Predicting Atrial Fibrillation Recurrence by Combining Population Data and Virtual Cohorts of Patient-Specific Left Atrial Models.

BACKGROUND: Current ablation therapy for atrial fibrillation is suboptimal, and long-term response is challenging to predict. Clinical trials identify bedside properties that provide only modest prediction of long-term response in populations, while patient-specific models in small cohorts primarily explain acute response to ablation. We aimed to predict long-term atrial fibrillation recurrence after ablation in large cohorts, by using machine learning to complement biophysical simulations by encoding more interindividual variability. METHODS: Patient-specific models were constructed for 100 atrial fibrillation patients (43 paroxysmal, 41 persistent, and 16 long-standing persistent), undergoing first ablation. Patients were followed for 1 year using ambulatory ECG monitoring. Each patient-specific biophysical model combined differing fibrosis patterns, fiber orientation maps, electrical properties, and ablation patterns to capture uncertainty in atrial properties and to test the ability of the tissue to sustain fibrillation. These simulation stress tests of different model variants were postprocessed to calculate atrial fibrillation simulation metrics. Machine learning classifiers were trained to predict atrial fibrillation recurrence using features from the patient history, imaging, and atrial fibrillation simulation metrics. RESULTS: We performed 1100 atrial fibrillation ablation simulations across 100 patient-specific models. Models based on simulation stress tests alone showed a maximum accuracy of 0.63 for predicting long-term fibrillation recurrence. Classifiers trained to history, imaging, and simulation stress tests (average 10-fold cross-validation area under the curve, 0.85±0.09; recall, 0.80±0.13; precision, 0.74±0.13) outperformed those trained to history and imaging (area under the curve, 0.66±0.17) or history alone (area under the curve, 0.61±0.14). CONCLUSION: A novel computational pipeline accurately predicted long-term atrial fibrillation recurrence in individual patients by combining outcome data with patient-specific acute simulation response. This technique could help to personalize selection for atrial fibrillation ablation

Doctor of Philosophy

dissertationFibrillation is defined as turbulent cardiac electrical activity and results in the inability of the myocardium to contract. When fibrillation occurs in the ventricles, it is known as ventricular fibrillation (VF). The consequence of VF is sudden death unless treated immediately. Fibrillation can also occur in the atria and is known as atrial fibrillation (AF). The consequences of atrial fibrillation (AF) are less immediate; however, it leads to increased risk of stroke. Despite the impact of fibrillatory arrhythmias, there are many gaps in our mechanistic knowledge of these arrhythmias. The purpose of this dissertation is to study through several projects how different cardiac substrates help initiate and/or sustain fibrillation. The first project examined several properties of the ventricular conduction system during VF. The conduction system coordinates excitation and consequently coordinates the contraction of the ventricles. Despite the conduction system's unique structure, its role in VF remains unclear. We examined the proximal conduction system and found that it develops a more rapid activation rate than the ventricular myocardium during prolonged VF, and may be driving the arrhythmia. The second and third projects examined the effects of fibrosis on electrical conduction to initiate and/or sustain AF. Despite fibrosis being associated with AF, it is still unknown whether it is a byproduct of an underlying heart disease and does not in itself promote AF, or if it affects the organization of conduction during fibrillation to promote AF. In the second project we studied the effect of fibrosis on conduction following different types of triggers. We found that fibrosis causes transverse conduction slowing following premature stimulation, which makes AF more likely to initiate. As AF persists, single episodes of AF last longer before the patient transitions into normal sinus rhythm, and in some cases AF can become permanent. The third project examined why some patients may never transition from AF to normal sinus rhythm. Specifically, this project found that regions of dense fibrosis anchor high-frequency activation that may be driving the arrhythmia. These studies showed that fibrosis causes conduction changes that make AF more likely to initiate and to be sustained

