Publications
486 results found
Arnold AD, Howard JP, Gopi A, et al., 2020, Corrigendum to: Discriminating electrocardiographic responses to His-bundle pacing using machine learning [Cardiovascular Digital Health Journal 1 (2020) 11–20/5], Cardiovascular Digital Health Journal, Vol: 1, Pages: 111-111, ISSN: 2666-6936
Brook J, Kim M-Y, Koutsoftidis S, et al., 2020, Development of a pro-arrhythmic ex vivo intact human and porcine model: cardiac electrophysiological changes associated with cellular uncoupling, Pflügers Archiv European Journal of Physiology, Vol: 472, Pages: 1435-1446, ISSN: 0031-6768
We describe a human and large animal Langendorff experimental apparatus for live electrophysiological studies and measure the electrophysiological changes due to gap-junction uncoupling in human and porcine hearts. The resultant ex vivo intact human and porcine model can bridge the translational gap between smaller simple laboratory models and clinical research. In particular, electrophysiological models would benefit from the greater myocardial mass of a large heart due to its effects on far field signal, electrode contact issues and motion artefacts, consequently more closely mimicking the clinical setting Porcine (n=9) and human (n=4) donor hearts were perfused on a custom-designed Langendorff apparatus. Epicardial electrograms were collected at 16 sites across the left atrium and left ventricle. 1mM of carbenoxolone was administered at 5ml/min to induce cellular uncoupling, and then recordings were repeated at the same sites. Changes in electrogram characteristics were analysed.We demonstrate the viability of a controlled ex vivo model of intact porcine and human hearts for electrophysiology with pharmacological modulation. Carbenoxolone reduces cellular coupling and changes contact electrogram features. The time from stimulus artefact to (-dV/dt)max increased between baseline and carbenoxolone (47.9±4.1ms to 67.2±2.7ms) indicating conduction slowing. The features with the largest percentage change between baseline to Carbenoxolone were Fractionation +185.3%, Endpoint amplitude -106.9%, S-Endpoint Gradient +54.9%, S Point, -39.4%, RS Ratio +38.6% and (-dV/dt)max -20.9%.The physiological relevance of this methodological tool is that it provides a model to further investigate pharmacologically-induced proarrhythmic substrates.
Kim M-Y, Sandler B, Sikkel MB, et al., 2020, The anatomical distribution of the ectopy-triggering ganglionated plexus in patients with atrial fibrillation, Circulation: Arrhythmia and Electrophysiology, Vol: 13, Pages: 1045-1047, ISSN: 1941-3084
Ng FS, Handa B, Li X, et al., 2020, Towards mechanism-directed electrophenotype-based treatments for atrial fibrillation, Frontiers in Physiology, Vol: 11, Pages: 1-7, ISSN: 1664-042X
Current treatment approaches for persistent atrial fibrillation (AF) have a ceiling of success of around 50%. This is despite 15 years of developing adjunctive ablation strategies in addition to pulmonary vein isolation to target the underlying arrhythmogenic substrate in AF. A major shortcoming of our current approach to AF treatment is its predominantly empirical nature. This has in part been due to a lack of consensus on the mechanisms that sustain human AF.6 In this article, we review evidence suggesting that the previous debates on AF being eitheran organised arrhythmia with a focal driver ora disorganised rhythm sustained by multiple wavelets, may prove to be a false dichotomy. Instead,a range of fibrillation electrophenotypes exists along a continuous spectrum, and the predominant mechanism in an individual case is determined by the nature and extent of remodelling of the underlying substrate. We propose moving beyond the current empirical approach to AF treatment, and highlight the need to prescribe AF treatments based on the underlying AFelectrophenotype, and review several possible novel mapping algorithms that may be useful in discerning the AF electrophenotype to guide tailored treatments, including Granger Causality mapping.
Arnold AD, Howard JP, Gopi AA, et al., 2020, Discriminating electrocardiographic responses to His-bundle pacing using machine learning., Cardiovascular Digital Health Journal, Vol: 1, Pages: 11-20
Background: His-bundle pacing (HBP) has emerged as an alternative to conventional ventricular pacing because of its ability to deliver physiological ventricular activation. Pacing at the His bundle produces different electrocardiographic (ECG) responses: selective His-bundle pacing (S-HBP), non-selective His bundle pacing (NS-HBP), and myocardium-only capture (MOC). These 3 capture types must be distinguished from each other, which can be challenging and time-consuming even for experts. Objective: The purpose of this study was to use artificial intelligence (AI) in the form of supervised machine learning using a convolutional neural network (CNN) to automate HBP ECG interpretation. Methods: We identified patients who had undergone HBP and extracted raw 12-lead ECG data during S-HBP, NS-HBP, and MOC. A CNN was trained, using 3-fold cross-validation, on 75% of the segmented QRS complexes labeled with their capture type. The remaining 25% was kept aside as a testing dataset. Results: The CNN was trained with 1297 QRS complexes from 59 patients. Cohen kappa for the neural network's performance on the 17-patient testing set was 0.59 (95% confidence interval 0.30 to 0.88; P <.0001), with an overall accuracy of 75%. The CNN's accuracy in the 17-patient testing set was 67% for S-HBP, 71% for NS-HBP, and 84% for MOC. Conclusion: We demonstrated proof of concept that a neural network can be trained to automate discrimination between HBP ECG responses. When a larger dataset is trained to higher accuracy, automated AI ECG analysis could facilitate HBP implantation and follow-up and prevent complications resulting from incorrect HBP ECG analysis.
