Fibrosis and Atrial Fibrillation: Computerized and Optical Mapping; A View into the Human Atria at Submillimeter Resolution

Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation

The complexity of cardiac electrophysiology, involving dynamic changes in numerous components across multiple spatial (from ion channel to organ) and temporal (from milliseconds to days) scales, makes an intuitive or empirical analysis of cardiac arrhythmogenesis challenging. Multiscale mechanistic computational models of cardiac electrophysiology provide precise control over individual parameters, and their reproducibility enables a thorough assessment of arrhythmia mechanisms. This review provides a comprehensive analysis of models of cardiac electrophysiology and arrhythmias, from the single cell to the organ level, and how they can be leveraged to better understand rhythm disorders in cardiac disease and to improve heart patient care. Key issues related to model development based on experimental data are discussed, and major families of human cardiomyocyte models and their applications are highlighted. An overview of organ-level computational modeling of cardiac electrophysiology and its clinical applications in personalized arrhythmia risk assessment and patient-specific therapy of atrial and ventricular arrhythmias is provided. The advancements presented here highlight how patient-specific computational models of the heart reconstructed from patient data have achieved success in predicting risk of sudden cardiac death and guiding optimal treatments of heart rhythm disorders. Finally, an outlook toward potential future advances, including the combination of mechanistic modeling and machine learning/artificial intelligence, is provided. As the field of cardiology is embarking on a journey toward precision medicine, personalized modeling of the heart is expected to become a key technology to guide pharmaceutical therapy, deployment of devices, and surgical interventions.

RAS Dataset: A 3D Cardiac LGE-MRI Dataset for Segmentation of Right Atrial Cavity

The current challenge in effectively treating atrial fibrillation (AF) stems from a limited understanding of the intricate structure of the human atria. The objective and quantitative interpretation of the right atrium (RA) in late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) scans relies heavily on its precise segmentation. Leveraging the potential of artificial intelligence (AI) for RA segmentation presents a promising solution. However, the successful implementation of AI in this context necessitates access to a substantial volume of annotated LGE-MRI images for model training. In this paper, we present a comprehensive 3D cardiac dataset comprising 50 high-resolution LGE-MRI scans, each meticulously annotated at the pixel level. The annotation process underwent rigorous standardization through crowdsourcing among a panel of medical experts, ensuring the accuracy and consistency of the annotations. Our dataset represents a significant contribution to the field, providing a valuable resource for advancing RA segmentation methods.

Atrial fibrosis heterogeneity is a risk for atrial fibrillation in pigs with ischaemic heart failure

BACKGROUND

Atrial fibrillation (AF) is the most common arrhythmia and is associated with considerable morbidity and mortality. Ischaemic heart failure (IHF) remains one of the most common causes of AF in clinical practice. However, ischaemia-mediated mechanisms leading to AF are still incompletely understood, and thus, current treatment approaches are limited. To improve our understanding of the pathophysiology, we studied a porcine IHF model.

METHODS

In pigs, IHF was induced by balloon occlusion of the left anterior descending artery for 90 min. After 30 days of reperfusion, invasive haemodynamic measurements and electrophysiological studies were performed. Masson trichrome and immunofluorescence staining were conducted to assess interstitial fibrosis and myofibroblast activation in different heart regions.

RESULTS

After 30 days of reperfusion, heart failure with significantly reduced ejection fraction (left anterior obique 30°, 34.78 ± 3.29% [IHF] vs. 62.03 ± 2.36% [control], p < .001; anterior-posterior 0°, 29.16 ± 3.61% vs. 59.54 ± 1.09%, p < .01) was observed. These pigs showed a significantly higher susceptibility to AF (33.90% [IHF] vs. 12.98% [control], p < .05). Histological assessment revealed aggravated fibrosis in atrial appendages but not in atrial free walls in IHF pigs (11.13 ± 1.44% vs. 5.99 ± .86%, p < .01 [LAA], 8.28 ± .56% vs. 6.01 ± .35%, p < .01 [RAA]), which was paralleled by enhanced myofibroblast activation (12.09 ± .65% vs. 9.00 ± .94%, p < .05 [LAA], 14.37 ± .60% vs. 10.30 ± 1.41%, p < .05 [RAA]). Correlation analysis indicated that not fibrosis per se but its cross-regional heterogeneous distribution across the left atrium was associated with AF susceptibility (r = .6344, p < .01).

CONCLUSION

Our results suggest that left atrial cross-regional fibrosis difference rather than overall fibrosis level is associated with IHF-related AF susceptibility, presumably by establishing local conduction disturbances and heterogeneity.

Left atrial volume affects the correlation of voltage map with magnetic resonance imaging

BACKGROUND

The low-voltage area detected by electroanatomic mapping (EAM) is a surrogate marker of left atrial fibrosis. However, the correlation between the EAM and late gadolinium enhancement magnetic resonance imaging (LGE-MRI) has been inconsistent among studies. This study aimed to investigate how LA size affects the correlation between EAM and LGE-MRI.

METHODS

High-density EAMs of the LA during sinus rhythm were collected in 22 patients undergoing AF ablation. The EAMs were co-registered with pre-ablation LGE-MRI models. Voltages in the areas with and without LGE were recorded. Left atrial volume index (LAVI) was calculated from MRI, and LAVI > 62 ml/m2 was defined as significant LA enlargement (LAE).

RESULTS

Atrial bipolar voltage negatively correlates with the left atrial volume index. The median voltages in areas without LGE were 1.1 mV vs 2.0 mV in patients with vs without significant LAE (p = 0.002). In areas of LGE, median voltages were 0.4 mV vs 0.8 mV in patients with vs without significant LAE (p = 0.02). A voltage threshold of 1.7 mV predicted atrial LGE in patients with normal or mildly enlarged LA (sensitivity and specificity of 74% and 59%, respectively). In contrast, areas of voltage less than 0.75 mV correlated with LGE in patients with significant LA enlargement (sensitivity 68% and specificity 66%).

CONCLUSIONS

LAVI affects left atrial bipolar voltage, and the correlation between low-voltage areas and LGE-MRI. Distinct voltage thresholds according to the LAVI value might be considered to identify atrial scar by EAM.

Effect of late gadolinium enhancement on left atrial impairment in myocarditis patients

OBJECTIVE

The aims of our study were to investigate the effect of the extent and location of late gadolinium enhancement (LGE) on the left atrium (LA) function in patients with acute myocarditis (AM) using cardiovascular magnetic resonance (CMR).

METHOD

This retrospective study performed CMR scans in 113 consecutive patients (89 males, 24 females; mean age 45.8 ± 17.3 years) with AM that met the updated Lake Louise criteria. Reservoir, conduit, and booster LA functions were analyzed by CMR feature tracking using dedicated software. Besides LA strain measurements, myocardial scar location and extent were assigned and quantified by LGE imaging.

RESULTS

AM patients with septal LGE had impaired reservoir, conduit, and conduit strain rate function in comparison with AM patients with non-septal LGE (p = 0.001, for all). In fully adjusted multivariable linear regression, reservoir and conduit were significantly associated with left ventricle (LV) LGE location (β coefficient = 8.205, p = 0.007; β coefficient = 5.185, p = 0.026; respectively). In addition, LA parameters decreased according to the increase in the extent of LV fibrosis (LGE ≤ 10%; LGE 11-19%; LGE ≥ 20%). After adjustment in multivariable linear regression, the association with LV LGE extent was no longer statistically significant.

