiffness at 40mmHg were significantly smaller at 17 and larger at 42°C than at 37°C, while the stiffness at 160mmHg were significantly larger at 17°C than at 37°C; however, there were no significant differences in the stiffness at 100mmHg among the four temperatures. Arterial contraction induced by SMC-activation was significantly different between 37°C and the other three temperatures; both of the maximum diameter response and diameter response at 100mmHg were significantly smaller at 17 and 27°C and larger at 42°C compared with 37°C. These results indicate that in the hypothermic range under the control condition, arteries are dilated when cooled, while they are constricted when heated. On the other hand, arterial response to SMC activation is significantly affected by the alterations of temperature. These results indicate that in the hypothermic range under the control condition, arteries are dilated when cooled, while they are constricted when heated. On the other hand, arterial response to the activation of vascular smooth muscle cells is significantly affected by the alteration of temperature. As the mechanical behavior of arterial wall is significantly influenced by temperature, this should be considered in the development of therapeutic methods and techniques for cardiovascular diseases.

Pulmonary vein isolation for persistent atrial fibrillation. Long-term results

BACKGROUND

Pulmonary vein isolation has been employed to eliminate paroxysmal atrial fibrillation. However, the long-term outcome in terms of long-standing persistent atrial fibrillation is unclear.

METHODS

One hundred patients with rheumatic mitral valve disease and long-standing (>1 year) persistent atrial fibrillation were operated on between July 1998 and June 2007. Mitral valve surgery and surgical isolation (cut-and-sew) of the pulmonary veins were performed in all cases. Transthoracic echocardiography and 24-h Holter monitoring were obtained after 3 and 6 months and yearly thereafter.

RESULTS

Early and late follow-up was 99% and 92% complete, respectively. The endpoint was freedom from atrial fibrillation. There was one (1%) hospital death. Atrial fibrillation was present in 39%, 47%, 63% and 68% of patients at 3 months, 1 year, 3 years, and 5 years after surgery, respectively. The odds ratios for recurrence of atrial fibrillation postoperatively were 1.41 (95% confidence interval 1.14-1.74), 2.17 (95% confidence interval 1.63-2.90), and 3.62 (95% confidence interval 2.44-5.38) at 1 week, 3 years, and 5 years, respectively. Actuarial freedom from atrial fibrillation was 35% at 3 years, and 30% at 5 years. A direct relationship was observed between preoperative left atrial size >6 cm and atrial fibrillation recurrence at 5 years (p < 0.05 odds ratio = 2.5, 95% confidence interval 1.15 - 5.4).

CONCLUSIONS

No beneficial effects of simple pulmonary vein isolation for long-standing persistent atrial fibrillation concomitant with rheumatic mitral valve disease were observed. Atrial fibrillation cannot be fully treated using only pulmonary vein isolation.

The logical operator map identifies novel candidate markers for critical sites in patients with atrial fibrillation

The identification of suitable markers for critical patterns during atrial fibrillation (AF) may be crucial to guide an effective ablation treatment. Single parameter maps, based on dominant frequency and complex fractionated electrograms, have been proposed as a tool for electrogram-guided ablation, however the specificity of these markers is debated. Experimental studies suggest that AF critical patterns may be identified on the basis of specific rate and organization features, where rapid organized and rapid fragmented activities characterize respectively localized sources and critical substrates. In this paper we introduce the logical operator map, a novel mapping tool for a point-by-point identification and localization of AF critical sites. Based on advanced signal and image processing techniques, the approach combines in a single map electrogram-derived rate and organization features with tomographic anatomical detail. The construction of the anatomically-detailed logical operator map is based on the time-domain estimation of atrial rate and organization in terms of cycle length and wave-similarity, the logical combination of these indexes to obtain suitable markers of critical sites, and the multimodal integration of electrophysiological and anatomical information by segmentation and registration techniques. Logical operator maps were constructed in 14 patients with persistent AF, showing the capability of the combined rate and organization markers to identify with high selectivity the subset of electrograms associated with localized sources and critical substrates. The precise anatomical localization of these critical sites revealed the confinement of rapid organized sources in the left atrium with organization and rate gradients towards the surrounding tissue, and the presence of rapid fragmented electrograms in proximity of the sources. By merging in a single map the most relevant electrophysiological and anatomical features of the AF process, the logical operator map may have significant clinical impact as a direct, comprehensive tool to understand arrhythmia mechanisms in the single patient and guide more conservative, step-wise ablation.