Davies HJ, Williams I, Peters NS, et al., 2020, In-ear SpO2: a tool for wearable, unobtrusive monitoring of core blood oxygen saturation, Sensors (Basel, Switzerland), Vol: 20, ISSN: 1424-8220
The non-invasive estimation of blood oxygen saturation (SpO2) by pulse oximetry is of vital importance clinically, from the detection of sleep apnea to the recent ambulatory monitoring of hypoxemia in the delayed post-infective phase of COVID-19. In this proof of concept study, we set out to establish the feasibility of SpO2 measurement from the ear canal as a convenient site for long term monitoring, and perform a comprehensive comparison with the right index finger-the conventional clinical measurement site. During resting blood oxygen saturation estimation, we found a root mean square difference of 1.47% between the two measurement sites, with a mean difference of 0.23% higher SpO2 in the right ear canal. Using breath holds, we observe the known phenomena of time delay between central circulation and peripheral circulation with a mean delay between the ear and finger of 12.4 s across all subjects. Furthermore, we document the lower photoplethysmogram amplitude from the ear canal and suggest ways to mitigate this issue. In conjunction with the well-known robustness to temperature induced vasoconstriction, this makes conclusive evidence for in-ear SpO2 monitoring being both convenient and superior to conventional finger measurement for continuous non-intrusive monitoring in both clinical and everyday-life settings.
Bachtiger P, Peters NS, Walsh SLF, 2020, Machine learning for COVID-19-asking the right questions, The Lancet Digital Health, Vol: 2, Pages: E391-E392, ISSN: 2589-7500
Handa BS, Li X, Aras KK, et al., 2020, Response by Handa et al to letter regarding article, "Granger causality-based analysis for classification of fibrillation mechanisms and localization of rotational drivers", Circulation: Arrhythmia and Electrophysiology, Vol: 13, ISSN: 1941-3084
Feeny AK, Chung MK, Madabhushi A, et al., 2020, Artificial intelligence and machine learning in arrhythmias and cardiac electrophysiology, Circulation: Arrhythmia and Electrophysiology, Vol: 13, Pages: 1-18, ISSN: 1941-3084
Artificial intelligence (AI) and machine learning (ML) in medicine are currently areas of intense exploration, showing potential to automate human tasks and even perform tasks beyond human capabilities. Literacy and understanding of AI/ML methods are becoming increasingly important to researchers and clinicians. The first objective of this review is to provide the novice reader with literacy of AI/ML methods and provide a foundation for how one might conduct an ML study. We provide a technical overview of some of the most commonly used terms, techniques, and challenges in AI/ML studies, with reference to recent studies in cardiac electrophysiology to illustrate key points. The second objective of this review is to use examples from recent literature to discuss how AI and ML are changing clinical practice and research in cardiac electrophysiology, with emphasis on disease detection and diagnosis, prediction of patient outcomes, and novel characterization of disease. The final objective is to highlight important considerations and challenges for appropriate validation, adoption, and deployment of AI technologies into clinical practice.