CONCLUSION

In patients with acute myocarditis, LA function abnormalities are significantly associated with LV LGE location, but not with LGE extent. Septal LGE is paralleled by a deterioration of LA reservoir and conduit function.

CLINICAL RELEVANCE STATEMENT

Left atrium dysfunction is associated with the presence of late gadolinium enhancement in the left ventricle septum and can be useful in the clinical prognostication of patients with acute myocarditis, allowing individually tailored treatment.

KEY POINTS

• Myocardial fibrosis is related to atrial impairment. • The location of myocardial fibrosis is the main determinant of atrial dysfunction in myocarditis patients. • The quantification of atrial mechanisms may provide more in-depth insight into myocarditis pathophysiology.

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.

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.

Effect of pulmonary vein isolation on rotor/multiple wavelet dynamics in persistent atrial fibrillation, association with vagal response and implications for adjunctive ablation

Persistent atrial fibrillation (PeAF) may develop arrhythmogenic substrates of rotors/multiple wavelets. However, the ways in which pulmonary vein isolation (PVI) affects the dynamics of rotor/multiple wavelets in PeAF patients remain elusive. Real-time phase-mapping (ExTRa mapping, EXT) in the whole left atrium (LA) was performed during PeAF before and after PVI (n = 111). The percentage of time in which rotor/multiple wavelets (phase singularities) was observed during each 5-s phase-mapping recording (non-passive activation ratio, %NP) was measured as an index of its burden. The mapping areas showing %NP ≥ 50% were defined as rotor/multiple-wavelet substrates (RSs). Before PVI, RSs were globally distributed in the LA. After PVI, %NP decreased (< 50%) in many RSs (PVI-modifiable RSs) but remained high (≥ 50%) in some RSs, especially localized in the anterior/septum/inferior regions (PVI-unmodifiable RSs, 2.3 ± 1.0 areas/patient). Before PVI, vagal response (VR) to high-frequency stimulation was observed in 23% of RSs, especially localized in the inferior region. VR disappearance after PVI was more frequently observed in PVI-modifiable RSs (79%) than in PVI-unmodifiable RSs (55%, p < 0.05), suggesting that PVI affects autonomic nerve activities and rotor/multiple wavelet dynamics. PVI-unmodifiable RSs were adjunctively ablated in 104 patients. The 1-year AT/AF-free survival rate was 70% in those with PVI alone (n = 115), and 86% in patients with the adjunctive ablation (log-rank test = 7.65, p < 0.01). PVI suppresses not only ectopic firing but also rotor/multiple wavelets partly via modification of autonomic nerve activities. The adjunctive ablation of PVI-unmodifiable RSs improved the outcome in PeAF patients and might be a novel ablation strategy beyond PVI.

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.

Homocysteine and atrial fibrillation: novel evidences and insights

Atrial fibrillation (AF) is one of the most prevalent rhythm disorders worldwide, with around 37.574 million cases around the globe (0.51 % global population).  Different studies showed a high informative value of different biomarkers, including such related to the systemic inflammation, biomechanical stress and fibrosis. In this review article we aimed to study only the relation of homocysteine to the AF development. Homocysteine is a sulfur-containing amino acid, that is produced in the process of methionine metabolism. Which is a non-canonical amino acid, that is derived from the food proteins. From the scientific point of view there is a relation between hyperhomocysteinemia and myocardial fibrosis, but these mechanisms are complicated and not sufficiently studied. Homocysteine regulates activity of the ion channels through their redox state. Elevated homocysteine level can condition electrical remodeling of the cardiomyocytes through the increase of sodium current and change in the function of rapid sodium channels, increase of inwards potassium current and decrease in amount of rapid potassium channels. High homocysteine concentration also leads to the shortening of the action potential, loss of the rate adaptation of the action potential and persistent circulation of the re-entry waves. In a series of experimental studies on mice there was an association found between the homocysteine level and activity of vascular inflammation. Elevation of homocysteine level is an independent factor of the thromboembolic events and AF relapses. Population studies showed, that homocysteine is an independent risk factor for AF. So, homocysteine is an interesting target for up-stream therapy.

Quantification of Myocyte Disarray in Human Cardiac Tissue

Proper three-dimensional (3D)-cardiomyocyte orientation is important for an effective tension production in cardiac muscle. Cardiac diseases can cause severe remodeling processes in the heart, such as cellular misalignment, that can affect both the electrical and mechanical functions of the organ. To date, a proven methodology to map and quantify myocytes disarray in massive samples is missing. In this study, we present an experimental pipeline to reconstruct and analyze the 3D cardiomyocyte architecture in massive samples. We employed tissue clearing, staining, and advanced microscopy techniques to detect sarcomeres in relatively large human myocardial strips with micrometric resolution. Z-bands periodicity was exploited in a frequency analysis approach to extract the 3D myofilament orientation, providing an orientation map used to characterize the tissue organization at different spatial scales. As a proof-of-principle, we applied the proposed method to healthy and pathologically remodeled human cardiac tissue strips. Preliminary results suggest the reliability of the method: strips from a healthy donor are characterized by a well-organized tissue, where the local disarray is log-normally distributed and slightly depends on the spatial scale of analysis; on the contrary, pathological strips show pronounced tissue disorganization, characterized by local disarray significantly dependent on the spatial scale of analysis. A virtual sample generator is developed to link this multi-scale disarray analysis with the underlying cellular architecture. This approach allowed us to quantitatively assess tissue organization in terms of 3D myocyte angular dispersion and may pave the way for developing novel predictive models based on structural data at cellular resolution.

Impaired left atrial reservoir and conduit strain in patients with atrial fibrillation and extensive left atrial fibrosis

BACKGROUND

Atrial fibrillation (AF) is associated with profound structural and functional changes in the atria. In the present study, we investigated the association between left atrial (LA) phasic function and the extent of LA fibrosis using advanced cardiovascular magnetic resonance (CMR) imaging techniques, including 3-dimensional (3D) late gadolinium enhancement (LGE) and feature tracking.

METHODS

Patients with paroxysmal and persistent AF (n = 105) underwent CMR in sinus rhythm. LA global reservoir strain, conduit strain and contractile strain were derived from cine CMR images using CMR feature tracking. The extent of LA fibrosis was assessed from 3D LGE images. Healthy subjects underwent CMR and served as controls (n = 19).

RESULTS

Significantly lower LA reservoir strain, conduit strain and contractile strain were found in AF patients, as compared to healthy controls (- 15.9 ± 3.8% vs. - 21.1 ± 3.6% P < 0.001, - 8.7 ± 2.7% vs. - 12.6 ± 2.5% P < 0.001 and - 7.2 ± 2.3% vs. - 8.6 ± 2.2% P = 0.02, respectively). Patients with a high degree of LA fibrosis (dichotomized by the median value) had lower reservoir strain and conduit strain compared to patients with a low degree of LA fibrosis (- 15.0 ± 3.9% vs. - 16.9 ± 3.3%, P = 0.02 and - 7.9 ± 2.7% vs. - 9.5 ± 2.6%, P = 0.01, respectively). In contrast, no difference was found for LA contractile strain (- 7.1 ± 2.4% vs. - 7.4 ± 2.3%, P = 0.55).