Challenges associated with interpreting mechanisms of AF

Determining optimal treatment strategies for complex arrhythmogenesis in AF is confounded by the lack of consensus regarding the mechanisms causing AF. Studies report different mechanisms for AF, ranging from hierarchical drivers to anarchical multiple activation wavelets. Differences in the assessment of AF mechanisms are likely due to AF being recorded across diverse models using different investigational tools, spatial scales and clinical populations. The authors review different AF mechanisms, including anatomical and functional re-entry, hierarchical drivers and anarchical multiple wavelets. They then describe different cardiac mapping techniques and analysis tools, including activation mapping, phase mapping and fibrosis identification. They explain and review different data challenges, including differences between recording devices in spatial and temporal resolutions, spatial coverage and recording surface, and report clinical outcomes using different data modalities. They suggest future research directions for investigating the mechanisms underlying human AF

Effects of Electrical and Structural Remodeling on Atrial Fibrillation Maintenance: A Simulation Study

Atrial fibrillation, a common cardiac arrhythmia, often progresses unfavourably: in patients with long-term atrial fibrillation, fibrillatory episodes are typically of increased duration and frequency of occurrence relative to healthy controls. This is due to electrical, structural, and contractile remodeling processes. We investigated mechanisms of how electrical and structural remodeling contribute to perpetuation of simulated atrial fibrillation, using a mathematical model of the human atrial action potential incorporated into an anatomically realistic three-dimensional structural model of the human atria. Electrical and structural remodeling both shortened the atrial wavelength - electrical remodeling primarily through a decrease in action potential duration, while structural remodeling primarily slowed conduction. The decrease in wavelength correlates with an increase in the average duration of atrial fibrillation/flutter episodes. The dependence of reentry duration on wavelength was the same for electrical vs. structural remodeling. However, the dynamics during atrial reentry varied between electrical, structural, and combined electrical and structural remodeling in several ways, including: (i) with structural remodeling there were more occurrences of fragmented wavefronts and hence more filaments than during electrical remodeling; (ii) dominant waves anchored around different anatomical obstacles in electrical vs. structural remodeling; (iii) dominant waves were often not anchored in combined electrical and structural remodeling. We conclude that, in simulated atrial fibrillation, the wavelength dependence of reentry duration is similar for electrical and structural remodeling, despite major differences in overall dynamics, including maximal number of filaments, wave fragmentation, restitution properties, and whether dominant waves are anchored to anatomical obstacles or spiralling freely

Multi-Modality Correspondence to Enhance Arrhythmogenic Atrial Substrate Identification: Guiding Persistent Atrial Fibrillation Ablation Therapy

