High-Density Mapping Analysis of Electrical Spatiotemporal Behaviour in Atrial Fibrillation

Tese de mestrado integrado, Engenharia Biomédica e Biofísica (Sinais e Imagens Médicas), 2022, Universidade de Lisboa, Faculdade de CiênciasDoenças cardiovasculares, tais como arritmias, são a principal causa de morte no mundo, especialmente no Sul e no Este da Ásia, e nos Estados Unidos da América [1]. As arritmas são caracterizadas pela alteração no ritmo sinusal normal do coração. Em particular, a fibrilhação auricular (FA) é a arritmia cardíaca mais comum na prática clínica, contribuindo para mais de 200 mil mortes globalmente em 2017 [2]. Caracteriza-se pela contração rápida e dessincronizada das aurículas, e está associada ao aumento da mortalidade e afecta de forma negativa a qualidade de vida dos pacientes. A FA é geralmente tratada através de medicação, porém quando esta falha, a ablação por cateter é indicada, sendo um tratamento de referência para combater esta patologia. A ablação apresenta uma taxa de sucesso de aproximadamente 50% no primeiro procedimento, sendo necessário efectuar vários procedimentos para aumentar a eficácia do tratamento [3]. A detecção desta patologia envolve, numa primeira fase, a realização de um electrocardiograma (ECG) e, posteriormente um estudo electrofisiológico para saber com precisão onde se localiza e o mecanismo subjacente à mesma. Este último implica o registo da actividade eléctrica através de electrogramas (EGM) locais em diferentes pontos das aurículas e dos ventrículos, com o auxílio de sistemas de mapeamento tridimensionais (3D) electroanatómicos, sendo um procedimento invasivo. Existem diversos métodos lineares e não lineares que permitem a análise dos EGMs nos domínios do tempo, frequência, fase, entre outros, com a finalidade de melhor compreender os mecanismos subjacentes à FA e, consequentemente aumentar a taxa de sucesso do processo de ablação e melhorar a sua eficiência. Esta área de estudo progrediu significativamente, tanto a nível de hardware, como de software. Apesar disso, os métodos desenvolvidos não têm nem acrescentado benefícios adicionais, nem melhorado significativamente a taxa de sucesso do processo de ablação. Existem várias razões para tal, e grande parte deve-se ao facto destes métodos de análise estarem incorporados nos sistemas de mapeamento e o seu software ser exclusivo. Isto leva a que não consigamos perceber como é que os algoritmos funcionam nos diferentes sistemas de mapeamento para comparar as suas diferenças e semelhanças. Devido a estes constrangimentos, os investigadores são compelidos a desenvolver os seus próprios métodos de análise e técnicas de mapeamento, o que leva à existência de uma multitude de métodos e técnicas de mapeamento que parecem ser diferentes entre si, resultando em informação ambígua e conflituosa no que diz respeito aos mecanismos da FA, e a conclusões distintas entre estudos. O sucesso do tratamento poderia aumentar se tivéssemos uma melhor compreensão dos métodos de análise e da sua aplicação no contexto da FA; perceber se os métodos apontam para o mesmo fenómeno de fibrilhação, se existe alguma correlação entre os métodos, e se a informação fornecida pelos mesmos é complementar ou redundante. Assim, o objectivo deste trabalho consistiu em implementar diferentes métodos para analisar os EGMs e a estrutura 3D da aurícula esquerda (AE) de doentes com FA, numa tentativa de responder às questões que motivaram a realização deste projecto. Em última análise, ao observar os mapas 3D da AE tendo uma melhor compreensão dos métodos, poderemos identificar com precisão as regiões na AE responsáveis por iniciar a FA, e ter mais conhecimento sobre os mecanismos responsáveis pela mesma. Desta forma, o processo de ablação poderá alcançar o seu potencial. Para este projecto, foram incluídos os mapas 3D electroanatómicos da AE de dez doentes com FA paroxística ou persistente do hospital de Santa Marta, recolhidos com o sistema de mapeamento CARTO 3. Cada ponto electroanatómico dos