CONCLUSIONS

Impaired LA reservoir and conduit strain are present in AF patients with extensive atrial fibrosis. Future studies are needed to examine the biologic nature of this association and possible therapeutic implications.

Fibrotic Remodeling during Persistent Atrial Fibrillation: In Silico Investigation of the Role of Calcium for Human Atrial Myofibroblast Electrophysiology

During atrial fibrillation, cardiac tissue undergoes different remodeling processes at different scales from the molecular level to the tissue level. One central player that contributes to both electrical and structural remodeling is the myofibroblast. Based on recent experimental evidence on myofibroblasts' ability to contract, we extended a biophysical myofibroblast model with Ca²⁺ handling components and studied the effect on cellular and tissue electrophysiology. Using genetic algorithms, we fitted the myofibroblast model parameters to the existing in vitro data. In silico experiments showed that Ca²⁺ currents can explain the experimentally observed variability regarding the myofibroblast resting membrane potential. The presence of an L-type Ca²⁺ current can trigger automaticity in the myofibroblast with a cycle length of 799.9 ms. Myocyte action potentials were prolonged when coupled to myofibroblasts with Ca²⁺ handling machinery. Different spatial myofibroblast distribution patterns increased the vulnerable window to induce arrhythmia from 12 ms in non-fibrotic tissue to 22 ± 2.5 ms and altered the reentry dynamics. Our findings suggest that Ca²⁺ handling can considerably affect myofibroblast electrophysiology and alter the electrical propagation in atrial tissue composed of myocytes coupled with myofibroblasts. These findings can inform experimental validation experiments to further elucidate the role of myofibroblast Ca²⁺ handling in atrial arrhythmogenesis.

Atrial slow conduction develops and dynamically expands during premature stimulation in an animal model of persistent atrial fibrillation

Slow conduction areas and conduction block in the atria are considered pro-arrhythmic conditions. Studies examining the size and distribution of slow conduction regions in the context of persistent atrial fibrillation (AF) may help to develop improved therapeutic strategies for patients with AF. In this work, we studied the differences of size and number in slow conduction areas between control and persistent AF goats and the influence of propagation direction on the development of these pathological conduction areas. Epicardial atrial electrical activations from the left atrial roof were optically mapped with physiological pacing cycle lengths and for the shortest captured cycle lengths. The recordings were converted to local activation times and conduction velocity measures. Regions with slow conduction velocity (less than [Formula: see text]) were identified. The size of the connected regions and the number of non-connected regions were counted for propagation from different orthogonal directions. We found that regions of slow conduction significantly increases in our 15 persistent AF goat recordings in response to premature stimulation (24.4±4.3% increase to 36.6±4.4%, p < 0.001). This increase is driven by an increase of size from (3.70±0.89[mm2] to 6.36±0.91[mm2], p = 0.014) for already existing regions and not by generation of new slow conduction regions (11.6±1.8 vs. 13±1.9, p = 0.242). In 12 control goat recordings, no increase from baseline pacing to premature pacing was found. Similarly, size of the slow conduction areas and the count did not change significantly in control animals.

Multiparameter optimization of nonuniform passive diffusion properties for creating coarse-grained equivalent models of cardiac propagation

The arrhythmogenic role of discrete cardiac propagation may be assessed by comparing discrete (fine-grained) and equivalent continuous (coarse-grained) models. We aim to develop an optimization algorithm for estimating the smooth conductivity field that best reproduces the diffusion properties of a given discrete model. Our algorithm iteratively adjusts local conductivity of the coarse-grained continuous model by simulating passive diffusion from white noise initial conditions during 3-10 ms and computing the root mean square error with respect to the discrete model. The coarse-grained conductivity field was interpolated from up to 300 evenly spaced control points. We derived an approximate formula for the gradient of the cost function that required (in two dimensions) only two additional simulations per iteration regardless of the number of estimated parameters. Conjugate gradient solver facilitated simultaneous optimization of multiple conductivity parameters. The method was tested in rectangular anisotropic tissues with uniform and nonuniform conductivity (slow regions with sinusoidal profile) and random diffuse fibrosis, as well as in a monolayer interconnected cable model of the left atrium with spatially-varying fibrosis density. Comparison of activation maps served as validation. The results showed that after convergence the errors in activation time were < 1 ms for rectangular geometries and 1-3 ms in the atrial model. Our approach based on the comparison of passive properties (<10 ms simulation) avoids performing active propagation simulations (>100 ms) at each iteration while reproducing activation maps, with possible applications to investigating the impact of microstructure on arrhythmias.

Simulation of diffuse and stringy fibrosis in a bilayer interconnected cable model of the left atrium

AIMS

The aim of this study is to design a computer model of the left atrium for investigating fibre-orientation-dependent microstructure such as stringy fibrosis.

METHODS AND RESULTS

We developed an approach for automatic construction of bilayer interconnected cable models from left atrial geometry and epi- and endocardial fibre orientation. The model consisted of two layers (epi- and endocardium) of longitudinal and transverse cables intertwined-like fabric threads, with a spatial discretization of 100 µm. Model validation was performed by comparison with cubic volumetric models in normal conditions. Then, diffuse (n = 2904), stringy (n = 3600), and mixed fibrosis patterns (n = 6840) were randomly generated by uncoupling longitudinal and transverse connections in the interconnected cable model. Fibrosis density was varied from 0% to 40% and mean stringy obstacle length from 0.1 to 2 mm. Total activation time, apparent anisotropy ratio, and local activation time jitter were computed during normal rhythm in each pattern. Non-linear regression formulas were identified for expressing measured propagation parameters as a function of fibrosis density and obstacle length (stringy and mixed patterns). Longer obstacles (even below tissue space constant) were independently associated with prolonged activation times, increased anisotropy, and local fluctuations in activation times. This effect was increased by endo-epicardial dissociation and mitigated when fibrosis was limited to the epicardium.

CONCLUSION

Interconnected cable models enable the study of microstructure in organ-size models despite limitations in the description of transmural structures.

Spatial concentration and distribution of phase singularities in human atrial fibrillation: Insights for the AF mechanism

BACKGROUND

Atrial fibrillation (AF) is characterized by the repetitive regeneration of unstable rotational events, the pivot of which are known as phase singularities (PSs). The spatial concentration and distribution of PSs have not been systematically investigated using quantitative statistical approaches.

OBJECTIVES

We utilized a geospatial statistical approach to determine the presence of local spatial concentration and global clustering of PSs in biatrial human AF recordings.

METHODS

64-electrode conventional basket (~5 min, n = 18 patients, persistent AF) recordings were studied. Phase maps were produced using a Hilbert-transform based approach. PSs were characterized spatially using the following approaches: (i) local "hotspots" of high phase singularity (PS) concentration using Getis-Ord Gi* (Z ≥ 1.96, P ≤ .05) and (ii) global spatial clustering using Moran's I (inverse distance matrix).

RESULTS

Episodes of AF were analyzed from basket catheter recordings (H: 41 epochs, 120 000 s, n = 18 patients). The Getis-Ord Gi* statistic showed local PS hotspots in 12/41 basket recordings. As a metric of spatial clustering, Moran's I showed an overall mean of 0.033 (95% CI: 0.0003-0.065), consistent with the notion of complete spatial randomness.

