Publications by authors named "Chris D Cantwell"

18 Publications

  • Page 1 of 1

Left Atrial Enhancement Correlates With Myocardial Conduction Velocity in Patients With Persistent Atrial Fibrillation.

Front Physiol 2020 12;11:570203. Epub 2020 Nov 12.

ElectroCardioMaths Programme of The Imperial Centre for Cardiac Engineering, Imperial College London, London, United Kingdom.

Background: Conduction velocity (CV) heterogeneity and myocardial fibrosis both promote re-entry, but the relationship between fibrosis as determined by left atrial (LA) late-gadolinium enhanced cardiac magnetic resonance imaging (LGE-CMRI) and CV remains uncertain.

Objective: Although average CV has been shown to correlate with regional LGE-CMRI in patients with persistent AF, we test the hypothesis that a localized relationship exists to underpin LGE-CMRI as a minimally invasive tool to map myocardial conduction properties for risk stratification and treatment guidance.

Method: 3D LA electroanatomic maps during LA pacing were acquired from eight patients with persistent AF following electrical cardioversion. Local CVs were computed using triads of concurrently acquired electrograms and were co-registered to allow correlation with LA wall intensities obtained from LGE-CMRI, quantified using normalized intensity (NI) and image intensity ratio (IIR). Association was evaluated using multilevel linear regression.

Results: An association between CV and LGE-CMRI intensity was observed at scales comparable to the size of a mapping electrode: -0.11 m/s per unit increase in NI ( < 0.001) and -0.96 m/s per unit increase in IIR ( < 0.001). The magnitude of this change decreased with larger measurement area. Reproducibility of the association was observed with NI, but not with IIR.

Conclusion: At clinically relevant spatial scales, comparable to area of a mapping catheter electrode, LGE-CMRI correlates with CV. Measurement scale is important in accurately quantifying the association of CV and LGE-CMRI intensity. Importantly, NI, but not IIR, accounts for changes in the dynamic range of CMRI and enables quantitative reproducibility of the association.
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http://dx.doi.org/10.3389/fphys.2020.570203DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7693630PMC
November 2020

Development of a pro-arrhythmic ex vivo intact human and porcine model: cardiac electrophysiological changes associated with cellular uncoupling.

Pflugers Arch 2020 10 1;472(10):1435-1446. Epub 2020 Sep 1.

Faculty of Medicine, National Heart and Lung Institute, Imperial College London, Hammersmith Campus, Du Cane Road, London, W12 0NN, UK.

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. A total of 1 mM of carbenoxolone was administered at 5 ml/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) increased between baseline and carbenoxolone (47.9 ± 4.1-67.2 ± 2.7 ms) indicating conduction slowing. The features with the largest percentage change between baseline and 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) - 20.9%. The physiological relevance of this methodological tool is that it provides a model to further investigate pharmacologically induced pro-arrhythmic substrates.
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http://dx.doi.org/10.1007/s00424-020-02446-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7476990PMC
October 2020

An audit of uncertainty in multi-scale cardiac electrophysiology models.

Philos Trans A Math Phys Eng Sci 2020 Jun 25;378(2173):20190335. Epub 2020 May 25.

Universitade Federal de Juiz de Fora, Juiz de Fora, Brazil.

Models of electrical activation and recovery in cardiac cells and tissue have become valuable research tools, and are beginning to be used in safety-critical applications including guidance for clinical procedures and for drug safety assessment. As a consequence, there is an urgent need for a more detailed and quantitative understanding of the ways that uncertainty and variability influence model predictions. In this paper, we review the sources of uncertainty in these models at different spatial scales, discuss how uncertainties are communicated across scales, and begin to assess their relative importance. We conclude by highlighting important challenges that continue to face the cardiac modelling community, identifying open questions, and making recommendations for future studies. This article is part of the theme issue 'Uncertainty quantification in cardiac and cardiovascular modelling and simulation'.
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http://dx.doi.org/10.1098/rsta.2019.0335DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7287340PMC
June 2020

Considering discrepancy when calibrating a mechanistic electrophysiology model.

Philos Trans A Math Phys Eng Sci 2020 Jun 25;378(2173):20190349. Epub 2020 May 25.

