Multiscale Cohort Modeling of Atrial Electrophysiology : Risk Stratification for Atrial Fibrillation through Machine Learning on Electrocardiograms

Patienten mit Vorhofflimmern sind einem fünffach erhöhten Risiko für einen ischämischen Schlaganfall ausgesetzt. Eine frühzeitige Erkennung und Diagnose der Arrhythmie würde ein rechtzeitiges Eingreifen ermöglichen, um möglicherweise auftretende Begleiterkrankungen zu verhindern. Eine Vergrößerung des linken Vorhofs sowie fibrotisches Vorhofgewebe sind Risikomarker für Vorhofflimmern, da sie die notwendigen Voraussetzungen für die Aufrechterhaltung der chaotischen elektrischen Depolarisation im Vorhof erfüllen. Mithilfe von Techniken des maschinellen Lernens könnten Fibrose und eine Vergrößerung des linken Vorhofs basierend auf P Wellen des 12-Kanal Elektrokardiogramms im Sinusrhythmus automatisiert identifiziert werden. Dies könnte die Basis für eine nicht-invasive Risikostrat- ifizierung neu auftretender Vorhofflimmerepisoden bilden, um anfällige Patienten für ein präventives Screening auszuwählen. Zu diesem Zweck wurde untersucht, ob simulierte Vorhof-Elektrokardiogrammdaten, die dem klinischen Trainingssatz eines maschinellen Lernmodells hinzugefügt wurden, zu einer verbesserten Klassifizierung der oben genannten Krankheiten bei klinischen Daten beitra- gen könnten. Zwei virtuelle Kohorten, die durch anatomische und funktionelle Variabilität gekennzeichnet sind, wurden generiert und dienten als Grundlage für die Simulation großer P Wellen-Datensätze mit genau bestimmbaren Annotationen der zugrunde liegenden Patholo- gie. Auf diese Weise erfüllen die simulierten Daten die notwendigen Voraussetzungen für die Entwicklung eines Algorithmus für maschinelles Lernen, was sie von klinischen Daten unterscheidet, die normalerweise nicht in großer Zahl und in gleichmäßig verteilten Klassen vorliegen und deren Annotationen möglicherweise durch unzureichende Expertenannotierung beeinträchtigt sind. Für die Schätzung des Volumenanteils von linksatrialem fibrotischen Gewebe wurde ein merkmalsbasiertes neuronales Netz entwickelt. Im Vergleich zum Training des Modells mit nur klinischen Daten, führte das Training mit einem hybriden Datensatz zu einer Reduzierung des Fehlers von durchschnittlich 17,5 % fibrotischem Volumen auf 16,5 %, ausgewertet auf einem rein klinischen Testsatz. Ein Long Short-Term Memory Netzwerk, das für die Unterscheidung zwischen gesunden und P Wellen von vergrößerten linken Vorhöfen entwickelt wurde, lieferte eine Genauigkeit von 0,95 wenn es auf einem hybriden Datensatz trainiert wurde, von 0,91 wenn es nur auf klinischen Daten trainiert wurde, die alle mit 100 % Sicherheit annotiert wurden, und von 0,83 wenn es auf einem klinischen Datensatz trainiert wurde, der alle Signale unabhängig von der Sicherheit der Expertenannotation enthielt. In Anbetracht der Ergebnisse dieser Arbeit können Elektrokardiogrammdaten, die aus elektrophysiologischer Modellierung und Simulationen an virtuellen Patientenkohorten resul- tieren und relevante Variabilitätsaspekte abdecken, die mit realen Beobachtungen übereinstim- men, eine wertvolle Datenquelle zur Verbesserung der automatisierten Risikostratifizierung von Vorhofflimmern sein. Auf diese Weise kann den Nachteilen klinischer Datensätze für die Entwicklung von Modellen des maschinellen Lernens entgegengewirkt werden. Dies trägt letztendlich zu einer frühzeitigen Erkennung der Arrhythmie bei, was eine rechtzeitige Auswahl geeigneter Behandlungsstrategien ermöglicht und somit das Schlaganfallrisiko der betroffenen Patienten verringert

Direct evidence for microdomain-specific localization and remodeling of functional L-type calcium channels in rat and human atrial myocytes