CONCLUSION

Using a systematic, quantitative geospatial statistical approach, evidence for the existence of spatial concentrations ("hotspots") of PSs were detectable in human AF, along with evidence of spatial clustering. Geospatial statistical approaches offer a new approach to map and ablate PS clusters using substrate-based approaches.

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.

Using Machine Learning to Characterize Atrial Fibrotic Substrate From Intracardiac Signals With a Hybrid in silico and in vivo Dataset

In patients with atrial fibrillation, intracardiac electrogram signal amplitude is known to decrease with increased structural tissue remodeling, referred to as fibrosis. In addition to the isolation of the pulmonary veins, fibrotic sites are considered a suitable target for catheter ablation. However, it remains an open challenge to find fibrotic areas and to differentiate their density and transmurality. This study aims to identify the volume fraction and transmurality of fibrosis in the atrial substrate. Simulated cardiac electrograms, combined with a generalized model of clinical noise, reproduce clinically measured signals. Our hybrid dataset approach combines in silico and clinical electrograms to train a decision tree classifier to characterize the fibrotic atrial substrate. This approach captures different in vivo dynamics of the electrical propagation reflected on healthy electrogram morphology and synergistically combines it with synthetic fibrotic electrograms from in silico experiments. The machine learning algorithm was tested on five patients and compared against clinical voltage maps as a proof of concept, distinguishing non-fibrotic from fibrotic tissue and characterizing the patient's fibrotic tissue in terms of density and transmurality. The proposed approach can be used to overcome a single voltage cut-off value to identify fibrotic tissue and guide ablation targeting fibrotic areas.

Atrial fibrosis as a dominant factor for the development of atrial fibrillation: facts and gaps

Atrial fibrillation (AF), the most commonly diagnosed arrhythmia, affects a notable percentage of the population and constitutes a major risk factor for thromboembolic events and other heart-related conditions. Fibrosis plays an important role in the onset and perpetuation of AF through structural and electrical remodelling processes. Multiple molecular pathways are involved in atrial substrate modification and the subsequent maintenance of AF. In this review, we aim to recapitulate underlying molecular pathways leading to atrial fibrosis and to indicate existing gaps in the complex interplay of atrial fibrosis and AF.

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.

Imaging Techniques for the Study of Fibrosis in Atrial Fibrillation Ablation: From Molecular Mechanisms to Therapeutical Perspectives

Atrial fibrillation (AF) is the most prevalent form of cardiac arrhythmia. It is often related to diverse pathological conditions affecting the atria and leading to remodeling processes including collagen accumulation, fatty infiltration, and amyloid deposition. All these events generate atrial fibrosis, which contribute to beget AF. In this scenario, cardiac imaging appears as a promising noninvasive tool for monitoring the presence and degree of LA fibrosis and remodeling. The aim of this review is to comprehensively examine the bench mechanisms of atrial fibrosis moving, then to describe the principal imaging techniques that characterize it, such as cardiac magnetic resonance (CMR) and multidetector cardiac computed tomography (MDCT), in order to tailor atrial fibrillation ablation to each individual.

Atrial fibrillation and cardiac fibrosis

The understanding of atrial fibrillation (AF) evolved from a sole rhythm disturbance towards the complex concept of a cardiomyopathy based on arrhythmia substrates. There is evidence that atrial fibrosis can be visualized using late gadolinium enhancement cardiac magnetic resonance imaging and that it is a powerful predictor for the outcome of AF interventions. However, a strategy of an individual and fibrosis guided management of AF looks promising but results from prospective multicentre trials are pending. This review gives an overview about the relationship between cardiac fibrosis and AF focusing on translational aspects, clinical observations, and fibrosis imaging to emphasize the concept of personalized paths in AF management taking into account the individual amount and distribution of fibrosis.

Left Atrial Myopathy in Atrial Fibrillation and Heart Failure: Clinical Implications, Mechanisms, and Therapeutic Targets

PURPOSE OF REVIEW

This review discusses the mechanisms, clinical implications, and treatments of left atrial (LA) myopathy in comorbid atrial fibrillation (AF) and heart failure (HF) across the spectrum of ejection fraction.

RECENT FINDINGS

AF and HF are highly comorbid conditions. Left atrial (LA) myopathy, characterized by impairments in LA structure, function, or electrical conduction, plays a fundamental role in the development of both AF and HF with preserved ejection fraction (AF-HFpEF) along with AF and HF with reduced ejection fraction (AF-HFrEF). While the nature of LA myopathy in AF-HFpEF is unique from that of AF-HFrEF, LA myopathy also leads to progression of both of these conditions. There may be a vulnerable cohort of AF-HF patients who have a disproportionate degree of LA myopathy compared with left ventricular (LV) dysfunction. Further investigations are required to identify therapies to improve LA function in this cohort.

Cardiac MRI to Manage Atrial Fibrillation

AF is the most common arrhythmia in clinical practice. In addition to the severe effect on quality of life, patients with AF are at higher risk of stroke and mortality. Recent studies have suggested that atrial and ventricular substrate play a major role in the development and maintenance of AF. Cardiac MRI has emerged as a viable tool for interrogating the underlying substrate in AF patients. Its advantage includes localisation and quantification of structural remodelling. Cardiac MRI of the atrial substrate is not only a tool for management and treatment of arrhythmia, but also to individualise the prevention of stroke and major cardiovascular events. This article provides an overview of atrial imaging using cardiac MRI and its clinical implications in the AF population.

Translational applications of computational modelling for patients with cardiac arrhythmias

Cardiac arrhythmia is associated with high morbidity, and its underlying mechanisms are poorly understood. Computational modelling and simulation approaches have the potential to improve standard-of-care therapy for these disorders, offering deeper understanding of complex disease processes and sophisticated translational tools for planning clinical procedures. This review provides a clinician-friendly summary of recent advancements in computational cardiology. Organ-scale models automatically generated from clinical-grade imaging data are used to custom tailor our understanding of arrhythmia drivers, estimate future arrhythmogenic risk and personalise treatment plans. Recent mechanistic insights derived from atrial and ventricular arrhythmia simulations are highlighted, and the potential avenues to patient care (eg, by revealing new antiarrhythmic drug targets) are covered. Computational approaches geared towards improving outcomes in resynchronisation therapy have used simulations to elucidate optimal patient selection and lead location. Technology to personalise catheter ablation procedures are also covered, specifically preliminary outcomes form early-stage or pilot clinical studies. To conclude, future developments in computational cardiology are discussed, including improving the representation of patient-specific fibre orientations and fibrotic remodelling characterisation and how these might improve understanding of arrhythmia mechanisms and provide transformative tools for patient-specific therapy.

Linking Electrical Drivers With Atrial Cardiomyopathy for the Targeted Treatment of Atrial Fibrillation

The relationship between atrial fibrillation (AF) and underlying functional and structural abnormalities has received substantial attention in the research literature over the past decade. Significant progress has been made in identifying these changes using non-invasive imaging, voltage mapping, and electrical recordings. Advances in computed tomography and cardiac magnetic resonance imaging can now provide insight regarding the presence and extent of cardiac fibrosis. Additionally, multiple technologies able to identify electrical targets during AF have emerged. However, an organized strategy to employ these resources in the targeted treatment of AF remains elusive. In this work, we will discuss the basis for mechanistic importance of atrial fibrosis and scar as potential sites promoting AF and emerging technologies to identify and target these structural and functional substrates in the electrophysiology laboratory. We also propose an approach to the use of such technologies to serve as a basis for ongoing work in the field.

