Unmasking Arrhythmogenic Hubs of Reentry Driving Persistent Atrial Fibrillation for Patient-Specific Treatment

Patchy fibrosis promotes trigger-substrate interactions that both generate and maintain atrial fibrillation

Fibrosis has been mechanistically linked to arrhythmogenesis in multiple cardiovascular conditions, including atrial fibrillation (AF). Previous studies have demonstrated that fibrosis can create functional barriers to conduction which may promote excitation wavebreak and the generation of re-entry, while also acting to pin re-entrant excitation in stable rotors during AF. However, few studies have investigated the role of fibrosis in the generation of AF triggers in detail. We apply our in-house computational framework to study the impact of fibrosis on the generation of AF triggers and trigger-substrate interactions in two- and three-dimensional atrial tissue models. Our models include a reduced and efficient description of stochastic, spontaneous cellular triggers as well as a simple model of heterogeneous inter-cellular coupling. Our results demonstrate that fibrosis promotes the emergence of focal excitations, primarily through reducing the electrotonic load on individual fibre strands. This enables excitation to robustly initiate within these single strands before spreading to neighbouring strands and inducing a full tissue focal excitation. Enhanced conduction block can allow trigger-substrate interactions that result in the emergence of complex, re-entrant excitation patterns. This study provides new insight into the mechanisms by which fibrosis promotes the triggers and substrate necessary to induce and sustain arrhythmia.

A simple approach for image-based modelling of the heart that enables robust simulation of highly heterogeneous electrical excitation

Remodelling of cardiac tissue structure, including intercellular electrical coupling, is a major determinant of the complex and heterogeneous excitation patterns associated with cardiac arrhythmias. Evaluation of the precise mechanisms by which local tissue structure determines global arrhythmic excitation patterns is a major challenge that may be critically important for the development of effective treatment strategies. Computational modelling is a key tool in the study of cardiac arrhythmias, yet the established approaches for organ-scale modelling are unsuitable to capture the impact of local conduction heterogeneities; a novel approach is required to provide this multi-scale mechanistic insight. We present a fundamentally simple yet powerful approach to simulate electrical excitation in highly heterogeneous whole-heart models that exploits the underlying discreteness of the myocardium. Preliminary simulations demonstrate that this approach can capture lower conduction velocities and reproduce wave breakdown and the development of re-entry in a range of conditions.

Three-dimensional functional anatomy of the human sinoatrial node for epicardial and endocardial mapping and ablation

The sinoatrial node (SAN) is the primary pacemaker of the human heart. It is a single, elongated, 3-dimensional (3D) intramural fibrotic structure located at the junction of the superior vena cava intercaval region bordering the crista terminalis (CT). SAN activation originates in the intranodal pacemakers and is conducted to the atria through 1 or more discrete sinoatrial conduction pathways. The complexity of the 3D SAN pacemaker structure and intramural conduction are underappreciated during clinical multielectrode mapping and ablation procedures of SAN and atrial arrhythmias. In fact, defining and targeting SAN is extremely challenging because, even during sinus rhythm, surface-only multielectrode mapping may not define the leading pacemaker sites in intramural SAN but instead misinterpret them as epicardial or endocardial exit sites through sinoatrial conduction pathways. These SAN exit sites may be distributed up to 50 mm along the CT beyond the ∼20-mm-long anatomic SAN structure. Moreover, because SAN reentrant tachycardia beats may exit through the same sinoatrial conduction pathway as during sinus rhythm, many SAN arrhythmias are underdiagnosed. Misinterpretation of arrhythmia sources and/or mechanisms (eg, enhanced automaticity, intranodal vs CT reentry) limits diagnosis and success of catheter ablation treatments for poorly understood SAN arrhythmias. The aim of this review is to provide a state-of-the-art overview of the 3D structure and function of the human SAN complex, mechanisms of SAN arrhythmias and available approaches for electrophysiological mapping, 3D structural imaging, pharmacologic interventions, and ablation to improve diagnosis and mechanistic treatment of SAN and atrial arrhythmias.