Background—Distinct subpopulations of L-type calcium channels (LTCCs) with different functional properties exist in cardiomyocytes. Disruption of cellular structure may affect LTCC in a microdomain-specific manner and contribute to the pathophysiology of cardiac diseases, especially in cells lacking organized transverse tubules (T-tubules) such as atrial myocytes (AMs). Methods and Results—Isolated rat and human AMs were characterized by scanning ion conductance, confocal, and electron microscopy. Half of AMs possessed T-tubules and structured topography, proportional to cell width. A bigger proportion of myocytes in the left atrium had organized T-tubules and topography than in the right atrium. Super-resolution scanning patch clamp showed that LTCCs distribute equally in T-tubules and crest areas of the sarcolemma, whereas, in ventricular myocytes, LTCCs primarily cluster in T-tubules. Rat, but not human, T-tubule LTCCs had open probability similar to crest LTCCs, but exhibited ≈40% greater current. Optical mapping of Ca2+ transients revealed that rat AMs presented ≈3-fold as many spontaneous Ca2+ release events as ventricular myocytes. Occurrence of crest LTCCs and spontaneous Ca2+ transients were eliminated by either a caveolae-targeted LTCC antagonist or disrupting caveolae with methyl-β-cyclodextrin, with an associated ≈30% whole-cell ICa,L reduction. Heart failure (16 weeks post–myocardial infarction) in rats resulted in a T-tubule degradation (by ≈40%) and significant elevation of spontaneous Ca2+ release events. Although heart failure did not affect LTCC occurrence, it led to ≈25% decrease in T-tubule LTCC amplitude. Conclusions—We provide the first direct evidence for the existence of 2 distinct subpopulations of functional LTCCs in rat and human AMs, with their biophysical properties modulated in heart failure in a microdomain-specific manner

Allele-specific NKX2-5 binding underlies multiple genetic associations with human electrocardiographic traits.

The cardiac transcription factor (TF) gene NKX2-5 has been associated with electrocardiographic (EKG) traits through genome-wide association studies (GWASs), but the extent to which differential binding of NKX2-5 at common regulatory variants contributes to these traits has not yet been studied. We analyzed transcriptomic and epigenomic data from induced pluripotent stem cell-derived cardiomyocytes from seven related individuals, and identified ~2,000 single-nucleotide variants associated with allele-specific effects (ASE-SNVs) on NKX2-5 binding. NKX2-5 ASE-SNVs were enriched for altered TF motifs, for heart-specific expression quantitative trait loci and for EKG GWAS signals. Using fine-mapping combined with epigenomic data from induced pluripotent stem cell-derived cardiomyocytes, we prioritized candidate causal variants for EKG traits, many of which were NKX2-5 ASE-SNVs. Experimentally characterizing two NKX2-5 ASE-SNVs (rs3807989 and rs590041) showed that they modulate the expression of target genes via differential protein binding in cardiac cells, indicating that they are functional variants underlying EKG GWAS signals. Our results show that differential NKX2-5 binding at numerous regulatory variants across the genome contributes to EKG phenotypes

Microdomain\u2013specific localization of functional L-type calcium channels in atrial cardiomyocytes: novel concept of local regulation and remodelling in disease

noRecently, novel concept of microdomain-specific regulation in cardiac cells have greatly extended our understanding of how specific subcellular localization impacts on channel function and regulation. Microdomain is a small region of cell membrane, which has a distinct structure, composition and function. It has been recognized that discrete clusters of different ion channels exist in the sarcolemma in different microdomains such as T-tubules, caveolae. This study addresses the hypothesis that distinct spatial compartmentalization of functional calcium channels in different intercellular microdomains are coupled with structural proteins and receptors and play an important role in unique Ca2+ signaling in atrial cardiomyocytes in health and pathology. Using several technical approaches (super-resolution scanning and whole-cell patch-clamp, confocal and electron microscopy), this study aims to investigate characteristics of subcellular micrdomains such as T-tubules and caveolae in atrial cardiomyocytes; and to answer the question whether in atrial cardiomyocytes functional L-type calcium channels (LTCCs) are specifically distributed within different microdomains and forming signalling complexes with receptors, that potentially causes a unique atrial cardiomyocyte Ca2+ signaling process. First, it was found that atrial cells could be characterised by heterogeneous T-tubule system the structure of which influenced by the cell size and atrial chamber localization. This study provides the first direct evidence for two distinct subpopulations of functional LTCCs in rat and human healthy atrial cardiomyocytes, with a micro-domain-specific regulation of their biophysical properties. In atrial cells, L-type calcium channels are equally distributed inside and outside of T-tubules, in contrast to ventricular cardiomyocytes where LTCCs are clustered in T-tubules (Bhargava, Lin et al. 2013). The population of LTCCs observed outside of T-tubules was associated with caveolae. LTCCs located in caveolae contribute essentially to atrial Ca2+ signaling, particularly in cardiomyocytes lacking the organized T-tubule network. Second, \u3b21-adreneric stimulation, which increases single LTCC activity and antiadrenergic effect of adenosine on functional LTCCs were investigated in both microdomains in rat atrial cariomyocytes. Third, using animal model, heart failure was found to be associated with loss of T-tubule structure and decrease in single amplitude of T-tubular LTCCs localized in atrial cardiomyocytes. Fourth, human studies revealed, that chronic atrial fibrillation is associated with the loss of T-tubule structure and downregulation of the L-type calcium current with increased activity of single LTCCs localized in T-tubule microdomains and the loss channels outside of T-tubules. Decrease of calcium current was associated with the downregulation of gene expression. These results support the notion that functional L-type calcium channels are linked with structural components of cardiac membrane and undergo remodelling in association with loss of structures during pathology