mapas inclui as 12 derivações do ECG, e os EGMs unipolares e bipolares registados com o cateter de mapeamento Pentaray de 20 pólos. Porém, apenas os EGMs bipolares foram incluídos na análise. Processaram-se os sinais bipolares e, devido a algumas limitações, foi possível apenas a implementação de dois métodos diferentes para os analisar: um no domínio da frequência – Frequência Dominante (FD) –, e outro no domínio da Teoria da Informação – a entropia de Shannon. De seguida, criaram-se três tipos de mapas 3D electroanatómicos da AE para cada doente: um de voltagem, cuja informação foi adquirida com o sistema de mapeamento, um de FD, e outro de entropia. A informação de cada mapa estava organizada segundo um padrão de cores. Observando os diferentes tipos de mapas da AE paralelamente, foi possível comparar os métodos, e perceber que tipo de informação cada um deles fornecia, numa tentativa de melhor compreender os mecanismos da FA. Foi possível observar em algumas regiões da AE, principalmente nos mapas de voltagem e de FD, a presença de “centros de activação” ou “centros de fibrilhação”, que poderão ser os gatilhos responsáveis por desencadear ou manter o mecanismo de fibrilhação. Para confirmar se de facto aquelas regiões eram os gatilhos de fibrilhação, seria necessário submeter os doentes ao processo de ablação e queimar essas zonas; e posteriormente acompanhar os doentes para observar os efeitos do procedimento e confirmar a hipótese. Contudo, dadas as limitações do trabalho e o facto desta área de investigação ser pouco explorada, é fulcral obter um maior número de estudo comparativos entre mais métodos de diferentes domínios e confirmar se apontam ou não para o mesmo fenómeno de fibrilhação. Apesar de terem sido implementados apenas dois métodos de análise dos EGMs, o projecto permitiu a comparação entre os mesmos, uma área de estudo por onde ainda há muito para investigar. Com mais conhecimento sobre os diferentes métodos, a sua aplicação, inter-relação e adequação no estudo dos mecanismos da FA e das propriedades electrofisiológicas desta patologia, é possível desenvolver procedimentos de ablação mais eficientes e selectivos, de forma a diminuir os riscos e aumentar a taxa de sucesso do tratamento.Atrial fibrillation (AF) is the most frequent cardiac arrhythmia in clinical practice and is described by rapid and irregular contractions of the atria. Despite catheter ablation (CA) being a well-established treatment for AF, it is sub-optimal, with a success rate of approximately 50 % after a single procedure, with some patients requiring multiple procedures to achieve long-term freedom from this pathology. This prompted the proposal and development of various quantitative electrogram (EGM)-based methods along with different mapping systems with their respective mapping techniques, to better understand the mechanisms responsible for initiating and maintaining AF, thus improving ablation outcomes. However, this diversification of methods and tools resulted in disperse and inconsistent data regarding the mechanisms of AF. This work consisted of employing two different methods to analyse the electrograms (EGM): dominant frequency (DF) and Shannon entropy (ShEn). From these EGMs, metrics were then extracted and displayed in colour-coded fashion on a 3D mesh of the left atrium (LA) from patients with paroxysmal or persistent AF. The two methods were compared to understand whether or not these indicated different phenomena/mechanisms, and if these could locate sites suspected of triggering and maintaining AF. The results, while not fully conforming to the literature, allowed the comparison between different EGM analysis methods, a field of study that requires further research. Overall, this project highlighted the limited data available within the topic, hindering our understanding of AF mechanisms and development of more effective and selective ablation procedures to avoid unnecessary complications, and ultimately improve the effects of the treatment's outcomes