Atrial fibrillation: Insights from animal models, computational modeling, and clinical studies

Atrial fibrillation (AF) is the most common human arrhythmia, affecting millions of patients worldwide. A combination of risk factors and comorbidities results in complex atrial remodeling, which increases AF vulnerability and persistence. Insights from animal models, clinical studies, and computational modeling have advanced the understanding of the mechanisms and pathophysiology of AF. Areas of heterogeneous pathological remodeling, as well as altered electrophysiological properties, serve as a substrate for AF drivers and spontaneous activations. The complex and individualized presentation of this arrhythmia suggests that mechanisms-based personalized approaches will likely be needed to overcome current challenges in AF management. In this paper, we review the insights on the mechanisms of AF obtained from animal models and clinical studies and how computational models integrate this knowledge to advance AF clinical management. We also assess the challenges that need to be overcome to implement these mechanistic models in clinical practice.

Dynamic electrophysiological mechanism in patients with long-standing persistent atrial fibrillation

Background

Improved understanding of the mechanisms that sustain persistent and long-standing persistent atrial fibrillation (LSpAF) is essential for providing better ablation solutions. The findings of traditional catheter-based electrophysiological studies can be impacted by the sedation required for these procedures. This is not required in non-invasive body-surface mapping (ECGI). ECGI allows for multiple mappings in the same patient at different times. This would expose potential electrophysiological changes over time, such as the location and stability of extra-pulmonary vein drivers and activation patterns in sustained AF.

Materials and methods

In this electrophysiological study, 10 open-heart surgery candidates with LSpAF, without previous ablation procedures (6 male, median age 73 years), were mapped on two occasions with a median interval of 11 days (IQR: 8–19) between mappings. Bi-atrial epicardial activation sequences were acquired using ECGI (CardioInsight™, Minneapolis, MN, United States).

Results

Bi-atrial electrophysiological abnormalities were documented in all 20 mappings. Interestingly, the anatomic location of focal and rotor activities changed between the mappings in all patients [100% showed changes, 95%CI (69.2–100%), p < 0.001]. Neither AF driver type nor their number varied significantly between the mappings in any patient (median total number of focal activities 8 (IQR: 1–16) versus 6 (IQR: 2–12), p = 0.68; median total number of rotor activities 48 (IQR: 44–67) versus 55 (IQR: 44–61), p = 0.30). However, individual zones showed a high number of quantitative changes (increase/decrease) of driver activity. Most changes of focal activity were found in the left atrial appendage, the region of the left lower pulmonary vein and the right atrial appendage. Most changes in rotor activity were found also at the left lower pulmonary vein region, the upper half of the right atrium and the right atrial appendage.

Conclusion

This clinical study documented that driver location and activation patterns in patients with LSpAF changes constantly. Furthermore, bi-atrial pathophysiology was demonstrated, which underscores the importance of treating both atria in LSpAF and the significant role that arrhythmogenic drivers outside the pulmonary veins seem to have in maintaining this complex arrhythmia.

Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps

Micro-anatomical reentry has been identified as a potential driver of atrial fibrillation (AF). In this paper, we introduce a novel computational method which aims to identify which atrial regions are most susceptible to micro-reentry. The approach, which considers the structural basis for micro-reentry only, is based on the premise that the accumulation of electrically insulating interstitial fibrosis can be modelled by simulating percolation-like phenomena on spatial networks. Our results suggest that at high coupling, where micro-reentry is rare, the micro-reentrant substrate is highly clustered in areas where the atrial walls are thin and have convex wall morphology, likely facilitating localised treatment via ablation. However, as transverse connections between fibres are removed, mimicking the accumulation of interstitial fibrosis, the substrate becomes less spatially clustered, and the bias to forming in thin, convex regions of the atria is reduced, possibly restricting the efficacy of localised ablation. Comparing our algorithm on image-based models with and without atrial fibre structure, we find that strong longitudinal fibre coupling can suppress the micro-reentrant substrate, whereas regions with disordered fibre orientations have an enhanced risk of micro-reentry. With further development, these methods may be useful for modelling the temporal development of the fibrotic substrate on an individualised basis.