Complexity of Atrial Fibrillation Electrograms Through Nonlinear Signal Analysis: In Silico Approach

Identification of atrial fibrillation (AF) mechanisms could improve the rate of ablation success. However, the incomplete understanding of those mechanisms makes difficult the decision of targeting sites for ablation. This work is focused on the importance of EGM analysis for detecting and modulating rotors to guide ablation procedures and improve its outcomes. Virtual atrial models are used to show how nonlinear measures can be used to generate electroanatomical maps to detect critical sites in AF. A description of the atrial cell mathematical models, and the procedure of coupling them within two‐dimensional and three‐dimensional virtual atrial models in order to simulate arrhythmogenic mechanisms, is given. Mathematical modeling of unipolar and bipolar electrogramas (EGM) is introduced. It follows a discussion of EGM signal processing. Nonlinear descriptors, such as approximate entropy and multifractal analysis, are used to study the dynamical behavior of EGM signals, which are not well described by a linear law. Our results evince that nonlinear analysis of EGM can provide information about the dynamics of rotors and other mechanisms of AF. Furthermore, these fibrillatory patterns can be simulated using virtual models. The combination of features using machine learning tools can be used for identifying arrhythmogenic sources of AF

Fully automatic segmentation and objective assessment of atrial scars for longstanding persistent atrial fibrillation patients using late gadolinium-enhanced MRI

Purpose: Atrial fibrillation (AF) is the most common heart rhythm disorder and causes considerable morbidity and mortality, resulting in a large public health burden that is increasing as the population ages. It is associated with atrial fibrosis, the amount and distribution of which can be used to stratify patients and to guide subsequent electrophysiology ablation treatment. Atrial fibrosis may be assessed non-invasively using late gadolinium-enhanced (LGE) magnetic resonance imaging (MRI) where scar tissue is visualised as a region of signal enhancement. However, manual segmentation of the heart chambers and of the atrial scar tissue is time-consuming and subject to inter-operator variability, particularly as image quality in AF is often poor. In this study, we propose a novel fully automatic pipeline to achieve accurate and objective segmentation of the heart (from MRI Roadmap data) and of scar tissue within the heart (from LGE MRI data) acquired in patients with AF. Methods: Our fully automatic pipeline uniquely combines: (1) a multi-atlas based whole heart segmentation (MA-WHS) to determine the cardiac anatomy from an MRI Roadmap acquisition which is then mapped to LGE MRI, and (2) a super-pixel and supervised learning based approach to delineate the distribution and extent of atrial scarring in LGE MRI. We compared the accuracy of the automatic analysis to manual ground-truth segmentations in 37 patients with persistent long standing AF. Results: Both our MA-WHS and atrial scarring segmentations showed accurate delineations of cardiac anatomy (mean Dice = 89%) and atrial scarring (mean Dice = 79%) respectively compared to the established ground truth from manual segmentation. In addition, compared to the ground truth, we obtained 88% segmentation accuracy, with 90% sensitivity and 79% specificity. Receiver operating characteristic analysis achieved an average area under the curve of 0.91. Conclusion: Compared with previously studied methods with manual interventions, our innovative pipeline demonstrated comparable results, but was computed fully automatically. The proposed segmentation methods allow LGE MRI to be used as an objective assessment tool for localisation, visualisation and quantification of atrial scarring and to guide ablation treatment

The contact electrogram and its architectural determinants in atrial fibrillation