Vorhofflimmern ist eines der häufigsten Gesundheitsprobleme und stellt nicht nur für Patienten, sondern auch für die Gesundheitssysteme eine erhebliche Belastung dar. Während die Pulmonalvenenisolation eine wirksame Therapie für paroxysmale Patienten mit Vorhofflimmern darstellt, sinkt die Erfolgsquote bei Patienten mit persistierendem Vorhofflimmern. Man nimmt an, dass dies auf strukturelle Veränderungen in den Vorhöfen zurückzuführen ist, die während des Fortschreitens des Vorhofflimmerns auftreten. Daher weisen Patienten mit persistierendem Vorhofflimmern ein zusätzliches pathologisches Substrat in den Vorhöfen auf, das die Arrhythmie aufrechterhält. Leider sind die derzeitigen Ansätze, bei denen Pulmonalvenenisolation und zusätzlich das pathologische Substrat angegangen werden, immer noch suboptimal, denn nur 50-70\% der Patienten sind nach der Katheterablation dauerhaft frei von Vorhofflimmern. Daher bleibt die optimale Ablationsstrategie eine offene Frage, die weitere Forschung erfordert, um vielversprechende Ablationsziele zu identifizieren. Zwei Ansätze, die in den letzten Jahren an Aufmerksamkeit gewonnen haben, sind die elektroanatomische Kartierung, die speziell auf Bereiche mit niedriger Spannung abzielt, und die Gadolinium-verstärkte Magnetresonanztomographie (LGE-MRI). Beide werden jedoch dadurch behindert, dass es keinen Konsens über eine präzise Methode zur Identifizierung des pathologischen Substrats gibt. Die eindeutige Identifizierung mittels Low Voltage Mapping wird erschwert, da die Auswirkungen von Kathetereigenschaften, die die Spannung neben dem pathologischen Substrat beeinflussen, nicht bekannt sind. Außerdem kann das Spannungsmapping während des Sinusrhythmus oder des Vorhofflimmerns durchgeführt werden. Im letzteren Fall ist das Mapping von Vorteil, da es den Bedarf an potenziell mehrfachen Kardioversionen reduziert. Es gibt jedoch keine genaue statistische Auswertung der Grenzwerte, die zur Bestimmung von Bereichen mit niedriger Spannung angewendet werden sollten. Der Vorteil der LGE-MRI ist, dass es sich um eine weniger invasive Diagnosemethode handelt. Allerdings ist die räumliche Auflösung der LGE-MRI begrenzt. Darüber hinaus ist der Grad der Übereinstimmung zwischen MRI und Spannungsmapping zum Nachweis von Fibrose umstritten. Diese Arbeit ist in drei Projekte unterteilt, deren übergeordnetes Ziel es ist, die Kartierungs-modalitäten zu vergleichen, um die oben genannten Einschränkungen zu beseitigen. Dadurch sollen robustere und genauere Methoden zur Identifizierung pathologischer Substratbereiche bereitgestellt werden, die für die Aufrechterhaltung von Vorhofflimmern bekannt sind. Im ersten Projekt wurden 28 Patienten mit persistierendem Vorhofflimmern untersucht, die sich einer elektro-anatomischen Kartierung unterzogen. Anschließend wurden die bipolaren und unipolaren Spannungskarten der einzelnen Patienten statistisch verglichen. Insbesondere wurde das Ausmaß der Übereinstimmung zwischen den Methoden ermittelt, um die optimalen unipolaren Schwellenwerte für die Lokalisierung des pathologischen Substrats zu finden, wie sie durch die bipolare Spannungskarte bestimmt wurden. Darüber hinaus wurde untersucht, wie sich die Abstände zwischen den Elektroden und anatomisch regionale Unterschiede auf die Vergleichbarkeit auswirken. Im zweiten Teil des Projekts wurden Simulationen durchgeführt, bei denen Elektroden unterschiedlicher Größe auf einem 2D-Patch und ein Lasso-Katheter in einer 3D-Geometrie des linken Vorhofs modelliert wurden. Dabei stellte sich heraus, dass die Kathetereigenschaften zwar die bipolaren Spannungswerte beeinflussen, aber keine wesentliche Rolle bei der Veränderung der Lage der "Low Voltage"-Bereiche spielen. Anhand der ermittelten unipolaren Schwellenwerte, die die bipolare und unipolare Karte miteinander in Beziehung setzen, lässt sich das Ausmaß des pathologischen Substrats in einem Bereich bestimmen. Darüber hinaus wurde festgestellt, dass größere Elektroden geringere Spannungen liefern, was den Vergleich der Ergebnisse verschiedener Studien und Zentren ermöglicht. Im zweiten Projekt wurde eine Patientenkohorte verwendet, bei der Patienten mit SR und Vorhofflimmern elektro-anatomisch kartiert wurden. Die beiden Rhythmen konnten dann bei jedem Patienten verglichen werden, und es konnten globale und regionale Schwellenwerte für die Spannung in Bezug auf die Rhythmen ermittelt werden. Darüber hinaus konnten die Auswirkungen der Induktion von Vorhofflimmern bei Patienten untersucht und die Vorteile verschiedener Methoden zur Spannungsberechnung analysiert werden. Es wurden Schwellenwerte für die Spannung vorgeschlagen, die das Mapping bei Vorhofflimmern mit SR besser in Beziehung setzen können. Es wurde festgestellt, dass die Verwendung der in dieser Arbeit vorgeschlagenen regionalen Schwellenwerte dazu beitragen könnte, eine falsche Darstellung des Ausmaßes des pathologischen Substrats in einem Gebiet zu vermeiden. Darüber hinaus führt die Verwendung des maximalen Spannungswerts in einem Signal zu einer höheren Konkordanz zwischen den Methoden, und die Verwendung eines Variabilitätsmaßes (Entropie) kann helfen, komplexe Ausbreitungsmuster zu erkennen, die die Signale bei Vorhofflimmern verzerren. Das letzte Projekt schließlich untersuchte 36 Patienten, bei denen sowohl LGE-MRI als auch elektro-anatomisches Mapping durchgeführt wurde. Anhand dieser Kohorte konnte die Übereinstimmung zwischen verschiedenen LGE-MRI-Kartierungsmodalitäten und der Spannungs- und Leitungsgeschwindigkeitskartierung untersucht werden. Darüber hinaus konnte eine neue LGE-MRI-Methode zur Verbesserung der Übereinstimmung zwischen den Modalitäten entwickelt werden. In dieser Arbeit wurden räumliche Histogramme erstellt, die typische Regionen mit niedriger Spannung und langsamer Leitung zeigen, um Klinikärzten zu helfen, wichtige Regionen zu identifizieren, die während eines Eingriffs erfasst und abgebildet werden müssen. Darüber hinaus wurden erhebliche Diskrepanzen zwischen den Methoden festgestellt, insbesondere an der Hinterwand, was weitere Untersuchungen erfordert. Schließlich wurde eine neue LGE-MRI-Schwellenwertmethode entwickelt, die zur Identifizierung von Patienten mit atrialer Kardiomyopathie eingesetzt werden könnte. Damit kann auf nicht-invasive Weise festgestellt werden, ob bei Patienten neben der PVI ein zusätzliches Mapping erforderlich ist. Die in dieser Arbeit vorgestellten Ergebnisse vermittelten der klinischen Gemeinschaft ein tieferes Verständnis dafür, wie die verschiedenen Methoden zur Identifizierung von pathologischem Substrat miteinander verglichen werden können. Darüber hinaus werden Techniken zur Verfügung gestellt, um die Methoden miteinander in Beziehung zu setzen, die Variabilität zwischen den Kliniken zu berücksichtigen und die Verfahrensdauer potenziell zu verkürzen. Die Übereinstimmung zwischen den Kartierungsmodalitäten war von Patient zu Patient unterschiedlich, was darauf hindeutet, dass es nicht nur eine einzige Ablationsstrategie für alle gibt. Daher unterstützt diese Arbeit die Umsetzung von stärker personalisierten Ablationsansätzen