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.

Efficacy and safety of dronedarone by atrial fibrillation history duration: Insights from the ATHENA study

Background

Atrial fibrillation/atrial flutter (AF/AFL) burden increases with increasing duration of AF/AFL history.

Hypothesis

Outcomes with dronedarone may also be impacted by duration of AF/AFL history.

Methods

In this post hoc analysis of ATHENA, efficacy and safety of dronedarone vs placebo were assessed in groups categorized by time from first known AF/AFL episode to randomization (ie, duration of AF/AFL history): <3 months (short), 3 to <24 months (intermediate), and ≥ 24 months (long).

Results

Of 2859 patients with data on duration of AF/AFL history, 45.3%, 29.6%, and 25.1% had short, intermediate, and long histories, respectively. Patients in the long history group had the highest prevalence of structural heart disease and were more likely to be in AF/AFL at baseline. Placebo‐treated patients in the long history group also had the highest incidence of AF/AFL recurrence and cardiovascular (CV) hospitalization during the study. The risk of first CV hospitalization/death from any cause was lower with dronedarone vs placebo in patients with short (hazard ratio, 0.79 [95% confidence interval: 0.65‐0.96]) and intermediate (0.72 [0.56‐0.92]) histories; a trend favoring dronedarone was also observed in patients with long history (0.84 [0.66‐1.07]). A similar pattern was observed for first AF/AFL recurrence. No new drug‐related safety issues were identified.

Conclusions

Patients with long AF/AFL history had the highest burden of AF/AFL at baseline and during the study. Dronedarone significantly improved efficacy vs placebo in patients with short and intermediate AF/AFL histories. While exploratory, these results support the potential value in initiating rhythm control treatment early in patients with AF/AFL.

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.

Optical Mapping-Validated Machine Learning Improves Atrial Fibrillation Driver Detection by Multi-Electrode Mapping

BACKGROUND

Atrial fibrillation (AF) can be maintained by localized intramural reentrant drivers. However, AF driver detection by clinical surface-only multielectrode mapping (MEM) has relied on subjective interpretation of activation maps. We hypothesized that application of machine learning to electrogram frequency spectra may accurately automate driver detection by MEM and add some objectivity to the interpretation of MEM findings.

METHODS

Temporally and spatially stable single AF drivers were mapped simultaneously in explanted human atria (n=11) by subsurface near-infrared optical mapping (NIOM; 0.3 mm² resolution) and 64-electrode MEM (higher density or lower density with 3 and 9 mm² resolution, respectively). Unipolar MEM and NIOM recordings were processed by Fourier transform analysis into 28 407 total Fourier spectra. Thirty-five features for machine learning were extracted from each Fourier spectrum.

RESULTS

Targeted driver ablation and NIOM activation maps efficiently defined the center and periphery of AF driver preferential tracks and provided validated annotations for driver versus nondriver electrodes in MEM arrays. Compared with analysis of single electrogram frequency features, averaging the features from each of the 8 neighboring electrodes, significantly improved classification of AF driver electrograms. The classification metrics increased when less strict annotation, including driver periphery electrodes, were added to driver center annotation. Notably, f1-score for the binary classification of higher-density catheter data set was significantly higher than that of lower-density catheter (0.81±0.02 versus 0.66±0.04, P<0.05). The trained algorithm correctly highlighted 86% of driver regions with higher density but only 80% with lower-density MEM arrays (81% for lower-density+higher-density arrays together).

CONCLUSIONS

The machine learning model pretrained on Fourier spectrum features allows efficient classification of electrograms recordings as AF driver or nondriver compared with the NIOM gold-standard. Future application of NIOM-validated machine learning approach may improve the accuracy of AF driver detection for targeted ablation treatment in patients.

Diverse activation patterns during persistent atrial fibrillation by noncontact charge-density mapping of human atrium

BACKGROUND

Global simultaneous recording of atrial activation during atrial fibrillation (AF) can elucidate underlying mechanisms contributing to AF maintenance. A better understanding of these mechanisms may allow for an individualized ablation strategy to treat persistent AF. The study aims to characterize left atrial endocardial activation patterns during AF using noncontact charge-density mapping.

METHODS

Twenty-five patients with persistent AF were studied. Activation patterns were characterized into three subtypes: (i) focal with centrifugal activation (FCA); (ii) localized rotational activation (LRA); and (iii) localized irregular activation (LIA). Continuous activation patterns were analyzed and distributed in 18 defined regions in the left atrium.

RESULTS

A total of 144 AF segments with 1068 activation patterns were analyzed. The most common pattern during AF was LIA (63%) which consists of four disparate features of activation: slow conduction (45%), pivoting (30%), collision (16%), and acceleration (7%). LRA was the second-most common pattern (20%). FCA accounted for 17% of all activations, arising frequently from the pulmonary veins (PVs)/ostia. A majority of patients (24/25; 96%) showed continuous and highly dynamic patterns of activation comprising multiple combinations of FCA, LRA, and LIA, transitioning from one to the other without a discernible order. Preferential conduction areas were typically seen in the mid-anterior (48%) and lower-posterior (40%) walls.

CONCLUSION

Atrial fibrillation is characterized by heterogeneous activation patterns identified in PV-ostia and non-PV regions throughout the LA at varying locations between individuals. Clinical implications of individualized ablation strategies guided by charge-density mapping need to be determined.

Systemic therapy in an RNA toxicity mouse model with an antisense oligonucleotide therapy targeting a non-CUG sequence within the DMPK 3'UTR RNA

Myotonic dystrophy type 1 (DM1), the most common adult muscular dystrophy, is an autosomal dominant disorder caused by an expansion of a (CTG)n tract within the 3' untranslated region (3'UTR) of the dystrophia myotonica protein kinase (DMPK) gene. Mutant DMPK mRNAs are toxic, present in nuclear RNA foci and correlated with a plethora of RNA splicing defects. Cardinal features of DM1 are myotonia and cardiac conduction abnormalities. Using transgenic mice, we have demonstrated that expression of the mutant DMPK 3'UTR is sufficient to elicit these features of DM1. Here, using these mice, we present a study of systemic treatment with an antisense oligonucleotide (ASO) (ISIS 486178) targeted to a non-CUG sequence within the 3'UTR of DMPK. RNA foci and DMPK 3'UTR mRNA levels were reduced in both the heart and skeletal muscles. This correlated with improvements in several splicing defects in skeletal and cardiac muscles. The treatment reduced myotonia and this correlated with increased Clcn1 expression. Furthermore, functional testing showed improvements in treadmill running. Of note, we demonstrate that the ASO treatment reversed the cardiac conduction abnormalities, and this correlated with restoration of Gja5 (connexin 40) expression in the heart. This is the first time that an ASO targeting a non-CUG sequence within the DMPK 3'UTR has demonstrated benefit on the key DM1 phenotypes of myotonia and cardiac conduction defects. Our data also shows for the first time that ASOs may be a viable option for treating cardiac pathology in DM1.