Ciaccio EJ, Coromilas J, Wan EY, et al., 2020, Slow uniform electrical activation during sinus rhythm is an indicator of reentrant VT isthmus location and orientation in an experimental model of myocardial infarction., Computer Methods and Programs in Biomedicine, Vol: 196, Pages: 105666-105666, ISSN: 0169-2607
BACKGROUND: To validate the predictability of reentrant circuit isthmus locations without ventricular tachycardia (VT) induction during high-definition mapping, we used computer methods to analyse sinus rhythm activation in experiments where isthmus location was subsequently verified by mapping reentrant VT circuits. METHOD: In 21 experiments using a canine postinfarction model, bipolar electrograms were obtained from 196-312 recordings with 4mm spacing in the epicardial border zone during sinus rhythm and during VT. From computerized electrical activation maps of the reentrant circuit, areas of conduction block were determined and the isthmus was localized. A linear regression was computed at three different locations about the reentry isthmus using sinus rhythm electrogram activation data. From the regression analysis, the uniformity, a measure of the constancy at which the wavefront propagates, and the activation gradient, a measure that may approximate wavefront speed, were computed. The purpose was to test the hypothesis that the isthmus locates in a region of slow uniform activation bounded by areas of electrical discontinuity. RESULTS: Based on the regression parameters, sinus rhythm activation along the isthmus near its exit proceeded uniformly (mean r2= 0.95±0.05) and with a low magnitude gradient (mean 0.37±0.10mm/ms). Perpendicular to the isthmus long-axis across its boundaries, the activation wavefront propagated much less uniformly (mean r2= 0.76±0.24) although of similar gradient (mean 0.38±0.23mm/ms). In the opposite direction from the exit, at the isthmus entrance, there was also less uniformity (mean r2= 0.80±0.22) but a larger magnitude gradient (mean 0.50±0.25mm/ms). A theoretical ablation line drawn perpendicular to the last sinus rhythm activation site along the isthmus long-axis was predicted to prevent VT reinduction. Anatomical conduction block occurred in 7/21 experiments, but comprised only small po
Lyon A, Babalis D, Morley-Smith AC, et al., 2020, Investigation of the safety and feasibility of AAV1/SERCA2a gene transfer in patients with chronic heart failure supported with a left ventricular assist device – the SERCA-LVAD TRIAL, Gene Therapy, Vol: 27, Pages: 579-590, ISSN: 0969-7128
The SERCA-LVAD trial was a phase 2a trial assessing the safety and feasibility of delivering an adeno-associated vector 1 carrying the cardiac isoform of the sarcoplasmic reticulum calcium ATPase (AAV1/SERCA2a) to adult chronic heart failure patients implanted with a left ventricular assist device. Enrolled subjects were randomised to receive a single intracoronary infusion of 1x1013 DNase-resistant AAV1/SERCA2a particles or a placebo solution in a double-blinded design, stratified by presence of neutralising antibodies to AAV. Elective endomyocardial biopsy was performed at 6 months unless the subject had undergone cardiac transplantation, with myocardial samples assessed for the presence of exogenous viral DNA from the treatment vector. Safety assessments including ELISPOT were serially performed. Although designed as a 24 subject trial, recruitment was stopped after five subjects had been randomised and received infusion due to the neutral result from the CUPID 2 trial. Here we describe the results from the 5 patients, which confirmed that viral DNA was delivered to the failing human heart in 2 patients receiving gene therapy with vector detectable at follow up endomyocardial biopsy or cardiac transplantation. Absolute levels of detectable transgene DNA were low, and no functional benefit was observed. There were no safety concerns in this small cohort. This trial identified some of the challenges of performing gene therapy trials in this LVAD patient cohort, which may help guide future trial design.
Ding EY, Svennberg E, Wurster C, et al., 2020, Survey of current perspectives on consumer-available digital health devices for detecting atrial fibrillation., Cardiovascular Digital Health Journal, Vol: 1, Pages: 21-29, ISSN: 2666-6936
Background: Many digital health technologies capable of atrial fibrillation (AF) detection are directly available to patients. However, adaptation into clinical practice by heart rhythm healthcare practitioners (HCPs) is unclear. Objective: To examine HCP perspectives on use of commercial technologies for AF detection and management. Methods: We created an electronic survey for HCPs assessing practice demographics and perspectives on digital devices for AF detection and management. The survey was distributed electronically to all members of 3 heart rhythm professional societies. Results: We received 1601 responses out of 73,563 e-mails sent, with 43.6% from cardiac electrophysiologists, 12.8% from fellows, and 11.6% from advanced practice practitioners. Most respondents (62.3%) reported having recommended patient use of a digital device for AF detection. Those who did not had concerns about their accuracy (29.6%), clinical utility of results (22.8%), and integration into electronic health records (19.8%). Results from a 30-second single-lead electrocardiogram were sufficient for 42.7% of HCPs to recommend oral anticoagulation for patients at high risk for stroke. Respondents wanted more data comparing the accuracy of digital devices to conventional devices for AF monitoring (64.9%). A quarter (27.3%) of HCPs had no reservations recommending digital devices for AF detection, and most (53.4%) wanted guidelines from their professional societies providing guidance on their optimal use. Conclusion: Many HCPs have already integrated digital devices into their clinical practice. However, HCPs reported facing challenges when using digital technologies for AF detection, and professional society recommendations on their use are needed.