School of Mathematics and Statistics, University of Sheffield, Sheffield, UK.

Uncertainty quantification (UQ) is a vital step in using mathematical models and simulations to take decisions. The field of cardiac simulation has begun to explore and adopt UQ methods to characterize uncertainty in model inputs and how that propagates through to outputs or predictions; examples of this can be seen in the papers of this issue. In this review and perspective piece, we draw attention to an important and under-addressed source of uncertainty in our predictions-that of uncertainty in the model structure or the equations themselves. The difference between imperfect models and reality is termed , and we are often uncertain as to the size and consequences of this discrepancy. Here, we provide two examples of the consequences of discrepancy when calibrating models at the ion channel and action potential scales. Furthermore, we attempt to account for this discrepancy when calibrating and validating an ion channel model using different methods, based on modelling the discrepancy using Gaussian processes and autoregressive-moving-average models, then highlight the advantages and shortcomings of each approach. Finally, suggestions and lines of enquiry for future work are provided. This article is part of the theme issue 'Uncertainty quantification in cardiac and cardiovascular modelling and simulation'.
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http://dx.doi.org/10.1098/rsta.2019.0349DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7287333PMC
June 2020

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 2019 09 3;16(9):1357-1367. Epub 2019 Jun 3.

Imperial College Healthcare NHS Trust, Hammersmith Hospital, London, United Kingdom. Electronic address:

Background: Bipolar electrogram voltage during sinus rhythm (V) has been used as a surrogate for atrial fibrosis in guiding catheter ablation of persistent atrial fibrillation (AF), but the fixed rate and wavefront characteristics present during sinus rhythm may not accurately reflect underlying functional vulnerabilities responsible for AF maintenance.

Objective: The purpose of this study was determine whether, given adequate temporal sampling, the spatial distribution of mean AF voltage (V) better correlates with delayed-enhancement magnetic resonance imaging (MRI-DE)-detected atrial fibrosis than V.

Methods: AF was mapped (8 seconds) during index ablation for persistent AF (20 patients) using a 20-pole catheter (660 ± 28 points/map). After cardioversion, V was mapped (557 ± 326 points/map). Electroanatomic and MRI-DE maps were co-registered in 14 patients.

Results: The time course of V was assessed from 1-40 AF cycles (∼8 seconds) at 1113 locations. V stabilized with sampling >4 seconds (mean voltage error 0.05 mV). Paired point analysis of V from segments acquired 30 seconds apart (3667 sites; 15 patients) showed strong correlation (r = 0.95; P <.001). Delayed enhancement (DE) was assessed across the posterior left atrial (LA) wall, occupying 33% ± 13%. V distributions were (median [IQR]) 0.21 [0.14-0.35] mV in DE vs 0.52 [0.34-0.77] mV in non-DE regions. V distributions were 1.34 [0.65-2.48] mV in DE vs 2.37 [1.27-3.97] mV in non-DE. V threshold of 0.35 mV yielded sensitivity of 75% and specificity of 79% in detecting MRI-DE compared with 63% and 67%, respectively, for V (1.8-mV threshold) CONCLUSION: The 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.
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http://dx.doi.org/10.1016/j.hrthm.2019.05.032DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6722483PMC
September 2019

Determinants of new wavefront locations in cholinergic atrial fibrillation.

Europace 2018 Nov;20(suppl_3):iii3-iii15

LIRYC Electrophysiology and Heart Modeling Institute, Bordeaux Fondation, Avenue du Haut-Lévèque, Pessac, France.

Aims: Atrial fibrillation (AF) wavefront dynamics are complex and difficult to interpret, contributing to uncertainty about the mechanisms that maintain AF. We aimed to investigate the interplay between rotors, wavelets, and focal sources during fibrillation.

Methods And Results: Arrhythmia wavefront dynamics were analysed for four optically mapped canine cholinergic AF preparations. A bilayer computer model was tuned to experimental preparations, and varied to have (i) fibrosis in both layers or the epicardium only, (ii) different spatial acetylcholine distributions, (iii) different intrinsic action potential duration between layers, and (iv) varied interlayer connectivity. Phase singularities (PSs) were identified and tracked over time to identify rotational drivers. New focal wavefronts were identified using phase contours. Phase singularity density and new wavefront locations were calculated during AF. There was a single dominant mechanism for sustaining AF in each of the preparations, either a rotational driver or repetitive new focal wavefronts. High-density PS sites existed preferentially around the pulmonary vein junctions. Three of the four preparations exhibited stable preferential sites of new wavefronts. Computational simulations predict that only a small number of connections are functionally important in sustaining AF, with new wavefront locations determined by the interplay between fibrosis distribution, acetylcholine concentration, and heterogeneity in repolarization within layers.

