1
|
Tonko J, Ehnesh M, Vigmond E, Chow A, Roney C, Lambiase PD. Omnipolar Conduction Velocity Mapping for Ventricular Substrate Characterisation: Impact of CV Estimation Method and EGM Type on In-Vivo Conduction Velocity Measurements. Heart Rhythm 2024:S1547-5271(24)02674-2. [PMID: 38851622 DOI: 10.1016/j.hrthm.2024.05.061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 05/29/2024] [Accepted: 05/30/2024] [Indexed: 06/10/2024]
Abstract
BACKGROUND Areas of abnormal and/or heterogenous conduction velocity (CV) are important ablation targets for ventricular tachycardias. Yet, precise assessment of CV in clinical contact mapping remains challenging. Numerous different CV estimation methods have been proposed. OBJECTIVE To compare the automated LAT-independent omnipolar-based CV estimation method termed "Wave Speed" (WS) with four established LAT-based methods and formally establish the quantitative differences between them. METHODS High-density contact maps in patients with structurally normal hearts during sinus rhythm and ventricular ectopy (VE) were retrospectively analysed. CV was assessed and compared using five methods: 1.Omnipolar WS, 2.Gradient method, 3.Planar wavefront fitting (PWF) 4.Circular wavefront fitting (CWF), 5.Radial basis function (RBF). CV variations based on EGM type (uni-/bi-/omnipolar), catheter movement and surrogate markers for catheter contact were analysed. RESULTS 23 patients (47.8% male, 45.7±17.3 years) with 22 sinus (11 LV/11 RV) and 16 VE maps (9 LV/7 RV) were included. WS algorithm yielded statistically significant higher CV estimates in SR (mean 1.41 ±0.18m/s) and VE maps (mean 1.23±0.18m/s) compared to all LAT-based estimation methods with absolute differences ranging from 0.1m/s to 0.81m/s. Median pointwise differences in SR and VE between WS and LAT-based methods were high, ranging from 0.55±0.15m/s (WS vs. PWF) to 0.67±0.16m/s (WS vs. RBF). For LAT-based methods, use of unipolar EGMs yielded significantly higher CV estimates than bi-/omnipolar EGMs in sinus. CONCLUSION The CV estimation method has an important, statistically significant impact on ventricular CV measurements. Future work will focus on how these differences impact identification of pathological conduction slowing in scar-related substrate.
Collapse
Affiliation(s)
- Johanna Tonko
- Institute for Cardiovascular Science, University College London, WC1E 6JF, UK,.
| | - Mahmoud Ehnesh
- School of Engineering and Materials Science, Queen Mary University of London, London E1 4NS, UK
| | - Edmon Vigmond
- IHU Liryc, Electrophysiology and Heart Modelling Institute, Fondation Bordeaux Universite, France
| | - Anthony Chow
- Barts Heart Centre, St. Bartholomew's Hospital, London, UK
| | - Caroline Roney
- School of Engineering and Materials Science, Queen Mary University of London, London E1 4NS, UK
| | - Pier D Lambiase
- Institute for Cardiovascular Science, University College London, WC1E 6JF, UK,; Barts Heart Centre, St. Bartholomew's Hospital, London, UK
| |
Collapse
|
2
|
Kong X, Ravikumar V, Mulpuru SK, Roukoz H, Tolkacheva EG. A Data-Driven Preprocessing Framework for Atrial Fibrillation Intracardiac Electrocardiogram Analysis. ENTROPY (BASEL, SWITZERLAND) 2023; 25:332. [PMID: 36832698 PMCID: PMC9955244 DOI: 10.3390/e25020332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 02/03/2023] [Accepted: 02/09/2023] [Indexed: 06/18/2023]
Abstract
Atrial Fibrillation (AF) is the most common cardiac arrhythmia. Signal-processing approaches are widely used for the analysis of intracardiac electrograms (iEGMs), which are collected during catheter ablation from patients with AF. In order to identify possible targets for ablation therapy, dominant frequency (DF) is widely used and incorporated in electroanatomical mapping systems. Recently, a more robust measure, multiscale frequency (MSF), for iEGM data analysis was adopted and validated. However, before completing any iEGM analysis, a suitable bandpass (BP) filter must be applied to remove noise. Currently, no clear guidelines for BP filter characteristics exist. The lower bound of the BP filter is usually set to 3-5 Hz, while the upper bound (BP¯th) of the BP filter varies from 15 Hz to 50 Hz according to many researchers. This large range of BP¯th subsequently affects the efficiency of further analysis. In this paper, we aimed to develop a data-driven preprocessing framework for iEGM analysis, and validate it based on DF and MSF techniques. To achieve this goal, we optimized the BP¯th using a data-driven approach (DBSCAN clustering) and demonstrated the effects of different BP¯th on subsequent DF and MSF analysis of clinically recorded iEGMs from patients with AF. Our results demonstrated that our preprocessing framework with BP¯th = 15 Hz has the best performance in terms of the highest Dunn index. We further demonstrated that the removal of noisy and contact-loss leads is necessary for performing correct data iEGMs data analysis.