Wavelength and Fibrosis Affect Phase Singularity Locations During Atrial Fibrillation

The mechanisms underlying atrial fibrillation (AF), the most common sustained cardiac rhythm disturbance, remain elusive. Atrial fibrosis plays an important role in the development of AF and rotor dynamics. Both electrical wavelength (WL) and the degree of atrial fibrosis change as AF progresses. However, their combined effect on rotor core location remains unknown. The aim of this study was to analyze the effects of WL change on rotor core location in both fibrotic and non-fibrotic atria. Three patient specific fibrosis distributions (total fibrosis content: 16.6, 22.8, and 19.2%) obtained from clinical imaging data of persistent AF patients were incorporated in a bilayer atrial computational model. Fibrotic effects were modeled as myocyte-fibroblast coupling + conductivity remodeling; structural remodeling; ionic current changes + conductivity remodeling; and combinations of these methods. To change WL, action potential duration (APD) was varied from 120 to 240ms, representing the range of clinically observed AF cycle length, by modifying the inward rectifier potassium current (IK1) conductance between 80 and 140% of the original value. Phase singularities (PSs) were computed to identify rotor core locations. Our results show that IK1 conductance variation resulted in a decrease of APD and WL across the atria. For large WL in the absence of fibrosis, PSs anchored to regions with high APD gradient at the center of the left atrium (LA) anterior wall and near the junctions of the inferior pulmonary veins (PVs) with the LA. Decreasing the WL induced more PSs, whose distribution became less clustered. With fibrosis, PS locations depended on the fibrosis distribution and the fibrosis implementation method. The proportion of PSs in fibrotic areas and along the borders varied with both WL and fibrosis modeling method: for patient one, this was 4.2–14.9% as IK1 varied for the structural remodeling representation, but 12.3–88.4% using the combination of structural remodeling with myocyte-fibroblast coupling. The degree and distribution of fibrosis and the choice of implementation technique had a larger effect on PS locations than the WL variation. Thus, distinguishing the fibrotic mechanisms present in a patient is important for interpreting clinical fibrosis maps to create personalized models