Signal Processing Methods for the Analysis of the Electrocardiogram

Das Elektrokardiogramm (EKG) zeichnet die elektrische Aktivität des Herzens auf der Brust- oberfläche auf. Dieses Signal kann einfach und kostengünstig aufgenommen werden und wird daher in einer Vielzahl von mobilen und stationären Anwendungen genutzt. Es ist über die letzten 100 Jahre zum Goldstandard bei der Diagnose vieler kardiologischer Krankheiten geworden. Herzerkrankungen bleiben ein relevantes Thema in unserer Gesellschaft, da sie zu 30 % aller Todesfälle weltweit führen. Allein die koronare Herzkrankheit ist die häufigste Todesursache überhaupt. Weiterhin sind 2 bis 3 % der Europäer von Herzrhythmusstörungen wie Vorhofflimmern und Vorhofflattern betroffen. Die damit verbundenen geschätzten Kosten in der Europäischen Union belaufen sich auf 26 Milliarden Euro pro Jahr. In allen diesen Fällen ist die Aufzeichnung des EKGs der erste unumgängliche Schritt für eine verlässliche Diagnose und erfolgreiche Therapie. Im Rahmen dieser Dissertation wurden eine Reihe von Algorithmen zur Signalver- arbeitung des EKG entwickelt, die automatisch die rhythmischen und morphologischen Eigenschaften aus dem EKG extrahieren und dadurch den diagnostischen Prozess und die Entscheidungsfindung des Arztes unterstützen. In einem ersten Projekt wurde das Phänomen der postextrasystolischen T-Wellen-Änderung (PEST) untersucht. Die aus der PEST ex- trahierten Biomarker haben wir als Prädiktoren für Herzversagen postuliert. Ein zweites Projekt handelte vom Entwurf eines akkuraten Algorithmus zur Detektion und Annotation der P-Welle im EKG. Als Referenz während der Entwicklung wurden intrakardial gemessene Signale verwendet. Eine dritte Untersuchg hatte das Ziel, das physiologische Phänomen der respiratorischen Sinusarrhythmie (RSA) besser zu verstehen. In diesem Projekt wurde ein Algorithmus zur Trennung der Herzratenvariabilität (HRV) in ihre atmungsabhängige und ihre atmungsunabhn ̈gige Komponente untersucht. Letzterer Anteil der HRV könnte neue Erkenntnisse über die Regulationsmechanismen des kardiovaskulären Systems liefern. In der vierten und letzten Studie wurde der Einfluss mentaler Belastung auf das EKG während der Autofahrt untersucht. Eine Vielzahl von Deskriptoren wurden gefunden, die eine gefährliche mentale Beanspruchung detektieren und somit den Fahrer vor einem möglichen Unfall schützen können. Wir schließen aus diesen Untersuchungen, dass gut entwickelte Methoden der Signalver- arbeitung des EKG das Potential haben, die Belastung der Patienten, die an Herzerkrankungen leiden, und die Anzahl der Verkehrsunfälle zu reduzieren

The Application of Computer Techniques to ECG Interpretation

This book presents some of the latest available information on automated ECG analysis written by many of the leading researchers in the field. It contains a historical introduction, an outline of the latest international standards for signal processing and communications and then an exciting variety of studies on electrophysiological modelling, ECG Imaging, artificial intelligence applied to resting and ambulatory ECGs, body surface mapping, big data in ECG based prediction, enhanced reliability of patient monitoring, and atrial abnormalities on the ECG. It provides an extremely valuable contribution to the field

Alternative Lead Systems for Diagnostic Electrocardiography: Validation and Clinical Applicability