PITX2 upregulation increases the risk of chronic atrial fibrillation in a dose-dependent manner by modulating IKs and ICaL -insights from human atrial modelling

Background

Functional analysis has shown that the paired-like homeodomain transcription factor 2 (PITX2) overexpression associated with atrial fibrillation (AF) leads to the slow delayed rectifier K⁺ current (I_Ks) increase and the L-type Ca²⁺ current (I_CaL) reduction observed in isolated right atrial myocytes from chronic AF (CAF) patients. Through multiscale computational models, this study aimed to investigate the functional impact of the PITX2 overexpression on atrial electrical activity.

Methods

The well-known Courtemanche-Ramirez-Nattel (CRN) model of human atrial action potentials (APs) was updated to incorporate experimental data on alterations in I_Ks and I_CaL due to the PITX2 overexpression. These cell models for sinus rhythm (SR) and CAF were then incorporated into homogeneous multicellular one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) tissue models. The proarrhythmic effects of the PITX2 overexpression were quantified with ion current profiles, AP morphology, AP duration (APD) restitution, conduction velocity restitution (CVR), wavelength (WL), vulnerable window (VW) for unidirectional conduction block, and minimal substrate size required to induce re-entry. Dynamic behaviors of spiral waves were characterized by measuring lifespan (LS), tip patterns and dominant frequencies.

Results

The I_Ks increase and the I_CaL decrease arising from the PITX2 overexpression abbreviated APD and flattened APD restitution (APDR) curves in single cells. It reduced WL and increased CV at high excitation rates at the 1D tissue level. Although it had no effects on VW for initiating spiral waves, it decreased the minimal substrate size necessary to sustain re-entry. It also stabilized and accelerated spiral waves in 2D and 3D tissue models.

Conclusions

Electrical remodeling (I_Ks and I_CaL) due to the PITX2 overexpression increases susceptibility to AF due to increased tissue vulnerability, abbreviated APD, shortened WL and altered CV, which, in combination, facilitate initiation and maintenance of spiral waves.

Visualization of Inflammation After Cryoballoon Ablation in Atrial Fibrillation Patients - Protocol for Proof-of-Concept Feasibility Trial

Background: Atrial fibrosis and inflammation play important roles in perpetuating and initiating atrial fibrillation (AF). Although the fibrotic area can be visualized as a delayed enhancement area on late gadolinium enhancement magnetic resonance imaging (LGE-MRI), atrial inflammation has not yet been visualized on any imaging modality. We describe the protocol for a feasibility study to visualize atrial inflammation on positron emission tomography/MRI (PET/MRI).

Methods and Results: This is a single-arm, prospective, open-label proof-of concept trial, involving AF patients after cryoballoon ablation (CBA). A total of 30 paroxysmal AF patients will be enrolled and undergo simultaneous PET/MRI for the assessment of regional ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) uptake 1 day after the CBA. Furthermore, LGE-MRI will be performed before CBA, and at 1 and 4 weeks after assessing the regional LGE area. The main outcome measures will be (1) the feasibility of imaging inflammation in the left atrium on PET/MRI; and (2) the safety of the intervention.

Conclusions: There are few data on the visualization of atrial inflammation using PET/MRI. Establishing the visualization methodology will contribute to elucidating the fundamental histopathologic findings of the progress to fibrosis, and to the planning and execution of a larger definitive trial to test the usefulness of PET/MRI.

Structural Analysis of Complex Atrial Intramural Microstructure from A Multi-layer Model Based on Siamese Network

Quantitative analysis of complex atrial intramural microstructure is a crucial step towards understanding the mechanism behind atrial fibrillation (AF) maintenance. Siamese network was adopted to extract features from computationally simulated multi-layer fibrosis structure. Through analysis of the features produced by the feature extractor, the difference between Non-sustained and Sustained simulations was comprehended intuitively and electrophysiologically. Complex conduction pathway marked by the feature extractor might be an indicator for AF radio-frequency ablation clinically.

Successful modulation of atrial fibrillation drivers anchoring to fibrotic tissue after box isolation using an online real-time phase mapping system: ExTRa Mapping

A 41-year-old man with persistent atrial fibrillation (AF) underwent radiofrequency (RF) catheter ablation using an online real-time phase mapping system: ExTRa Mapping. Box isolation could not terminate AF. Subsequently, RF applications on nonpassively activated areas (NPAs), where rotational activations were frequently observed, at the posterior bottom of left atrium outside of box lesion could convert AF to common atrial flutter. Of interest, the NPA near the posterior bottom were located on the patchy fibrotic tissue area assessed by the late-gadolinium enhancement magnetic resonance imaging. This indicated the possibility of the critical AF rotor meandering through the fibrotic tissue area.

Acetylcholine Delays Atrial Activation to Facilitate Atrial Fibrillation

Background

Acetylcholine (ACh) shortens action potential duration (APD) in human atria. APD shortening facilitates atrial fibrillation (AF) by reducing the wavelength for reentry. However, the influence of ACh on electrical conduction in human atria and its contribution to AF are unclear, particularly when combined with impaired conduction from interstitial fibrosis.

Objective

To investigate the effect of ACh on human atrial conduction and its role in AF with computational, experimental, and clinical approaches.

Methods

S1S2 pacing (S1 = 600 ms and S2 = variable cycle lengths) was applied to the following human AF computer models: a left atrial appendage (LAA) myocyte to quantify the effects of ACh on APD, maximum upstroke velocity (V _max ), and resting membrane potential (RMP); a monolayer of LAA myocytes to quantify the effects of ACh on conduction; and 3) an intact left atrium (LA) to determine the effects of ACh on arrhythmogenicity. Heterogeneous ACh and interstitial fibrosis were applied to the monolayer and LA models. To corroborate the simulations, APD and RMP from isolated human atrial myocytes were recorded before and after 0.1 μM ACh. At the tissue level, LAAs from AF patients were optically mapped ex vivo using Di-4-ANEPPS. The difference in total activation time (AT) was determined between AT initially recorded with S1 pacing, and AT recorded during subsequent S1 pacing without (n = 6) or with (n = 7) 100 μM ACh.

Results

In LAA myocyte simulations, S1 pacing with 0.1 μM ACh shortened APD by 41 ms, hyperpolarized RMP by 7 mV, and increased V _max by 27 mV/ms. In human atrial myocytes, 0.1 μM ACh shortened APD by 48 ms, hyperpolarized RMP by 3 mV, and increased V _max by 6 mV/ms. In LAA monolayer simulations, S1 pacing with ACh hyperpolarized RMP to delay total AT by 32 ms without and 35 ms with fibrosis. This led to unidirectional conduction block and sustained reentry in fibrotic LA with heterogeneous ACh during S2 pacing. In AF patient LAAs, S1 pacing with ACh increased total AT from 39.3 ± 26 ms to 71.4 ± 31.2 ms (p = 0.036) compared to no change without ACh (56.7 ± 29.3 ms to 50.0 ± 21.9 ms, p = 0.140).

Conclusion

In fibrotic atria with heterogeneous parasympathetic activation, ACh facilitates AF by shortening APD and slowing conduction to promote unidirectional conduction block and reentry.