Conclusion: We were able to identify preferential sites of new wavefront initiation and rotational activity, in order to determine the mechanisms sustaining AF. Electrical measurements should be interpreted differently according to whether they are endocardial or epicardial recordings.
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http://dx.doi.org/10.1093/europace/euy235DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6251188PMC
November 2018

Rethinking multiscale cardiac electrophysiology with machine learning and predictive modelling.

Comput Biol Med 2019 01 18;104:339-351. Epub 2018 Oct 18.

ElectroCardioMaths Group, Imperial College Centre for Cardiac Engineering, Imperial College London, London, UK; National Heart and Lung Institute, Imperial College London, South Kensington Campus, London, UK.

We review some of the latest approaches to analysing cardiac electrophysiology data using machine learning and predictive modelling. Cardiac arrhythmias, particularly atrial fibrillation, are a major global healthcare challenge. Treatment is often through catheter ablation, which involves the targeted localised destruction of regions of the myocardium responsible for initiating or perpetuating the arrhythmia. Ablation targets are either anatomically defined, or identified based on their functional properties as determined through the analysis of contact intracardiac electrograms acquired with increasing spatial density by modern electroanatomic mapping systems. While numerous quantitative approaches have been investigated over the past decades for identifying these critical curative sites, few have provided a reliable and reproducible advance in success rates. Machine learning techniques, including recent deep-learning approaches, offer a potential route to gaining new insight from this wealth of highly complex spatio-temporal information that existing methods struggle to analyse. Coupled with predictive modelling, these techniques offer exciting opportunities to advance the field and produce more accurate diagnoses and robust personalised treatment. We outline some of these methods and illustrate their use in making predictions from the contact electrogram and augmenting predictive modelling tools, both by more rapidly predicting future states of the system and by inferring the parameters of these models from experimental observations.
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http://dx.doi.org/10.1016/j.compbiomed.2018.10.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6334203PMC
January 2019

A novel approach to mapping the atrial ganglionated plexus network by generating a distribution probability atlas.

J Cardiovasc Electrophysiol 2018 12 5;29(12):1624-1634. Epub 2018 Oct 5.

Myocardial Function Section, Imperial Centre for Translational and Experimental Medicine, Imperial College London, London, UK.

Introduction: The ganglionated plexuses (GPs) of the intrinsic cardiac autonomic system are implicated in arrhythmogenesis. GP localization by stimulation of the epicardial fat pads to produce atrioventricular dissociating (AVD) effects is well described. We determined the anatomical distribution of the left atrial GPs that influence atrioventricular (AV) dissociation.

Methods And Results: High frequency stimulation was delivered through a Smart-Touch catheter in the left atrium of patients undergoing atrial fibrillation (AF) ablation. Three dimensional locations of points tested throughout the entire chamber were recorded on the CARTO™ system. Impact on the AV conduction was categorized as ventricular asystole, bradycardia, or no effect. CARTO maps were exported, registered, and transformed onto a reference left atrial geometry using a custom software, enabling data from multiple patients to be overlaid. In 28 patients, 2108 locations were tested and 283 sites (13%) demonstrated (AVD-GP) effects. There were 10 AVD-GPs (interquartile range, 11.5) per patient. Eighty percent (226) produced asystole and 20% (57) showed bradycardia. The distribution of the two groups was very similar. Highest probability of AVD-GPs (>20%) was identified in: inferoseptal portion (41%) and right inferior pulmonary vein base (30%) of the posterior wall, right superior pulmonary vein antrum (31%).