Bachtiger P, Adamson A, Quint JK, et al., 2020, Belief of Previous COVID-19 Infection and Unclear Government Policy are Associated with Reduced Willingness to Participate in App-Based Contact Tracing: A UK-Wide Observational Study of 13,000 Patients
<jats:title>ABSTRACT</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Contact tracing and lockdown are health policies being used worldwide to combat the coronavirus (COVID-19). While easing lockdown, the UK National Health Service (NHS) launched its Track and Trace Service at the end of May 2020, and aims by end of June 2020 also to include app-based notification and advice to self-isolate for those who have been in contact with a person known to have COVID-19. To be successful, such an app will require high uptake, the determinants and willingness for which are unclear but essential to understand for effective public health benefit.</jats:p></jats:sec><jats:sec><jats:title>Objectives</jats:title><jats:p>To measure the determinants of willingness to participate in an NHS app-based contact tracing programme using a questionnaire within the Care Information Exchange (CIE) - the largest patient-facing electronic health record in the NHS.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Observational study of 47,708 registered NHS users of the CIE, 27% of whom completed a novel questionnaire asking about willingness to participate in app-based contact tracing, understanding of government advice, mental and physical wellbeing and their healthcare utilisation -- related or not to COVID-19. Descriptive statistics are reported alongside univariate and multivariable logistic regression models, with positive or negative responses to a question on app-based contact tracing as the dependent variable.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>26.1% of all CIE participants were included in the analysis (N = 12,434, 43.0% male, mean age 55.2). 60.3% of respondents were willing to participate in app-based contact tracing. Out of those who responded ‘no’, 67.2% state
Ciacci A, Falkenberg M, Manani KA, et al., 2020, Understanding the transition from paroxysmal to persistent atrial fibrillation, Physical Review Research, Vol: 2, Pages: 1-23, ISSN: 2643-1564
Atrial fibrillation (AF) is the most common cardiac arrhytmia, characterisedby the chaotic motion of electrical wavefronts in the atria. In clinicalpractice, AF is classified under two primary categories: paroxysmal AF, shortintermittent episodes separated by periods of normal electrical activity, andpersistent AF, longer uninterrupted episodes of chaotic electrical activity.However, the precise reasons why AF in a given patient is paroxysmal orpersistent is poorly understood. Recently, we have introduced the percolationbased Christensen-Manani-Peters (CMP) model of AF which naturally exhibits bothparoxysmal and persistent AF, but precisely how these differences emerge in themodel is unclear. In this paper, we dissect the CMP model to identify the causeof these different AF classifications. Starting from a mean-field model wherewe describe AF as a simple birth-death process, we add layers of complexity tothe model and show that persistent AF arises from the formation of temporallystable structural re-entrant circuits that form from the interaction ofwavefront collisions during paroxysmal AF. These results are compatible withrecent findings suggesting that the formation of re-entrant drivers in fibroticborder zones perpetuates persistent AF.
Roney CH, Wit AL, Peters NS, 2020, Challenges associated with interpreting mechanisms of AF, Arrhythmia & electrophysiology review, Vol: 8, Pages: 273-284, ISSN: 2050-3369
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.
Bachtiger P, Plymen CM, Pabari PA, et al., 2020, Artificial intelligence, data sensors and interconnectivity: future Opportunities for heart failure, Cardiac Failure Review, Vol: 6, Pages: e11-e11, ISSN: 2057-7540
A higher proportion of patients with heart failure have benefitted from a wide and expanding variety of sensor-enabled implantable devices than any other patient group. These patients can now also take advantage of the ever-increasing availability and affordability of consumer electronics. Wearable, on- and near-body sensor technologies, much like implantable devices, generate massive amounts of data. The connectivity of all these devices has created opportunities for pooling data from multiple sensors - so-called interconnectivity - and for artificial intelligence to provide new diagnostic, triage, risk-stratification and disease management insights for the delivery of better, more personalised and cost-effective healthcare. Artificial intelligence is also bringing important and previously inaccessible insights from our conventional cardiac investigations. The aim of this article is to review the convergence of artificial intelligence, sensor technologies and interconnectivity and the way in which this combination is set to change the care of patients with heart failure.
Falkenberg M, Hickey D, Terrill L, et al., 2020, Identifying potential re-entrant circuit locations from atrial fibre maps., Computing in cardiology, Vol: 46, Pages: 1-4, ISSN: 2325-8861
Re-entrant circuits have been identified as potential drivers of atrial fibrillation (AF). In this paper, we develop a novel computational framework for finding the locations of re-entrant circuits from high resolution fibre orientation data. The technique follows a statistical approach whereby we generate continuous fibre tracts across the tissue and couple adjacent fibres stochastically if they are within a given distance of each other. By varying the connection distance, we identify which regions are most susceptible to forming re-entrant circuits if muscle fibres are uncoupled, through the action of fibrosis or otherwise. Our results highlight the sleeves of the pulmonary veins, the posterior left atrium and the left atrial appendage as the regions most susceptible to re-entrant circuit formation. This is consistent with known risk locations in clinical AF. If the model can be personalised for individual patients undergoing ablation, future versions may be able to suggest suitable ablation targets.