The standard 12-lead electrocardiogram (ECG) remains one of the most important and most frequently used tools for diagnosing cardiac diseases, although several different examination modalities in cardio¬logy have been developed over the years. The standard ECG uses 10 electrodes placed on well-defined positions on the body, 6 on the torso and 4 distally on the limbs. Both industry and academia have invested many years in development of the criteria used to interpret the “diagnostic” standard ECG, and the waveform patterns are taught in medical school. In several situations, however – such as during long-term ECG monitoring or stress testing – use of the electrode positions of the standard ECG is not optimal because of the abundance of noise. In these situations, the limb electrodes must be placed proximally, often even on the torso, and the Mason-Likar (M-L) positions are commonly used. Interference with other clinical procedures, such as echocardiography, can also constitute a problem. An ECG-recording system with fewer electrodes and without any electrodes on the limbs that provides a 12-lead ECG similar to the standard ECG would be valuable. The so-called EASI system uses only 4 recording electrodes in easily determined locations on the torso from which the full 12-lead ECG can be derived. The 12-lead ECG derived from the EASI system has been evaluated in adults in several clinical situations. Physicians who use ECGs in their day-to-day work are often not aware of the differences between 12-lead ECGs recorded from standard versus alternative electrode positions, and they might use criteria developed for the standard ECG when interpreting an ECG obtained from an alternative lead system. This can lead to misinterpretation with the risk of potentially serious consequences for the patient. Optimizing the proximal positions for better concordance with the standard ECG would be of great value for improved diagnostic performance. A version of the “Lund” (LU) lead system has been reported to agree better with the standard lead system than does the M-L lead system, with regard to both Q-wave width and QRS frontal plane axis. To develop a uniform convention for ECG recording, i.e. both for diagnostic ECG and for monitoring, a recording must produce waveforms that have morphologies approximating those obtained with standard ECG and that has noise immunity close to that of M-L. The overall objectives of this thesis were 1) to further validate the EASI system to gain more knowledge about the agreement between EASI-derived and standard 12-lead ECGs, and 2) to investigate the possibility of optimizing the positions of proximally placed limb electrodes. EASI studies In Study I, age-specific transformation coefficients were determined for use in deriving 12-lead ECGs from the EASI signals. The agreement of the waveforms between simultaneously recorded standard and EASI-derived 12-lead ECGs in children (healthy and with various cardiac diagnoses) was studied. For children, it was better to use age-specific transformation coefficients than adult coefficients. The agreement between standard and EASI-derived ECGs was mostly good. In Study II, the intrareader variation of interpretations of 2 standard 12-lead ECGs was compared with the variation of interpretations of standard versus EASI-derived 12-lead ECGs in children (Study I population). The variation of the interpretation of standard versus EASI-derived ECGs was only slightly larger than the intrareader variation of interpretations of standard ECGs. In Study III, the amplitudes of myoelectric noise and baseline wander were compared between simultaneously recorded EASI-derived and M-L 12-lead ECGs in healthy adults. Overall, the 2 lead systems had similar susceptibilities to baseline wander, but EASI was less susceptible than M-L to myoelectric noise. In Study IV, differences in the estimated size of myocardial infarction (MI), as assessed by Selvester scores, were compared between standard and EASI-derived 12-lead ECGs among patients who had had an episode of chest pain suggestive of an acute coronary syndrome. These scores were also compared with MI size measured by cardiac magnetic resonance imaging (MRI). Estimated MI size did not differ significantly between the 2 lead systems, but neither the correlation nor the agreement between MRI and either of the 2 lead systems was very strong. Study to optimize the proximal positions of the limb electrodes In Study V, waveforms from the LU and M-L systems were compared with those from standard ECGs with regard to the QRS axis in the frontal plane and QRS changes of inferior MI. The noise immunities of the standard, LU, and M-L systems were also compared. LU produced ECG waveforms that more closely resembled those obtained with standard ECG than did M-L. The LU system was more noise-immune than was the standard system, and the noise immunities of the LU and the M-L systems were comparable

Analysis of Ventricular Depolarisation and Repolarisation Using Registration and Machine Learning

Our understanding of cardiac diseases has greatly advanced since the advent of electrocardiography (ECG). With the increasing influx of available data in recent times, significant research efforts have been put forth to automate the study and detection of cardiac conditions. Naturally, the focus has progressed toward studying dynamic changes in ventricular depolarisation and repolarisation across serial recordings - as complex beat-to-beat changes in morphology manifest over time. Manual extraction of diagnostic and prognostic markers is a laborious task. Hence, automated and accurate methods are required to extract markers for the study of ventricular lability and detection of common diseases, such as myocardial ischemia and myocardial infarction. The aim of this thesis is to improve automated marker extraction and detection of diseases for the study of ventricular depolarisation and repolarisation lability in ECG. As such, two novel template adaptation methods capable of capturing complex beat-to-beat morphological changes are proposed for three-dimensional and two-dimensional data, respectively. The proposed three-dimensional template adaptation method provides an inhomogeneous method for transforming template vectorcardiogram (VCG) by exploiting registrationinspired parametrisation and an efficient kernel ridge regression formulation. Analysis across simulated data and clinical myocardial infarction data demonstrates state-of-the-art results. The two-dimensional template adaptation method draws from traditional registrationbased techniques and treats the ECG as a two-dimensional point set problem. Validation against previously employed simulated data and a gold-standard annotated clinical database demonstrate the highest level of performance. Subsequently, frameworks employing the proposed template adaptation techniques are developed for the automated detection of ischemic beats and myocardial infarction. Furthermore, a small study analysing ventricular repolarisation variability (VRV) in non-ischemic cardiomyopathy (CM) is considered, utilising markers of cardiac lability proposed in the development of the three-dimensional template adaptation system. In summary, this thesis highlights the necessity for custom template adaptation methods for the accurate measurement of beat-to-beat variability in cardiac data. Two novel stateof- the-art methods are proposed and extended to study myocardial ischemia, myocardial infarction and non-ischemic CM.Thesis (Ph.D.) -- University of Adelaide, School of Electrical and Electronic Engineering, 202