Detection of focal source and arrhythmogenic substrate from body surface potentials to guide atrial fibrillation ablation

Focal sources (FS) are believed to be important triggers and a perpetuation mechanism for paroxysmal atrial fibrillation (AF). Detecting FS and determining AF sustainability in atrial tissue can help guide ablation targeting. We hypothesized that sustained rotors during FS-driven episodes indicate an arrhythmogenic substrate for sustained AF, and that non-invasive electrical recordings, like electrocardiograms (ECGs) or body surface potential maps (BSPMs), could be used to detect FS and AF sustainability. Computer simulations were performed on five bi-atrial geometries. FS were induced by pacing at cycle lengths of 120–270 ms from 32 atrial sites and four pulmonary veins. Self-sustained reentrant activities were also initiated around the same 32 atrial sites with inexcitable cores of radii of 0, 0.5 and 1 cm. FS fired for two seconds and then AF inducibility was tested by whether activation was sustained for another second. ECGs and BSPMs were simulated. Equivalent atrial sources were extracted using second-order blind source separation, and their cycle length, periodicity and contribution, were used as features for random forest classifiers. Longer rotor duration during FS-driven episodes indicates higher AF inducibility (area under ROC curve = 0.83). Our method had accuracy of 90.6±1.0% and 90.6±0.6% in detecting FS presence, and 93.1±0.6% and 94.2±1.2% in identifying AF sustainability, and 80.0±6.6% and 61.0±5.2% in determining the atrium of the focal site, from BSPMs and ECGs of five atria. The detection of FS presence and AF sustainability were insensitive to vest placement (±9.6%). On pre-operative BSPMs of 52 paroxysmal AF patients, patients classified with initiator-type FS on a single atrium resulted in improved two-to-three-year AF-free likelihoods (p-value < 0.01, logrank tests). Detection of FS and arrhythmogenic substrate can be performed from ECGs and BSPMs, enabling non-invasive mapping towards mechanism-targeted AF treatment, and malignant ectopic beat detection with likely AF progression

Automated algorithm-driven methods of localising drivers of persistent atrial fibrillation using atrial fibrillation cycle length and atrial fibrillation voltage

The assessment of atrial fibrillation cycle length has played a role in the development of atrial fibrillation ablation by pulmonary vein isolation (PVI) and has also been used to assess response to ablation. Areas of rapid rotational activity in the left atrium have been implied to act as drivers of persistent atrial fibrillation and several methods have been developed to identify these potential drivers. Unprocessed atrial fibrillation electrograms show large variation in cycle length and signal amplitude. Current methods of localising driver regions rely on complex pattern recognition and subjective assessment of operators. The main hypotheses of this thesis were as follows: 1) a technique can be developed to ascertain a clinically relevant, dominant cycle length for any AF segment, 2) the automated technique, can be used to map rapid and regular activity in the left atrium, 3) a patient-tailored definition of rapid activity and low AF voltage, calculated based on patient-specific parameters is feasible; 4) paired with automated low voltage substrate analysis, dominant cycle length analysis is able to provide a framework for localising drivers of AF that is objective, transparent and requires no complex pattern recognition of subjective judgement. To test the hypotheses, a technique was developed based on manual annotation of real-world AF electrograms that was able to ascertain cycle length independent of missing segments or variable cycle length or signal amplitude. Following this, an automated algorithm was validated to determine dominant cycle length. In the following chapter, the nature of AF cycle length was investigated by investigating the patterns of rapid activity with extended AF segments and the concept of patient-tailored definitions of rapid activity was introduced. In the subsequent analysis, the effect of PVI was examined on AF voltage and the AF cycle length, focusing on rapid and regular areas and low voltage zones, and their changes. The last chapter utilised the accumulated information to test the sensitivity and specificity of a percentile-based, patient-tailored approach to low AF voltage and to present an objective, automated method of localising rapid and regular areas within low voltage zones within the left atrium. In summary, it is feasible to assess and locate rapid and regular areas, and localise low voltage zones in persistent AF with a completely automated algorithm, and patient-tailored definitions of low voltage rapid AF activity are a preferable alternative to absolute cut offs.Open Acces