Collapse
Affiliation(s)
- Xiangzhen Kong
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455, USA
| | - Vasanth Ravikumar
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455, USA
| | - Siva K. Mulpuru
- Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN 55905, USA
| | - Henri Roukoz
- Division of Cardiology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Elena G. Tolkacheva
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, USA
- Lillehei Heart Institute, University of Minnesota, Minneapolis, MN 55455, USA
- Institute for Engineering in Medicine, University of Minnesota, Minneapolis, MN 55455, USA
| |
Collapse
|
3
|
Santurri M, Bonga J, Schmid M, Cauti FM, Solimene F, Polselli M, Bura M, Piccolo F, Malacrida M, Pelargonio G, Spera FR, Bianchi S, Rossi P. Automated conduction velocity estimation based on isochronal activation of heart chambers. J Interv Card Electrophysiol 2022; 66:647-660. [PMID: 36178554 PMCID: PMC10066170 DOI: 10.1007/s10840-022-01339-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 08/09/2022] [Indexed: 10/14/2022]
Abstract
BACKGROUND Spatial differences in conduction velocity (CV) are critical for cardiac arrhythmias induction. We propose a method for an automated CV calculation to identify areas of slower conduction during cardiac arrhythmias and sinus rhythm. METHODS Color-coded representations of the isochronal activation map using data coming from the RHYTHMIA™ Mapping System were reproduced by applying a temporal isochronal window at 20 ms. Geodesic distances of the 3D mesh were calculated using an algorithm selecting the minimum distance pathway (MDP). The CV estimation was performed considering points on the boundary of two spatially and temporally adjacent isochrones. For each of the boundary points of a given isochrone, the nearest boundary point of the consecutive isochrone was chosen, the MDP was evaluated, and a map of CV was created. The proposed method has been applied to a population of 29 patients. RESULTS In all cases of perimitral atrial flutter (16 pts out of 29 (55%)), areas with significantly low CV (< 30 cm/s) were found. Half of the cases present regions with low CV located in the anterior wall. No case with low CV at the so-called LA isthmus was observed. Right atrial maps during common atrial flutters showed low CV areas mainly located in the inferior inter-atrial septum. No areas of low CV were observed in subjects without a history of atrial arrhythmia while pts affected by paroxysmal AF showed areas with a limited extension of low CV. CONCLUSIONS The proposed software for automated CV estimation allows the identification of low CV areas, potentially helping electrophysiologists to plan the ablation strategy.
Collapse
Affiliation(s)
- Michela Santurri
- BioLab3, Biomedical Engineering Laboratory, Roma Tre University, Rome, Italy
| | - Jennifer Bonga
- BioLab3, Biomedical Engineering Laboratory, Roma Tre University, Rome, Italy
| | - Maurizio Schmid
- BioLab3, Biomedical Engineering Laboratory, Roma Tre University, Rome, Italy
| | - Filippo Maria Cauti
- Arrhythmology Unit, Hospital Fatebenefratelli Isola Tiberina-Gemelli Isola, Rome, Italy
| | - Francesco Solimene
- Electrophysiology Unit, Clinica Montevergine, Mercogliano, Avellino, Italy
| | - Marco Polselli
- Arrhythmology Unit, Hospital Fatebenefratelli Isola Tiberina-Gemelli Isola, Rome, Italy
| | | | | | | | - Gemma Pelargonio
- Cardiovascular Sciences Department, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Francesco Raffaele Spera
- Cardiovascular Sciences Department, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Stefano Bianchi
- Arrhythmology Unit, Hospital Fatebenefratelli Isola Tiberina-Gemelli Isola, Rome, Italy
| | - Pietro Rossi
- Arrhythmology Unit, Hospital Fatebenefratelli Isola Tiberina-Gemelli Isola, Rome, Italy.