Handa B, Li X, Aras KK, et al., 2020, Granger causality-based analysis for classification of fibrillation mechanisms and localisation of rotational drivers, Circulation: Arrhythmia and Electrophysiology, Vol: 12, Pages: 258-273, ISSN: 1941-3084
Background:The mechanisms sustaining myocardial fibrillation remain disputed, partly due to a lack of mapping tools that can accurately identify the mechanism with low spatial resolution clinical recordings. Granger causality (GC) analysis, an econometric tool for quantifying causal relationships between complex time-series, was developed as a novel fibrillation mapping tool and adapted to low spatial resolution sequentially acquired data.Methods:Ventricular fibrillation (VF) optical mapping was performed in Langendorff-perfused Sprague-Dawley rat hearts (n=18), where novel algorithms were developed using GC-based analysis to (1) quantify causal dependence of neighboring signals and plot GC vectors, (2) quantify global organization with the causality pairing index, a measure of neighboring causal signal pairs, and (3) localize rotational drivers (RDs) by quantifying the circular interdependence of neighboring signals with the circular interdependence value. GC-based mapping tools were optimized for low spatial resolution from downsampled optical mapping data, validated against high-resolution phase analysis and further tested in previous VF optical mapping recordings of coronary perfused donor heart left ventricular wedge preparations (n=12), and adapted for sequentially acquired intracardiac electrograms during human persistent atrial fibrillation mapping (n=16).Results:Global VF organization quantified by causality pairing index showed a negative correlation at progressively lower resolutions (50% resolution: P=0.006, R2=0.38, 12.5% resolution, P=0.004, R2=0.41) with a phase analysis derived measure of disorganization, locations occupied by phase singularities. In organized VF with high causality pairing index values, GC vector mapping characterized dominant propagating patterns and localized stable RDs, with the circular interdependence value showing a significant difference in driver versus nondriver regions (0.91±0.05 versus 0.35±0.06, P=0.0002).
Tarkin JM, Cole GD, Gopalan D, et al., 2020, Multimodal imaging of granulomatosis with polyangiitis aortitis complicated by severe aortic regurgitation and complete heart block, Circulation: Cardiovascular Imaging, Vol: 13, Pages: 1-3, ISSN: 1941-9651
Li X, Handa BS, Peters NS, et al., 2020, Classification of fibrillation subtypes with single-channel surface electrocardiogram, UK Workshop on Computational Intelligence (UKCI), Publisher: Springer International Publishing, Pages: 472-479, ISSN: 2194-5357
Atrial fibrillation (AF) and ventricular fibrillation (VF) are complex heart rhythm disorders with increasing prevalence. Mechanisms sustaining these arrhythmias are different, and subsequently, the required treatments options differ. Although many algorithms have been developed for differentiating fibrillation from normal sinus rhythm, very few methods exist to differentiate between different forms of AF and VF from surface electrocardiogram (ECG). To address the issue, we propose a novel ECG classification method to differentiate fibrillation that is completely chaotic from forms where it is organized with key driving sites. Differentiating fibrillation organisation from ECGs may aid patient selection, and identify those who may benefit from targeted ablation treatment. Evaluation using real-world data sets based on rat VF model shows that the proposed method could recognise the correct Fibrillation subtype from the single-channel electrocardiogram with an accuracy of 88.89 % .
Falkenberg McGillivray M, Ford A, Li A, et al., 2019, Unified mechanism of local drivers in a percolation model of atrial fibrillation, Physical Review E, Vol: 100, ISSN: 2470-0045
The mechanisms of atrial fibrillation (AF) are poorly understood, resulting in disappointing success rates of ablative treatment. Different mechanisms defined largely by different atrial activation patterns have been proposed and, arguably, this dispute has slowed the progress of AF research. Recent clinical evidence suggests a unifying mechanism of local drivers based on sustained re-entrant circuits in the complex atrial architecture. Here, we present a percolation inspired computational model showing spontaneous emergence of AF that strongly supports, and gives a theoretical explanation for, the clinically observed diversity of activation. We show that the difference in surface activation patterns is a direct consequence of the thickness of the discrete network of heart muscle cells through which electrical signals percolate to reach the imaged surface. The model naturally follows the clinical spectrum of AF spanning sinus rhythm, paroxysmal and persistent AF as the decoupling of myocardial cells results in the lattice approaching the percolation threshold. This allows the model to make the novel prediction that for paroxysmal AF, re-entrant circuits emerge near the endocardium, but in persistent AF they emerge deeper in the bulk of the atrial wall. If experimentally verified, this may go towards explaining the lowering ablation success rate as AF becomes more persistent.