Conclusion: It is feasible to map the entire left atrium for AVD-GPs before AF ablation. Aggregated data from multiple patients, producing a distribution probability atlas of AVD-GPs, identified three regions with a higher likelihood for finding AVD-GPs and these matched the histological descriptions. This approach could be used to better characterize the autonomic network.
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http://dx.doi.org/10.1111/jce.13723DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6369684PMC
December 2018

Analytical approaches for myocardial fibrillation signals.

Comput Biol Med 2018 11 17;102:315-326. Epub 2018 Jul 17.

ElectroCardioMaths, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, United Kingdom. Electronic address:

Atrial and ventricular fibrillation are complex arrhythmias, and their underlying mechanisms remain widely debated and incompletely understood. This is partly because the electrical signals recorded during myocardial fibrillation are themselves complex and difficult to interpret with simple analytical tools. There are currently a number of analytical approaches to handle fibrillation data. Some of these techniques focus on mapping putative drivers of myocardial fibrillation, such as dominant frequency, organizational index, Shannon entropy and phase mapping. Other techniques focus on mapping the underlying myocardial substrate sustaining fibrillation, such as voltage mapping and complex fractionated electrogram mapping. In this review, we discuss these techniques, their application and their limitations, with reference to our experimental and clinical data. We also describe novel tools including a new algorithm to map microreentrant circuits sustaining fibrillation.
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http://dx.doi.org/10.1016/j.compbiomed.2018.07.008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6215772PMC
November 2018

Characterisation of re-entrant circuit (or rotational activity) in vitro using the HL1-6 myocyte cell line.

J Mol Cell Cardiol 2018 06 7;119:155-164. Epub 2018 May 7.

Myocardial Function, National Heart and Lung Institute, Imperial College London, London, UK. Electronic address:

Fibrillation is the most common arrhythmia observed in clinical practice. Understanding of the mechanisms underlying its initiation and maintenance remains incomplete. Functional re-entries are potential drivers of the arrhythmia. Two main concepts are still debated, the "leading circle" and the "spiral wave or rotor" theories. The homogeneous subclone of the HL1 atrial-derived cardiomyocyte cell line, HL1-6, spontaneously exhibits re-entry on a microscopic scale due to its slow conduction velocity and the presence of triggers, making it possible to examine re-entry at the cellular level. We therefore investigated the re-entry cores in cell monolayers through the use of fluorescence optical mapping at high spatiotemporal resolution in order to obtain insights into the mechanisms of re-entry. Re-entries in HL1-6 myocytes required at least two triggers and a minimum colony area to initiate (3.5 to 6.4 mm). After electrical activity was completely stopped and re-started by varying the extracellular K concentration, re-entries never returned to the same location while 35% of triggers re-appeared at the same position. A conduction delay algorithm also allows visualisation of the core of the re-entries. This work has revealed that the core of re-entries is conduction blocks constituted by lines and/or groups of cells rather than the round area assumed by the other concepts of functional re-entry. This highlights the importance of experimentation at the microscopic level in the study of re-entry mechanisms.
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http://dx.doi.org/10.1016/j.yjmcc.2018.05.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6004038PMC
June 2018

Concurrent micro- to macro-cardiac electrophysiology in myocyte cultures and human heart slices.

Sci Rep 2018 05 2;8(1):6947. Epub 2018 May 2.

Myocardial Function Section, National Heart and Lung Institute, Imperial College London, 4th floor Imperial Centre for Translational and Experimental Medicine, Hammersmith Campus, Du Cane Road, London, W12 0NN, UK.

The contact cardiac electrogram is derived from the extracellular manifestation of cellular action potentials and cell-to-cell communication. It is used to guide catheter based clinical procedures. Theoretically, the contact electrogram and the cellular action potential are directly related, and should change in conjunction with each other during arrhythmogenesis, however there is currently no methodology by which to concurrently record both electrograms and action potentials in the same preparation for direct validation of their relationships and their direct mechanistic links. We report a novel dual modality apparatus for concurrent electrogram and cellular action potential recording at a single cell level within multicellular preparations. We further demonstrate the capabilities of this system to validate the direct link between these two modalities of voltage recordings.
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http://dx.doi.org/10.1038/s41598-018-25170-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5932023PMC
May 2018

Spatial Resolution Requirements for Accurate Identification of Drivers of Atrial Fibrillation.