Genetic and non-genetic risk factors associated with atrial fibrillation

Atrial fibrillation (AF) is the most common arrhythmic disorder and its prevalence in the United States is projected to increase to more than twelve million cases in 2030. AF increases the risk of other forms of cardiovascular disease, including stroke. As the incidence of atrial fibrillation increases dramatically with age, it is paramount to elucidate risk factors underlying AF pathogenesis. Here, we review tissue and cellular pathways underlying AF, as well as critical components that impact AF susceptibility including genetic and environmental risk factors. Finally, we provide the latest information on potential links between SARS-CoV-2 and human AF. Improved understanding of mechanistic pathways holds promise in preventative care and early diagnostics, and also introduces novel targeted forms of therapy that might attenuate AF progression and maintenance.

Impact of Adenosine on Wavefront Propagation in Persistent Atrial Fibrillation: Insights From Global Noncontact Charge Density Mapping of the Left Atrium

Background

Adenosine shortens action potential duration and refractoriness and provokes atrial fibrillation. This study aimed to evaluate the effect of adenosine on mechanisms of wavefront propagation during atrial fibrillation.

Methods and Results

The study included 22 patients undergoing catheter ablation for persistent atrial fibrillation. Left atrial mapping was performed using the AcQMap charge density system before and after administration of intravenous adenosine at 1 or more of 3 time points during the procedure (before pulmonary vein isolation, after pulmonary vein isolation, and after nonpulmonary vein isolation ablation). Wave‐front propagation patterns were evaluated allowing identification and quantification of localized rotational activation (LRA), localized irregular activation, and focal firing. Additional signal processing was performed to identify phase singularities and calculate global atrial fibrillation cycle length and dominant frequency. A total of 35 paired maps were analyzed. Adenosine shortened mean atrial fibrillation cycle length from 181.7±14.3 to 165.1±16.3, (mean difference 16.6 ms; 95% CI, 11.3–21.9, P<0.0005) and increased dominant frequency from 6.0±0.7 Hz to 6.6±0.8 Hz (95% CI, 0.4–0.9, P<0.0005). This was associated with a 50% increase in the number of LRA occurrences (16.1±7.6–24.2±8.1; mean difference 8.1, 95% CI, 4.1–12, P<0.0005) as well as a 20% increase in the number of phase singularities detected (30.1±7.8–36.6±9.3; mean difference 6.5; 95% CI, 2.6–10.0, P=0.002). The percentage of left atrial surface area with LRA increased with adenosine and 42 of 70 zones (60%) with highest density of LRA coincided with high density LRA zones at baseline with only 28% stable across multiple maps.

Conclusions

Adenosine accelerates atrial fibrillation and promotes rotational activation patterns with no impact on focal activation. There is little evidence that rotational activation seen with adenosine represents promising targets for ablation aimed at sites of stable arrhythmogenic sources in the left atrium.

Future Directions for Mapping Atrial Fibrillation

Mapping for AF focuses on the identification of regions of interest that may guide management and - in particular - ablation therapy. Mapping may point to specific mechanisms associated with localised scar or fibrosis, or electrical features, such as localised repetitive, rotational or focal activation. In patients in whom AF is caused by disorganised waves with no spatial predilection, as proposed in the multiwavelet theory for AF, mapping would be of less benefit. The role of AF mapping is controversial at the current time in view of the debate over the underlying mechanisms. However, recent clinical expansions of mapping technologies confirm the importance of understanding the state of the art, including limitations of current approaches and potential areas of future development.