Li X, Roney C, Handa B, et al., 2019, Standardised framework for quantitative analysisof fibrillation dynamics, Scientific Reports, Vol: 9, ISSN: 2045-2322
The analysis of complex mechanisms underlying ventricular fibrillation (VF) and atrial fibrillation (AF) requires sophisticatedtools for studying spatio-temporal action potential (AP) propagation dynamics. However, fibrillation analysis tools are oftencustom-made or proprietary, and vary between research groups. With no optimal standardised framework for analysis, resultsfrom different studies have led to disparate findings. Given the technical gap, here we present a comprehensive framework andset of principles for quantifying properties of wavefront dynamics in phase-processed data recorded during myocardial fibrillationwith potentiometric dyes. Phase transformation of the fibrillatory data is particularly useful for identifying self-perpetuating spiralwaves or rotational drivers (RDs) rotating around a phase singularity (PS). RDs have been implicated in sustaining fibrillation,and thus accurate localisation and quantification of RDs is crucial for understanding specific fibrillatory mechanisms. In thiswork, we assess how variation of analysis parameters and thresholds in the tracking of PSs and quantification of RDs couldresult in different interpretations of the underlying fibrillation mechanism. These techniques have been described and appliedto experimental AF and VF data, and AF simulations, and examples are provided from each of these data sets to demonstratethe range of fibrillatory behaviours and adaptability of these tools. The presented methodologies are available as an opensource software and offer an off-the-shelf research toolkit for quantifying and analysing fibrillatory mechanisms.
Ciaccio EJ, Wan EY, Saluja DS, et al., 2019, Addressing challenges of quantitative methodologies and event interpretation in the study of atrial fibrillation, Computer Methods and Programs in Biomedicine, Vol: 178, Pages: 113-122, ISSN: 0169-2607
Atrial fibrillation (AF) is the commonest arrhythmia, yet the mechanisms of its onset and persistence are incompletely known. Although techniques for quantitative assessment have been investigated, there have been few attempts to integrate this information to advance disease treatment protocols. In this review, key quantitative methods for AF analysis are described, and suggestions are provided for the coordination of the available information, and to develop foci and directions for future research efforts. Quantitative biologists may have an interest in this topic in order to develop machine learning and tools for arrhythmia characterization, but they may perhaps have a minimal background in the clinical methodology and in the types of observed events and mechanistic hypotheses that have thus far been developed. We attempt to address these issues via exploration of the published literature. Although no new data is presented in this review, examples are shown of current lines of investigation, and in particular, how electrogram analysis and whole-chamber quantitative modeling of the left atrium may be useful to characterize fibrillatory patterns of activity, so as to propose avenues for more efficacious acquisition and interpretation of AF data.
Shun-Shin MJ, Leong KMW, Ng FS, et al., 2019, Ventricular conduction stability test: a method to identify and quantify changes in whole heart activation patterns during physiological stress, EP-Europace, Vol: 21, Pages: 1422-1431, ISSN: 1099-5129
AIMS: Abnormal rate adaptation of the action potential is proarrhythmic but is difficult to measure with current electro-anatomical mapping techniques. We developed a method to rapidly quantify spatial discordance in whole heart activation in response to rate cycle length changes. We test the hypothesis that patients with underlying channelopathies or history of aborted sudden cardiac death (SCD) have a reduced capacity to maintain uniform activation following exercise. METHODS AND RESULTS: Electrocardiographical imaging (ECGI) reconstructs >1200 electrograms (EGMs) over the ventricles from a single beat, providing epicardial whole heart activation maps. Thirty-one individuals [11 SCD survivors; 10 Brugada syndrome (BrS) without SCD; and 10 controls] with structurally normal hearts underwent ECGI vest recordings following exercise treadmill. For each patient, we calculated the relative change in EGM local activation times (LATs) between a baseline and post-exertion phase using custom written software. A ventricular conduction stability (V-CoS) score calculated to indicate the percentage of ventricle that showed no significant change in relative LAT (<10 ms). A lower score reflected greater conduction heterogeneity. Mean variability (standard deviation) of V-CoS score over 10 consecutive beats was small (0.9 ± 0.5%), with good inter-operator reproducibility of V-CoS scores. Sudden cardiac death survivors, compared to BrS and controls, had the lowest V-CoS scores post-exertion (P = 0.011) but were no different at baseline (P = 0.50). CONCLUSION: We present a method to rapidly quantify changes in global activation which provides a measure of conduction heterogeneity and proof of concept by demonstrating SCD survivors have a reduced capacity to maintain uniform activation following exercise.