Circ Arrhythm Electrophysiol 2017 May;10(5):e004899

From the ElectroCardioMaths Programme (C.H.R., C.D.C., N.A.Q., P.B.L., P.K., N.S.P., F.S.N.), and the Department of Bioengineering (J.H.T.), Imperial College London, United Kingdom; IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France (J.D.B., E.J.V.); and Université de Bordeaux, IMB, UMR 5251, Talence, France (J.D.B., E.J.V.).

Background: Recent studies have demonstrated conflicting mechanisms underlying atrial fibrillation (AF), with the spatial resolution of data often cited as a potential reason for the disagreement. The purpose of this study was to investigate whether the variation in spatial resolution of mapping may lead to misinterpretation of the underlying mechanism in persistent AF.

Methods And Results: Simulations of rotors and focal sources were performed to estimate the minimum number of recording points required to correctly identify the underlying AF mechanism. The effects of different data types (action potentials and unipolar or bipolar electrograms) and rotor stability on resolution requirements were investigated. We also determined the ability of clinically used endocardial catheters to identify AF mechanisms using clinically recorded and simulated data. The spatial resolution required for correct identification of rotors and focal sources is a linear function of spatial wavelength (the distance between wavefronts) of the arrhythmia. Rotor localization errors are larger for electrogram data than for action potential data. Stationary rotors are more reliably identified compared with meandering trajectories, for any given spatial resolution. All clinical high-resolution multipolar catheters are of sufficient resolution to accurately detect and track rotors when placed over the rotor core although the low-resolution basket catheter is prone to false detections and may incorrectly identify rotors that are not present.

Conclusions: The spatial resolution of AF data can significantly affect the interpretation of the underlying AF mechanism. Therefore, the interpretation of human AF data must be taken in the context of the spatial resolution of the recordings.
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http://dx.doi.org/10.1161/CIRCEP.116.004899DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5434962PMC
May 2017

Rotor Tracking Using Phase of Electrograms Recorded During Atrial Fibrillation.

Ann Biomed Eng 2017 04 5;45(4):910-923. Epub 2016 Dec 5.

National Heart and Lung Institute, Imperial College London, 4th floor Imperial Centre for Translational and Experimental Medicine, Hammersmith Campus, Du Cane Road, London, W12 0NN, UK.

Extracellular electrograms recorded during atrial fibrillation (AF) are challenging to interpret due to the inherent beat-to-beat variability in amplitude and duration. Phase mapping represents these voltage signals in terms of relative position within the cycle, and has been widely applied to action potential and unipolar electrogram data of myocardial fibrillation. To date, however, it has not been applied to bipolar recordings, which are commonly acquired clinically. The purpose of this study is to present a novel algorithm for calculating phase from both unipolar and bipolar electrograms recorded during AF. A sequence of signal filters and processing steps are used to calculate phase from simulated, experimental, and clinical, unipolar and bipolar electrograms. The algorithm is validated against action potential phase using simulated data (trajectory centre error <0.8 mm); between experimental multi-electrode array unipolar and bipolar phase; and for wavefront identification in clinical atrial tachycardia. For clinical AF, similar rotational content (R  = 0.79) and propagation maps (median correlation 0.73) were measured using either unipolar or bipolar recordings. The algorithm is robust, uses standard signal processing techniques, and accurately quantifies AF wavefronts and sources. Identifying critical sources, such as rotors, in AF, may allow for more accurate targeting of ablation therapy and improved patient outcomes.
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http://dx.doi.org/10.1007/s10439-016-1766-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5362653PMC
April 2017

A technique for visualising three-dimensional left atrial cardiac activation data in two dimensions with minimal distance distortion.

Annu Int Conf IEEE Eng Med Biol Soc 2015 ;2015:7296-9

Electro-anatomic mapping and medical imaging systems, used during clinical procedures for treatment of atrial arrhythmias, frequently record and display measurements on an anatomical surface of the left atrium. As such, obtaining a complete picture of activation necessitates simultaneous views from multiple angles. In addition, post-processing of three-dimensional surface data is challenging, since algorithms are typically applicable to planar or volumetric data. We applied a surface flattening methodology to medical imaging data and electro-anatomic mapping data to generate a two-dimensional representation that best preserves distances, since the calculation of many clinically relevant metrics, including conduction velocity and rotor trajectory identification require an accurate representation of distance. Distance distortions were small and improved upon exclusion of the pulmonary veins. The technique is demonstrated using maps of local activation time, based on clinical data, and plotting rotor-core trajectories, using simulated data.
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http://dx.doi.org/10.1109/EMBC.2015.7320076DOI Listing
September 2016

Automated fiducial point selection for reducing registration error in the co-localisation of left atrium electroanatomic and imaging data.