Advanced Signal Processing in Wearable Sensors for Health Monitoring

Smart, wearables devices on a miniature scale are becoming increasingly widely available, typically in the form of smart watches and other connected devices. Consequently, devices to assist in measurements such as electroencephalography (EEG), electrocardiogram (ECG), electromyography (EMG), blood pressure (BP), photoplethysmography (PPG), heart rhythm, respiration rate, apnoea, and motion detection are becoming more available, and play a significant role in healthcare monitoring. The industry is placing great emphasis on making these devices and technologies available on smart devices such as phones and watches. Such measurements are clinically and scientifically useful for real-time monitoring, long-term care, and diagnosis and therapeutic techniques. However, a pertaining issue is that recorded data are usually noisy, contain many artefacts, and are affected by external factors such as movements and physical conditions. In order to obtain accurate and meaningful indicators, the signal has to be processed and conditioned such that the measurements are accurate and free from noise and disturbances. In this context, many researchers have utilized recent technological advances in wearable sensors and signal processing to develop smart and accurate wearable devices for clinical applications. The processing and analysis of physiological signals is a key issue for these smart wearable devices. Consequently, ongoing work in this field of study includes research on filtration, quality checking, signal transformation and decomposition, feature extraction and, most recently, machine learning-based methods

Non-invasive cardiac radiosurgery with MRI guidance: a ground-truth for real-time target localisation using the XCAT phantom

Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia. The growing epidemic of AF already affects millions of patients around the world and millions more are forecast to develop the condition in coming decades. The standard non-pharmacological treatment for AF is catheter ablation, an invasive and time consuming procedure. Non-invasive treatment of AF with radiosurgery has recently been put forward but is challenged by complex cardiac and respiratory motion. Compensating for target motion and treating in real-time could be realised with a MRI linear accelerator (MRI-Linac). A recent study developed methodology to track cardiac targets for this purpose but until now no measure of its accuracy has been accessible. In this investigation, the existing real-time cardiac tracking is quantified and developed on a digital phantom platform. It is first tested within a perfect digital scenario and then extended to a realistic anthropomorphic simulation. In a final experiment, developed tracking methods are applied to real-world anatomical data. A total number of twenty-one virtual patients were generated with the 4 dimensional extended cardiac-torso (XCAT) phantom software and received magnetic resonance imaging (MRI) simulated cardiac scans. A 3D volume representing a distinct cardiac phase is comprised of 2D slices which cover the entire target area. These template volumes are matched through pixel similarity to 2D orthogonal real-time MRI planes to localise the target volume in real-time. One virtual patient represented ideal and thus unrealistic MRI scans to initially test the cardiac tracking. Twenty virtual patients were subjected to MRI scans that closely model the proposed real-world scenario. An available ground-truth is compared to target motion trajectories output from the cardiac tracking algorithm for the twenty-one virtual patients. The cardiac tracking methodology is simultaneously developed as a result of the quantitative measures. Additionally, the correlation and significance of the virtual patients’ physiological parameters with tracking accuracy is investigated. Finally, the best performing tracking function is qualitatively assessed on a single patient’s real-world MRI scans. Employing a tracking method with the same basic methodology as the original tracking on the twenty virtual patient cohort resulted in a mean 3D tracking error of 3.2 ± 1.7 mm. The three anatomical plane constituent errors were 1.3 ± 0.9 mm in the superior inferior (SI) plane, 1.4 ± 0.9 mm in the anterior posterior (AP) plane and 2.2 ± 1.8 mm in the left right (LR) plane. This result is in strong agreement with the inferred error of 3 - 4 mm from the previous study that was based on 2D quantification. After tracking developments were implemented, the best performing mean 3D tracking error of 2.9 ± 1.6 mm was ascertained. A patient’s heart rate is the only anatomical parameter to show a significant linear relationship with tracking error (r=0.65, p-value = 0.0018). Comparing best performing tracking functions across the virtual patients show that the optimal tracking function is patient-specific. When the developed methods were reintroduced to a patient’s MRI data the tracking accuracy was qualitatively assessed to have improved. The results of the previous single patient treatment planning indicate that high-dose cardiac radiosurgery can be administered for the treatment of AF when safety margins are below 5 mm. The quantitative measures presented here demonstrate that real-time target localisation and motion compensation could successfully be implemented with an MRI-Linac. The conclusions of this work strongly encourage further development of the proposed AF treatment with non-invasive radiosurgery