Understanding PITX2-Dependent Atrial Fibrillation Mechanisms through Computational Models

Atrial fibrillation (AF) is a common arrhythmia. Better prevention and treatment of AF are needed to reduce AF-associated morbidity and mortality. Several major mechanisms cause AF in patients, including genetic predispositions to AF development. Genome-wide association studies have identified a number of genetic variants in association with AF populations, with the strongest hits clustering on chromosome 4q25, close to the gene for the homeobox transcription PITX2. Because of the inherent complexity of the human heart, experimental and basic research is insufficient for understanding the functional impacts of PITX2 variants on AF. Linking PITX2 properties to ion channels, cells, tissues, atriums and the whole heart, computational models provide a supplementary tool for achieving a quantitative understanding of the functional role of PITX2 in remodelling atrial structure and function to predispose to AF. It is hoped that computational approaches incorporating all we know about PITX2-related structural and electrical remodelling would provide better understanding into its proarrhythmic effects leading to development of improved anti-AF therapies. In the present review, we discuss advances in atrial modelling and focus on the mechanistic links between PITX2 and AF. Challenges in applying models for improving patient health are described, as well as a summary of future perspectives.

Computational models of atrial fibrillation: achievements, challenges, and perspectives for improving clinical care

Despite significant advances in its detection, understanding and management, atrial fibrillation (AF) remains a highly prevalent cardiac arrhythmia with a major impact on morbidity and mortality of millions of patients. AF results from complex, dynamic interactions between risk factors and comorbidities that induce diverse atrial remodelling processes. Atrial remodelling increases AF vulnerability and persistence, while promoting disease progression. The variability in presentation and wide range of mechanisms involved in initiation, maintenance and progression of AF, as well as its associated adverse outcomes, make the early identification of causal factors modifiable with therapeutic interventions challenging, likely contributing to suboptimal efficacy of current AF management. Computational modelling facilitates the multilevel integration of multiple datasets and offers new opportunities for mechanistic understanding, risk prediction and personalized therapy. Mathematical simulations of cardiac electrophysiology have been around for 60 years and are being increasingly used to improve our understanding of AF mechanisms and guide AF therapy. This narrative review focuses on the emerging and future applications of computational modelling in AF management. We summarize clinical challenges that may benefit from computational modelling, provide an overview of the different in silico approaches that are available together with their notable achievements, and discuss the major limitations that hinder the routine clinical application of these approaches. Finally, future perspectives are addressed. With the rapid progress in electronic technologies including computing, clinical applications of computational modelling are advancing rapidly. We expect that their application will progressively increase in prominence, especially if their added value can be demonstrated in clinical trials.

Novel approaches to mechanism-based atrial fibrillation ablation

Modern cardiac electrophysiology has reported significant advances in the understanding of mechanisms underlying complex wave propagation patterns during atrial fibrillation (AF), although disagreements remain. One school of thought adheres to the long-held postulate that AF is the result of randomly propagating wavelets that wonder throughout the atria. Another school supports the notion that AF is deterministic in that it depends on a small number of high-frequency rotors generating three-dimensional scroll waves that propagate throughout the atria. The spiralling waves are thought to interact with anatomic and functional obstacles, leading to fragmentation and new wavelet formation associated with the irregular activation patterns documented on AF tracings. The deterministic hypothesis is consistent with demonstrable hierarchical gradients of activation frequency and AF termination on ablation at specific (non-random) atrial regions. During the last decade, data from realistic animal models and pilot clinical series have triggered a new era of novel methodologies to identify and ablate AF drivers outside the pulmonary veins. New generation electroanatomical mapping systems and multielectrode mapping catheters, complimented by powerful mathematical analyses, have generated the necessary platforms and tools for moving these approaches into clinical procedures. Recent clinical data using such platforms have provided encouraging evidence supporting the feasibility of targeting and effectively ablating driver regions in addition to pulmonary vein isolation in persistent AF. Here, we review state-of-the-art technologies and provide a comprehensive historical perspective, characterization, classification, and expected outcomes of current mechanism-based methods for AF ablation. We discuss also the challenges and expected future directions that scientists and clinicians will face in their efforts to understand AF dynamics and successfully implement any novel method into regular clinical practice.