Atrial Fibrosis: Translational Considerations for the Management of AF Patients

Fibrosis plays a fundamental role in the initiation and maintenance of AF, mainly due to enhanced automaticity and anisotropy-related re-entry. The identification and quantification of atrial fibrosis is achieved either preprocedurally by late gadolinium enhancement MRI or intraprocedurally using electroanatomic voltage mapping. The presence and extent of left atrial fibrosis among AF patients may influence relevant decision making regarding the need for anticoagulation, the adoption of rate versus rhythm control and mainly the type of ablation strategy that will be followed during interventional treatment. Several types of individualised substrate modifications targeting atrial fibrotic areas have been proposed, although their impact on patient outcome needs to be further investigated in adequately powered prospective randomised controlled clinical trials.

Atrial contractility and fibrotic biomarkers are associated with atrial fibrillation after elective coronary artery bypass grafting

OBJECTIVE

New-onset postoperative atrial fibrillation is common after cardiac surgery. Less has been reported about the relationship among fibrosis, inflammation, calcium-induced left atrial and right atrial contractile forces, and postoperative atrial fibrillation. We sought to identify predictors of postoperative atrial fibrillation.

METHODS

From August 2016 to February 2018, we evaluated 229 patients who had preoperative sinus rhythm before elective primary coronary artery bypass grafting. Of 229 patients, 191 maintained sinus rhythm postoperatively, whereas 38 patients developed atrial fibrillation. Preoperative tissue inhibitor of metalloproteinase-1, pentraxin-3, matrix metallopeptidase-9, galectin-3, high-sensitivity C-reactive protein, growth differentiation factor 15, and transforming growth factor-ß were measured. Clinical and echocardiographic findings (tricuspid annular plane systolic excursion for right heart function) and calcium-induced force measurements from left atrial and right atrial-derived skinned myocardial fibers were recorded.

RESULTS

Patients with atrial fibrillation were older (P = .001), had enlarged left atrial (P = .0001) and right atrial areas (P = .0001), and had decreased tricuspid annular plane systolic excursion (P = .001). Levels of matrix metallopeptidase-9 and pentraxin-3 were decreased (P < .05), whereas growth differentiation factor 15 was increased (P = .001). We detected lower left atrial force values at calcium-induced force measurements 5.5 (P < .05), 5.4 (P < .01), and 5.3 to 4.52 (P = .0001) and right atrial force values at calcium-induced force measurements 5.0 to 4.52 (P < .05) in patients with postoperative atrial fibrillation. Multivariable analysis showed that advanced age (P = .033), decreased left atrial force value at calcium-induced force measurement of 5.5 (P = .033), enlarged left atrial (P = .013) and right atrial (P = .081) areas, and reduced tricuspid annular plane systolic excursion (P = .010) independently predicted postoperative atrial fibrillation.

CONCLUSIONS

Advanced age, decreased left atrial force value at calcium-induced force measurement of 5.5, enlarged left atrial and right atrial areas, and reduced tricuspid annular plane systolic excursion were identified as independent predictors for postoperative atrial fibrillation.

Iterative navigation of multipole diagnostic catheters to locate repeating-pattern atrial fibrillation drivers

Introduction

Targeting repeating‐pattern atrial fibrillation (AF) sources (reentry or focal drivers) can help in patient‐specific ablation therapy for AF; however, the development of reliable and accurate tools for locating such sources remains a major challenge. We describe iterative catheter navigation (ICAN) algorithm to locate AF drivers using a conventional circular Lasso catheter.

Methods and Results

At each step, the algorithm analyzes 10 bipolar electrograms recoded at a given catheter location and the history of previous catheter movements to determine if the source is inside the catheter loop. If not, it calculates new coordinates and selects a new position for the catheter. The process continues until a source is located. The algorithm was evaluated in a computer model of atrial tissue with various degrees of fibrosis under a broad range of arrhythmia scenarios. The latter included slow and fast reentry, macroreentry, figure‐of‐eight reentry, and fibrillatory conduction. Depending on the initial distance of the catheter from the source and scenario, it took about 3 to 16 steps to localize an AF source. In 94% of cases, the identified location was within 4 mm from the source, independently of the initial position of the catheter. The algorithm worked equally well in the presence of patchy fibrosis, low‐voltage areas, fragmented electrograms, and dominant‐frequency gradients.

Conclusions

AF repeating‐pattern sources can be localized using circular catheters without the need to map the entire tissue. The proposed algorithm has the potential to become a useful tool for patient‐specific ablation of AF sources located outside the pulmonary veins.

Fully Automatic Left Atrium Segmentation From Late Gadolinium Enhanced Magnetic Resonance Imaging Using a Dual Fully Convolutional Neural Network

Atrial fibrillation (AF) is the most prevalent form of cardiac arrhythmia. Current treatments for AF remain suboptimal due to a lack of understanding of the underlying atrial structures that directly sustain AF. Existing approaches for analyzing atrial structures in 3-D, especially from late gadolinium-enhanced (LGE) magnetic resonance imaging, rely heavily on manual segmentation methods that are extremely labor-intensive and prone to errors. As a result, a robust and automated method for analyzing atrial structures in 3-D is of high interest. We have, therefore, developed AtriaNet, a 16-layer convolutional neural network (CNN), on 154 3-D LGE-MRIs with a spatial resolution of 0.625 mm ×0.625 mm ×1.25 mm from patients with AF, to automatically segment the left atrial (LA) epicardium and endocardium. AtriaNet consists of a multi-scaled, dual-pathway architecture that captures both the local atrial tissue geometry and the global positional information of LA using 13 successive convolutions and three further convolutions for merging. By utilizing computationally efficient batch prediction, AtriaNet was able to successfully process each 3-D LGE-MRI within 1 min. Furthermore, benchmarking experiments have shown that AtriaNet has outperformed the state-of-the-art CNNs, with a DICE score of 0.940 and 0.942 for the LA epicardium and endocardium, respectively, and an inter-patient variance of <0.001. The estimated LA diameter and volume computed from the automatic segmentations were accurate to within 1.59 mm and 4.01 cm3 of the ground truths. Our proposed CNN was tested on the largest known data set for LA segmentation, and to the best of our knowledge, it is the most robust approach that has ever been developed for segmenting LGE-MRIs. The increased accuracy of atrial reconstruction and analysis could potentially improve the understanding and treatment of AF.

The effect of complex intramural microstructure caused by structural remodeling on the stability of atrial fibrillation: Insights from a three-dimensional multi-layer modeling study

BACKGROUND

Recent researches have suggested that the complex three-dimensional structures caused by structural remodeling play a key role in atrial fibrillation (AF) substrates. Here we aimed to investigate this hypothesis using a multi-layer model representing intramural microstructural features.

METHODS

The proposed multi-layer model was composed of the endocardium, connection wall, and epicardium. In the connection wall, intramural fibrosis was simulated using fibrotic patches randomly scattered in the myocardial tissue of fibrotic layers, while endo-epicardial dissociation was simulated using myocardial patches randomly scattered in the fibrotic tissue of isolation layers. Multiple simulation groups were generated to quantitatively analyze the effects of endo-epicardial dissociation and intramural fibrosis on AF stability, including a stochastic group, interrelated groups, fibrosis-degree-controlled groups, and dissociation-degree-controlled groups.