Mann I, Coyle C, Qureshi N, et al., 2019, Evaluation of a new algorithm for tracking activation during atrial fibrillation using multipolar catheters in humans, JOURNAL OF CARDIOVASCULAR ELECTROPHYSIOLOGY, Vol: 30, Pages: 1464-1474, ISSN: 1045-3873
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Qureshi N, Kim S, Cantwell C, et al., 2019, Voltage during atrial fibrillation is superior to voltage during sinus rhythm in localizing areas of delayed enhancement on magnetic resonance imaging: An assessment of the posterior left atrium in patients with persistent atrial fibrillation, Heart Rhythm, Vol: 16, Pages: 1357-1367, ISSN: 1547-5271
BackgroundBipolar electrogram voltage during sinus rhythm (VSR) has been used as a surrogate for atrial fibrosis in guiding catheter ablation of persistent AF, but the fixed rate and wavefront characteristics present during sinus rhythm may not accurately reflect underlying functional vulnerabilities responsible for AF maintenance.ObjectivesWe hypothesized that given adequate temporal sampling, the spatial distribution of mean AF voltage (VmAF) should better correlate with delayed-enhancement MRI (MRI-DE) detected atrial fibrosis than VSR.MethodsAF was mapped (8s) during index ablation for persistent AF (20 patients) using a 20-pole catheter (660±28 points/map). Following cardioversion, VSR was mapped (557±326 points/map). Electroanatomic and MRI-DE maps were co-registered in 14 patients.Results(i) The time course of VmAF was assessed from 1-40 AF-cycles (∼8s) at 1113 locations. VmAF stabilized with sampling >4s (mean voltage error=0.05mV). (ii) Paired point analysis of VmAF from segments acquired 30s apart (3,667-sites, 15-patients), showed strong correlation (r=0.95, p<0.001). (iii) Delayed-enhancement (DE) was assessed across the posterior left atrial (LA) wall, occupying 33±13%. VmAF distributions (median[IQR]) were 0.21[0.14-0.35]mV in DE vs. 0.52[0.34-0.77]mV in Non-DE regions. VSR distributions were 1.34[0.65-2.48]mV in DE vs. 2.37[1.27-3.97]mV in Non-DE. A VmAF threshold of 0.35mV yielded sensitivity/specificity 75%/79% in detecting MRI-DE, compared with 63%/67% for VSR (1.8mV threshold).ConclusionThe correlation between low-voltage and posterior LA MRI-DE is significantly improved when acquired during AF vs. sinus rhythm. With adequate sampling, mean AF voltage is a reproducible marker reflecting the functional response to the underlying persistent AF substrate.
Slotwiner DJ, Tarakji KG, Al-Khatib SM, et al., 2019, Transparent sharing of digital health data: A call to action, Heart Rhythm, Vol: 16, Pages: e95-e106, ISSN: 1547-5271
Luther V, Agarwal S, Chow A, et al., 2019, Ripple-AT study: A multicenter and randomized study comparing 3d mapping techniques during atrial tachycardia ablations, Circulation: Arrhythmia and Electrophysiology, Vol: 12, Pages: 1-13, ISSN: 1941-3084
BACKGROUND: Ripple mapping (RM) is an alternative approach to activation mapping of atrial tachycardia (AT) that avoids electrogram annotation. We tested whether RM is superior to conventional annotation based local activation time (LAT) mapping for AT diagnosis in a randomized and multicenter study. METHODS: Patients with AT were randomized to either RM or LAT mapping using the CARTO3v4 CONFIDENSE system. Operators determined the diagnosis using the assigned 3D mapping arm alone, before being permitted a single confirmatory entrainment manuever if needed. A planned ablation lesion set was defined. The primary end point was AT termination with delivery of the planned ablation lesion set. The inability to terminate AT with this first lesion set, the use of more than one entrainment manuever, or the need to crossover to the other mapping arm was defined as failure to achieve the primary end point. RESULTS: One hundred five patients from 7 centers were recruited with 22 patients excluded due to premature AT termination, noninducibility or left atrial appendage thrombus. Eighty-three patients (pts; RM=42, LAT=41) completed mapping and ablation within the 2 groups of similar characteristics (RM versus LAT: prior ablation or cardiac surgery n=35 [83%] versus n=35 [85%], P=0.80). The primary end point occurred in 38/42 pts (90%) in the RM group and 29/41pts (71%) in the LAT group (P=0.045). This was achieved without any entrainment in 31/42 pts (74%) with RM and 18/41 pts (44%) with LAT (P=0.01). Of those patients who failed to achieve the primary end point, AT termination was achieved in 9/12 pts (75%) in the LAT group following crossover to RM with entrainment, but 0/4 pts (0%) in the RM group crossing over to LAT mapping with entrainment (P=0.04). CONCLUSIONS: RM is superior to LAT mapping on the CARTO3v4 CONFIDENSE system in guiding ablation to terminate AT with the first lesion set and with reduced entrainment to assist diagnosis. CLINICAL TRIALS REGISTRATION: https:/