The electrogram is the sine qua non of excitable tissues, yet classification in atrial fibrillation (AF) remains poorly related to substrate factors. The objective of this thesis was to establish the relationship between electrograms and two commonly implicated substrate factors, connexin 43 and fibrosis in AF. The substrates and methods chosen to achieve this ranged from human acutely induced AF using open chest surgical mapping (Chapter 6), ex vivo whole heart Langendorff (Chapter 7) with in vivo telemetry confirming spontaneous AF in a new species of rat, the Brown Norway and finally isolated atrial preparations from an older cohort of rats using orthogonal pacing and novel co-localisation methods at sub-millimetre resolution and in some atria, optical mapping (Chapter 8). In rodents, electrode size and spacing was varied (Chapters 5, 10) to study its effects on structure function correlations (Chapter 9). Novel indices of AF organisation and automated electrogram morphology were used to quantify function (Chapter 4). Key results include the discoveries that humans without any history of prior AF have sinus rhythm electrograms with high spectral frequency content, that wavefront propagation velocities correlated with fibrosis and connexin phosphorylation ratios, that AF heterogeneity of conduction correlates to fibrosis and that orthogonal pacing in heavily fibrosed atria causes anisotropy in electrogram-fibrosis correlations. Furthermore, fibrosis and connexin 43 have differing and distinct spatial resolutions in their relationship with AF organisational indices. In conclusion a new model of AF has been found, and structure function correlations shown on an unprecedented scale, but with caveats of electrode size and direction dependence. These findings impact structure function methods and prove the effect of substrate on AF organisation.Open Acces

The ganglionated plexus: The upstream triggers of atrial fibrillation

The ganglionated plexuses (GP) are dense epicardial nerves that are implicated in atrial fibrillation (AF). They can be functionally located from the endocardium using high frequency stimulation (HFS) which can locate distinct GP that trigger atrial ectopy/AF (ET-GP) or atrioventricular (AV) dissociating (AVD-GP). Our aim was to map and understand the histological, anatomical and functional properties of the different types of GP and ablate them with or without pulmonary vein isolation (PVI) in patients with AF. We hypothesised that ablating these specific GP sites is feasible, and prevents AF. Firstly, to investigate this, we mapped for AVD-GP and ET-GP using HFS in the left atrium of patients with AF. An automated process was used to merge and transform all patient maps onto one reference left atrial shell. A probability density function was applied at each tested site, including GP and negative HFS response sites, to create a probability distribution atlas of AVD-GP and ET-GP. There were distinct anatomical regions according to each GP sub-type, and ET-GP had preponderance to the PV ostia, roof, and mid-anterior wall. These are the areas that would usually be targeted with circumferential PVI. Therefore, a prospective, randomised, controlled study was performed (GANGLIA-AF) which assessed ET-GP ablation without PVI and PVI alone in patients with paroxysmal AF. Patients were followed-up for 12 months with multiple 48hr Holter monitors. The primary endpoint was any documented atrial arrhythmia >30s, and the secondary endpoints included complications and redo ablations. This showed that there was no statistically significant difference in AF prevention between the two arms, however the GP ablation arm required less ablation on average than the PVI arm. We also performed a smaller pilot study of redo AF ablation patients, assessing for feasibility and safety of GP ablation in addition to redo PVI. The same follow-up and endpoint criteria were used as in the GANGLIA-AF study. Some patients had permanent PVI, and non-PV triggers of AF were identifiable with HFS. We also developed a custom-built high frequency stimulator (Tau-20) that was used to identify ectopy-triggering (ET) sites in Langendorff-perfused porcine hearts. We were able to replicate the HFS responses used in the clinical setting in the porcine atria. Transmural cross-sectional dissections were taken from ET and non-ET sites, and the tissues were stained for parasympathetic and sympathetic nerves using immunohistochemistry methods. This showed that the mean density of nerves was greater in ET sites compare to non-ET sites. The Tau-20 has been successfully trialled in humans in the clinical setting, and with further improvements, it may replace the old Grass S88 stimulator for future GP ablation cases. In conclusion, ET-GP are upstream triggers of AF that can be ablated without PVI to prevent paroxysmal AF. GP ablation can be achieved with less RF energy than PVI implying a more specific technique on mechanistic grounds. The cross-over rate and clinical outcomes for GP ablation needs further improvement but GANGLIA-AF provides evidence that GP ablation may be an alternative or an adjunct technique to PVI. In addition, our ex-vivo evidence of increased nerve density at ET sites may account for the differential functional response of ET-GP stimulation in the clinical setting.Open Acces