Anatomical characteristics of pulmonary veins for the prediction of postoperative recurrence after radiofrequency catheter ablation of atrial fibrillation

Background

The relationship between focal pulmonary vein potential and atrial fibrillation (AF) has been confirmed. Pulmonary vein (PV) isolation and circumferential pulmonary vein ablation have been the most commonly used procedures of radiofrequency ablation. However, few studies have investigated the relationship between anatomical characteristics of PV and AF recurrences after radiofrequency ablation.

Methodology

For 267 AF patients treated by radiofrequency catheter ablation, the anatomic structure characteristics of pulmonary veins were assessed by multi-slice spiral computed tomography while the values of left atrial diameter (LAD) were measured with transesophageal ultrasonic cardiogram. After radiofrequency catheter ablation, postoperative recurrence was evaluated during a 10-month term follow-up.

Principal Findings

During follow-up, postoperative recurrence occurred in 44 patients. The mean diameters of LAD, left superior PV, right superior PV, all left PV, and all superior PV were significantly larger in patients with postoperative recurrence (Recurrence vs. Non-recurrence group; 43.9 ± 6.4 mm vs. 40.7 ± 5.6 mm; 18.4 ± 2.1 mm vs. 17.1 ± 3.1 mm; 18.2 ± 2.8 mm vs. 17.2 mm ± 3.9 mm; 16.4 ± 1.5 mm vs. 15.6 ± 2.5 mm; 18.3 ± 2.1 mm vs. 17.1 ± 3.0 mm; respectively; all P < 0.05). Multivariable survival analysis showed that the type and the course of AF, LAD, and the diameters of all superior PV were the independent risk factors for the postoperative recurrence after radiofrequency catheter ablation.

Conclusions

The enlargements of all superior PV and LAD, long course of diseases, and persistent AF were the independent risk factors for the postoperative recurrence after radiofrequency catheter ablation.

Dominant frequency increase rate predicts transition from paroxysmal to long-term persistent atrial fibrillation

BACKGROUND

Little is known about the mechanisms underlying the transition from paroxysmal to persistent atrial fibrillation (AF). In an ovine model of long-standing persistent AF we tested the hypothesis that the rate of electric and structural remodeling, assessed by dominant frequency (DF) changes, determines the time at which AF becomes persistent.

METHODS AND RESULTS

Self-sustained AF was induced by atrial tachypacing. Seven sheep were euthanized 11.5±2.3 days after the transition to persistent AF and without reversal to sinus rhythm; 7 sheep were euthanized after 341.3±16.7 days of long-standing persistent AF. Seven sham-operated animals were in sinus rhythm for 1 year. DF was monitored continuously in each group. Real-time polymerase chain reaction, Western blotting, patch clamping, and histological analyses were used to determine the changes in functional ion channel expression and structural remodeling. Atrial dilatation, mitral valve regurgitation, myocyte hypertrophy, and atrial fibrosis occurred progressively and became statistically significant after the transition to persistent AF, with no evidence for left ventricular dysfunction. DF increased progressively during the paroxysmal-to-persistent AF transition and stabilized when AF became persistent. Importantly, the rate of DF increase correlated strongly with the time to persistent AF. Significant action potential duration abbreviation, secondary to functional ion channel protein expression changes (CaV1.2, NaV1.5, and KV4.2 decrease; Kir2.3 increase), was already present at the transition and persisted for 1 year of follow up.

CONCLUSIONS

In the sheep model of long-standing persistent AF, the rate of DF increase predicts the time at which AF stabilizes and becomes persistent, reflecting changes in action potential duration and densities of sodium, L-type calcium, and inward rectifier currents.