| |
Collapse
|
4
|
Atrial conduction velocity mapping: clinical tools, algorithms and approaches for understanding the arrhythmogenic substrate. Med Biol Eng Comput 2022; 60:2463-2478. [PMID: 35867323 PMCID: PMC9365755 DOI: 10.1007/s11517-022-02621-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 06/07/2022] [Indexed: 11/02/2022]
Abstract
Characterizing patient-specific atrial conduction properties is important for understanding arrhythmia drivers, for predicting potential arrhythmia pathways, and for personalising treatment approaches. One metric that characterizes the health of the myocardial substrate is atrial conduction velocity, which describes the speed and direction of propagation of the electrical wavefront through the myocardium. Atrial conduction velocity mapping algorithms are under continuous development in research laboratories and in industry. In this review article, we give a broad overview of different categories of currently published methods for calculating CV, and give insight into their different advantages and disadvantages overall. We classify techniques into local, global, and inverse methods, and discuss these techniques with respect to their faithfulness to the biophysics, incorporation of uncertainty quantification, and their ability to take account of the atrial manifold.
Collapse
|
5
|
Siles-Paredes JG, Crowley CJ, Fenton FH, Bhatia N, Iravanian S, Sandoval I, Pollnow S, Dössel O, Salinet J, Uzelac I. Circle Method for Robust Estimation of Local Conduction Velocity High-Density Maps From Optical Mapping Data: Characterization of Radiofrequency Ablation Sites. Front Physiol 2022; 13:794761. [PMID: 36035466 PMCID: PMC9417315 DOI: 10.3389/fphys.2022.794761] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 06/15/2022] [Indexed: 01/10/2023] Open
Abstract
Conduction velocity (CV) slowing is associated with atrial fibrillation (AF) and reentrant ventricular tachycardia (VT). Clinical electroanatomical mapping systems used to localize AF or VT sources as ablation targets remain limited by the number of measuring electrodes and signal processing methods to generate high-density local activation time (LAT) and CV maps of heterogeneous atrial or trabeculated ventricular endocardium. The morphology and amplitude of bipolar electrograms depend on the direction of propagating electrical wavefront, making identification of low-amplitude signal sources commonly associated with fibrotic area difficulty. In comparison, unipolar electrograms are not sensitive to wavefront direction, but measurements are susceptible to distal activity. This study proposes a method for local CV calculation from optical mapping measurements, termed the circle method (CM). The local CV is obtained as a weighted sum of CV values calculated along different chords spanning a circle of predefined radius centered at a CV measurement location. As a distinct maximum in LAT differences is along the chord normal to the propagating wavefront, the method is adaptive to the propagating wavefront direction changes, suitable for electrical conductivity characterization of heterogeneous myocardium. In numerical simulations, CM was validated characterizing modeled ablated areas as zones of distinct CV slowing. Experimentally, CM was used to characterize lesions created by radiofrequency ablation (RFA) on isolated hearts of rats, guinea pig, and explanted human hearts. To infer the depth of RFA-created lesions, excitation light bands of different penetration depths were used, and a beat-to-beat CV difference analysis was performed to identify CV alternans. Despite being limited to laboratory research, studies based on CM with optical mapping may lead to new translational insights into better-guided ablation therapies.