RESULTS

1. Stable intramural re-entries were observed to move along complete re-entrant circuits inside the transmural wall in four of 65 simulations in the stochastic group. 2. About 21 of 23 stable simulations in the stochastic group were distributed in the areas with high endo-epicardial dissociation and intramural fibrosis. 3. The difference between fibrosis-degree-controlled groups and dissociation-degree-controlled groups suggested that some distributions of connection areas may affect AF episodes despite low intramural fibrosis and endo-epicardial dissociation. 4. The overview of tracking phase singularities revealed that endo-epicardial dissociation played a visible role in AF substrates.

CONCLUSION

The complex intramural microstructure is positively correlated with critical components of AF maintenance mechanisms. The occurrence of intramural re-entry further indicates the complexity of AF wave-dynamics.

Human Atrial Fibrillation Drivers Resolved With Integrated Functional and Structural Imaging to Benefit Clinical Mapping

OBJECTIVES

This study sought to improve atrial fibrillation (AF) driver identification by integrating clinical multielectrode mapping with driver fingerprints defined by high-resolution ex vivo 3-dimensional (3D) functional and structural imaging.

BACKGROUND

Clinical multielectrode mapping of AF drivers suffers from variable contact, signal processing, and structural complexity within the 3D human atrial wall, raising questions on the validity of such drivers.

METHODS

Sustained AF was mapped in coronary-perfused explanted human hearts (n = 11) with transmural near-infrared optical mapping (∼0.3 mm² resolution). Simultaneously, custom FIRMap catheters (∼9 × 9 mm² resolution) mapped endocardial and epicardial surfaces, which were analyzed by Focal Impulse and Rotor Mapping activation and Rotational Activity Profile (Abbott Labs, Chicago, Illinois). Functional maps were integrated with contrast-enhanced cardiac magnetic resonance imaging (∼0.1 mm³ resolution) analysis of 3D fibrosis architecture.

RESULTS

During sustained AF, near-infrared optical mapping identified 1 to 2 intramural, spatially stable re-entrant AF drivers per heart. Driver targeted ablation affecting 2.2 ± 1.1% of the atrial surface terminated and prevented AF. Driver regions had significantly higher phase singularity density and dominant frequency than neighboring nondriver regions. Focal Impulse and Rotor Mapping had 80% sensitivity to near-infrared optical mapping-defined driver locations (16 of 20), and matched 14 of 20 driver visualizations: 10 of 14 re-entries seen with Rotational Activity Profile; and 4 of 6 breakthrough/focal patterns. Focal Impulse and Rotor Mapping detected 1.1 ± 0.9 false-positive rotational activity profiles per recording, but these regions had lower intramural contrast-enhanced cardiac magnetic resonance imaging fibrosis than did driver regions (14.9 ± 7.9% vs. 23.2 ± 10.5%; p < 0.005).

CONCLUSIONS

The study revealed that both re-entrant and breakthrough/focal AF driver patterns visualized by surface-only clinical multielectrodes can represent projections of 3D intramural microanatomic re-entries. Integration of multielectrode mapping and 3D fibrosis analysis may enhance AF driver detection, thereby improving the efficacy of driver-targeted ablation.

Ionic and cellular mechanisms underlying TBX5/PITX2 insufficiency-induced atrial fibrillation: Insights from mathematical models of human atrial cells

Transcription factors TBX5 and PITX2 involve in the regulation of gene expression of ion channels and are closely associated with atrial fibrillation (AF), the most common cardiac arrhythmia in developed countries. The exact cellular and molecular mechanisms underlying the increased susceptibility to AF in patients with TBX5/PITX2 insufficiency remain unclear. In this study, we have developed and validated a novel human left atrial cellular model (TPA) based on the ten Tusscher-Panfilov ventricular cell model to systematically investigate how electrical remodeling induced by TBX5/PITX2 insufficiency leads to AF. Using our TPA model, we have demonstrated that spontaneous diastolic depolarization observed in atrial myocytes with TBX5-deletion can be explained by altered intracellular calcium handling and suppression of inward-rectifier potassium current (IK1). Additionally, our computer simulation results shed new light on the novel cellular mechanism underlying AF by indicating that the imbalance between suppressed outward current IK1 and increased inward sodium-calcium exchanger current (INCX) resulted from SR calcium leak leads to spontaneous depolarizations. Furthermore, our simulation results suggest that these arrhythmogenic triggers can be potentially suppressed by inhibiting sarcoplasmic reticulum (SR) calcium leak and reversing remodeled IK1. More importantly, this study has clinically significant implications on the drugs used for maintaining SR calcium homeostasis, whereby drugs such as dantrolene may confer significant improvement for the treatment of AF patients with TBX5/PITX2 insufficiency.

Atrial Fibrillation Mechanisms and Implications for Catheter Ablation

AF is a heterogeneous rhythm disorder that is related to a wide spectrum of etiologies and has broad clinical presentations. Mechanisms underlying AF are complex and remain incompletely understood despite extensive research. They associate interactions between triggers, substrate and modulators including ionic and anatomic remodeling, genetic predisposition and neuro-humoral contributors. The pulmonary veins play a key role in the pathogenesis of AF and their isolation is associated to high rates of AF freedom in patients with paroxysmal AF. However, ablation of persistent AF remains less effective, mainly limited by the difficulty to identify the sources sustaining AF. Many theories were advanced to explain the perpetuation of this form of AF, ranging from a single localized focal and reentrant source to diffuse bi-atrial multiple wavelets. Translating these mechanisms to the clinical practice remains challenging and limited by the spatio-temporal resolution of the mapping techniques. AF is driven by focal or reentrant activities that are initially clustered in a relatively limited atrial surface then disseminate everywhere in both atria. Evidence for structural remodeling, mainly represented by atrial fibrosis suggests that reentrant activities using anatomical substrate are the key mechanism sustaining AF. These reentries can be endocardial, epicardial, and intramural which makes them less accessible for mapping and for ablation. Subsequently, early interventions before irreversible remodeling are of major importance. Circumferential pulmonary vein isolation remains the cornerstone of the treatment of AF, regardless of the AF form and of the AF duration. No ablation strategy consistently demonstrated superiority to pulmonary vein isolation in preventing long term recurrences of atrial arrhythmias. Further research that allows accurate identification of the mechanisms underlying AF and efficient ablation should improve the results of PsAF ablation.

Is extensive atrial fibrosis in the setting of heart failure associated with a reduced atrial fibrillation burden?

Atrial fibrillation (AF) affects 10-50% of patients with chronic heart failure (HF) and is associated with poor long-term prognosis. AF is commonly associated with atrial structural remodeling (ASR), principally characterized by atrial dilatation and fibrosis. However, the occurrence of AF in the full spectrum of ASR encountered in patients with HF is poorly defined. Experimental studies have presented evidence that extensive ASR can be accompanied with a reduced burden of AF, secondary to a prominent depression of atrial excitability. This reduction in AF burden is associated with severe atrial fibrosis rather than with dilatation. Clinical studies of patients with HF point to the possibility that advanced ASR is associated with a less frequent AF occurrence than moderate ASR. Our goal in this review is to introduce the hypothesis that AF is less likely to occur in severe versus moderate atrial ASR in the setting of HF and that it is severe atrial fibrosis-associated depression of atrial excitability that reduces AF burden.