Sau A, Howard J, Al-Aidarous S, et al., 2019, Meta-analysis of randomized controlled trials of atrial fibrillation ablation with pulmonary vein isolation versus without, JACC: Clinical Electrophysiology, Vol: 5, Pages: 968-976, ISSN: 2405-5018
ObjectivesThis meta-analysis examined the ability of pulmonary vein isolation (PVI) to prevent atrial fibrillation in randomized controlled trials (RCTs) in which the patients not receiving PVI nevertheless underwent a procedure.BackgroundPVI is a commonly used procedure for the treatment of atrial fibrillation (AF), and its efficacy has usually been judged against therapy with anti-arrhythmic drugs in open-label trials. There have been several RCTs of AF ablation in which both arms received an ablation, but the difference between the treatment arms was inclusion or omission of PVI. These trials of an ablation strategy with PVI versus an ablation strategy without PVI may provide a more rigorous method for evaluating the efficacy of PVI.MethodsMedline and Cochrane databases were searched for RCTs comparing ablation including PVI with ablation excluding PVI. The primary efficacy endpoint was freedom from atrial fibrillation (AF) and atrial tachycardia at 12 months. A random-effects meta-analysis was performed using the restricted maximum likelihood estimator.ResultsOverall, 6 studies (610 patients) met inclusion criteria. AF recurrence was significantly lower with an ablation including PVI than an ablation without PVI (RR: 0.54; 95% confidence interval [CI]: 0.33 to 0.89; p 1⁄4 0.0147; I2 1⁄4 79.7%). Neither the type of AF (p 1⁄4 0.48) nor the type of non-PVI ablation (p 1⁄4 0.21) was a significant moderator of the effect size. In 3 trials the non-PVI ablation procedure was performed in both arms, whereas PVI was performed in only 1 arm. In these studies, AF recurrence was significantly lower when PVI was included (RR: 0.32; 95% CI: 0.14 to 0.73; p 1⁄4 0.007, I2 78%ConclusionIn RCTs where both arms received an ablation, and therefore an expectation amongst patients and doctors of benefit, being randomized to PVI had a striking effect, reducing AF recurrence by a half.
Sau A, Al-Aidarous S, Howard J, et al., 2019, Optimum lesion set and predictors of outcome in persistent atrial fibrillation ablation: a meta-regression analysis, Europace, Vol: 21, Pages: 1176-1184, ISSN: 1099-5129
AIMS: Ablation of persistent atrial fibrillation (PsAF) has been performed by many techniques with varying success rates. This may be due to ablation techniques, patient demographics, comorbidities, and trial design. We conducted a meta-regression of studies of PsAF ablation to elucidate the factors affecting atrial fibrillation (AF) recurrence. METHODS AND RESULTS : Databases were searched for prospective studies of PsAF ablation. A meta-regression was performed. Fifty-eight studies (6767 patients) were included. Complex fractionated atrial electrogram (CFAE) ablation reduced freedom from AF by 8.9% [95% confidence interval (CI) -15 to -2.3, P = 0.009). Left atrial appendage [LAA isolation (three study arms)] increased freedom from AF by 39.5% (95% CI 9.1-78.4, P = 0.008). Posterior wall isolation (PWI) (eight study arms) increased freedom from AF by 19.4% (95% CI 3.3-38.1, P = 0.017). Linear ablation or ganglionated plexi ablation resulted in no significant effect on freedom from AF. More extensive ablation increased intraprocedural AF termination; however, intraprocedural AF termination was not associated with improved outcomes. Increased left atrial diameter was associated with a reduction in freedom from AF by 4% (95% CI -6.8% to -1.1%, P = 0.007) for every 1 mm increase in diameter. CONCLUSION : Linear ablation, PWI, and CFAE ablation improves intraprocedural AF termination, but such termination does not predict better long-term outcomes. Study arms including PWI or LAA isolation in the lesion set were associated with improved outcomes in terms of freedom from AF; however, further randomized trials are required before these can be routinely recommended. Left atrial size is the most important marker of AF chronicity influencing outcomes.
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