Annu Int Conf IEEE Eng Med Biol Soc 2015 ;2015:1989-92

Registration of electroanatomic surfaces and segmented images for the co-localisation of structural and functional data typically requires the manual selection of fiducial points, which are used to initialise automated surface registration. The identification of equivalent points on geometric features by the human eye is heavily subjective, and error in their selection may lead to distortion of the transformed surface and subsequently limit the accuracy of data co-localisation. We propose that the manual trimming of the pulmonary veins through the region of greatest geometrical curvature, coupled with an automated angle-based fiducial-point selection algorithm, significantly reduces target registration error compared with direct manual selection of fiducial points.
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http://dx.doi.org/10.1109/EMBC.2015.7318775DOI Listing
September 2016

A software platform for the comparative analysis of electroanatomic and imaging data including conduction velocity mapping.

Annu Int Conf IEEE Eng Med Biol Soc 2014 ;2014:1591-4

Electroanatomic mapping systems collect increasingly large quantities of spatially-distributed electrical data which may be potentially further scrutinized post-operatively to expose mechanistic properties which sustain and perpetuate atrial fibrillation. We describe a modular software platform, developed to post-process and rapidly analyse data exported from electroanatomic mapping systems using a range of existing and novel algorithms. Imaging data highlighting regions of scar can also be overlaid for comparison. In particular, we describe the conduction velocity (CV) mapping algorithm used to highlight wavefront behaviour. CV was found to be particularly sensitive to the spatial distribution of the triangulation points and corresponding activation times. A set of geometric conditions were devised for selecting suitable triangulations of the electrogram set for generating CV maps.
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http://dx.doi.org/10.1109/EMBC.2014.6943908DOI Listing
July 2016

An automated algorithm for determining conduction velocity, wavefront direction and origin of focal cardiac arrhythmias using a multipolar catheter.

Annu Int Conf IEEE Eng Med Biol Soc 2014 ;2014:1583-6

Determining locations of focal arrhythmia sources and quantifying myocardial conduction velocity (CV) are two major challenges in clinical catheter ablation cases. CV, wave-front direction and focal source location can be estimated from multipolar catheter data, but currently available methods are time-consuming, limited to specific electrode configurations, and can be inaccurate. We developed automated algorithms to rapidly identify CV from multipolar catheter data with any arrangement of electrodes, whilst providing estimates of wavefront direction and focal source position, which can guide the catheter towards a focal arrhythmic source. We validated our methods using simulations on realistic human left atrial geometry. We subsequently applied them to clinically-acquired intracardiac electrogram data, where CV and wavefront direction were accurately determined in all cases, whilst focal source locations were correctly identified in 2/3 cases. Our novel automated algorithms can potentially be used to guide ablation of focal arrhythmias in real-time in cardiac catheter laboratories.
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http://dx.doi.org/10.1109/EMBC.2014.6943906DOI Listing
July 2016

High-order spectral/ element discretisation for reaction-diffusion problems on surfaces: Application to cardiac electrophysiology.

J Comput Phys 2014 Jan;257(PA):813-829

Department of Aeronautics, Imperial College London, London, UK.

We present a numerical discretisation of an embedded two-dimensional manifold using high-order continuous Galerkin spectral/ elements, which provide exponential convergence of the solution with increasing polynomial order, while retaining geometric flexibility in the representation of the domain. Our work is motivated by applications in cardiac electrophysiology where sharp gradients in the solution benefit from the high-order discretisation, while the computational cost of anatomically-realistic models can be significantly reduced through the surface representation and use of high-order methods. We describe and validate our discretisation and provide a demonstration of its application to modelling electrochemical propagation across a human left atrium.
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http://dx.doi.org/10.1016/j.jcp.2013.10.019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3991332PMC
January 2014