Comprehensive evaluation of electrophysiological and 3D structural features of human atrial myocardium with insights on atrial fibrillation maintenance mechanisms

Atrial fibrillation (AF) occurrence and maintenance is associated with progressive remodeling of electrophysiological (repolarization and conduction) and 3D structural (fibrosis, fiber orientations, and wall thickness) features of the human atria. Significant diversity in AF etiology leads to heterogeneous arrhythmogenic electrophysiological and structural substrates within the 3D structure of the human atria. Since current clinical methods have yet to fully resolve the patient-specific arrhythmogenic substrates, mechanism-based AF treatments remain underdeveloped. Here, we review current knowledge from in-vivo, ex-vivo, and in-vitro human heart studies, and discuss how these studies may provide new insights on the synergy of atrial electrophysiological and 3D structural features in AF maintenance. In-vitro studies on surgically acquired human atrial samples provide a great opportunity to study a wide spectrum of AF pathology, including functional changes in single-cell action potentials, ion channels, and gene/protein expression. However, limited size of the samples prevents evaluation of heterogeneous AF substrates and reentrant mechanisms. In contrast, coronary-perfused ex-vivo human hearts can be studied with state-of-the-art functional and structural technologies, such as high-resolution near-infrared optical mapping and contrast-enhanced MRI. These imaging modalities can resolve atrial arrhythmogenic substrates and their role in reentrant mechanisms maintaining AF and validate clinical approaches. Nonetheless, longitudinal studies are not feasible in explanted human hearts. As no approach is perfect, we suggest that combining the strengths of direct human atrial studies with high fidelity approaches available in the laboratory and in realistic patient-specific computer models would elucidate deeper knowledge of AF mechanisms. We propose that a comprehensive translational pipeline from ex-vivo human heart studies to longitudinal clinically relevant AF animal studies and finally to clinical trials is necessary to identify patient-specific arrhythmogenic substrates and develop novel AF treatments.

Unmasking Arrhythmogenic Hubs of Reentry Driving Persistent Atrial Fibrillation for Patient-Specific Treatment

Background

Atrial fibrillation (AF) driver mechanisms are obscured to clinical multielectrode mapping approaches that provide partial, surface‐only visualization of unstable 3‐dimensional atrial conduction. We hypothesized that transient modulation of refractoriness by pharmacologic challenge during multielectrode mapping improves visualization of hidden paths of reentrant AF drivers for targeted ablation.

Methods and Results

Pharmacologic challenge with adenosine was tested in ex vivo human hearts with a history of AF and cardiac diseases by multielectrode and high‐resolution subsurface near‐infrared optical mapping, integrated with 3‐dimensional structural imaging and heart‐specific computational simulations. Adenosine challenge was also studied on acutely terminated AF drivers in 10 patients with persistent AF. Ex vivo, adenosine stabilized reentrant driver paths within arrhythmogenic fibrotic hubs and improved visualization of reentrant paths, previously seen as focal or unstable breakthrough activation pattern, for targeted AF ablation. Computational simulations suggested that shortening of atrial refractoriness by adenosine may (1) improve driver stability by annihilating spatially unstable functional blocks and tightening reentrant circuits around fibrotic substrates, thus unmasking the common reentrant path; and (2) destabilize already stable reentrant drivers along fibrotic substrates by accelerating competing fibrillatory wavelets or secondary drivers. In patients with persistent AF, adenosine challenge unmasked hidden common reentry paths (9/15 AF drivers, 41±26% to 68±25% visualization), but worsened visualization of previously visible reentry paths (6/15, 74±14% to 34±12%). AF driver ablation led to acute termination of AF.

Conclusions

Our ex vivo to in vivo human translational study suggests that transiently altering atrial refractoriness can stabilize reentrant paths and unmask arrhythmogenic hubs to guide targeted AF driver ablation treatment.