Collapse
Affiliation(s)
- Jimena G. Siles-Paredes
- Graduate Program in Biotechnoscience, Federal University of ABC, São Paulo, Brazil
- HEartLab, Federal University of ABC, São Paulo, Brazil
- *Correspondence: Jimena G. Siles-Paredes,
| | | | - Flavio H. Fenton
- Georgia Institute of Technology, School of Physics, Atlanta, GA, United States
| | - Neal Bhatia
- Division of Cardiology, Section of Electrophysiology, Emory University Hospital, Atlanta, GA, United States
| | - Shahriar Iravanian
- Division of Cardiology, Section of Electrophysiology, Emory University Hospital, Atlanta, GA, United States
| | | | - Stefan Pollnow
- Karlsruhe Institute of Technology (KIT)/Institute of Biomedical Engineering, Karlsruhe, Germany
| | - Olaf Dössel
- Karlsruhe Institute of Technology (KIT)/Institute of Biomedical Engineering, Karlsruhe, Germany
| | - João Salinet
- Graduate Program in Biotechnoscience, Federal University of ABC, São Paulo, Brazil
- HEartLab, Federal University of ABC, São Paulo, Brazil
| | - Ilija Uzelac
- Georgia Institute of Technology, School of Physics, Atlanta, GA, United States
| |
Collapse
|
6
|
A Review on Atrial Fibrillation (Computer Simulation and Clinical Perspectives). HEARTS 2022. [DOI: 10.3390/hearts3010005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Atrial fibrillation (AF), a heart condition, has been a well-researched topic for the past few decades. This multidisciplinary field of study deals with signal processing, finite element analysis, mathematical modeling, optimization, and clinical procedure. This article is focused on a comprehensive review of journal articles published in the field of AF. Topics from the age-old fundamental concepts to specialized modern techniques involved in today’s AF research are discussed. It was found that a lot of research articles have already been published in modeling and simulation of AF. In comparison to that, the diagnosis and post-operative procedures for AF patients have not yet been totally understood or explored by the researchers. The simulation and modeling of AF have been investigated by many researchers in this field. Cellular model, tissue model, and geometric model among others have been used to simulate AF. Due to a very complex nature, the causes of AF have not been fully perceived to date, but the simulated results are validated with real-life patient data. Many algorithms have been proposed to detect the source of AF in human atria. There are many ablation strategies for AF patients, but the search for more efficient ablation strategies is still going on. AF management for patients with different stages of AF has been discussed in the literature as well but is somehow limited mostly to the patients with persistent AF. The authors hope that this study helps to find existing research gaps in the analysis and the diagnosis of AF.
Collapse
|
7
|
Masè M, Cristoforetti A, Del Greco M, Ravelli F. A Divergence-Based Approach for the Identification of Atrial Fibrillation Focal Drivers From Multipolar Mapping: A Computational Study. Front Physiol 2021; 12:749430. [PMID: 35002755 PMCID: PMC8740027 DOI: 10.3389/fphys.2021.749430] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 11/30/2021] [Indexed: 11/13/2022] Open
Abstract
The expanding role of catheter ablation of atrial fibrillation (AF) has stimulated the development of novel mapping strategies to guide the procedure. We introduce a novel approach to characterize wave propagation and identify AF focal drivers from multipolar mapping data. The method reconstructs continuous activation patterns in the mapping area by a radial basis function (RBF) interpolation of multisite activation time series. Velocity vector fields are analytically determined, and the vector field divergence is used as a marker of focal drivers. The method was validated in a tissue patch cellular automaton model and in an anatomically realistic left atrial (LA) model with Courtemanche-Ramirez-Nattel ionic dynamics. Divergence analysis was effective in identifying focal drivers in a complex simulated AF pattern. Localization was reliable even with consistent reduction (47%) in the number of mapping points and in the presence of activation time misdetections (noise <10% of the cycle length). Proof-of-concept application of the method to human AF mapping data showed that divergence analysis consistently detected focal activation in the pulmonary veins and LA appendage area. These results suggest the potential of divergence analysis in combination with multipolar mapping to identify AF critical sites. Further studies on large clinical datasets may help to assess the clinical feasibility and benefit of divergence analysis for the optimization of ablation treatment.
Collapse
Affiliation(s)
- Michela Masè
- Laboratory of Biophysics and Translational Cardiology, Department of Cellular, Computational and Integrative Biology – CIBIO, University of Trento, Trento, Italy
- Institute of Mountain Emergency Medicine, EURAC Research, Bolzano, Italy
| | - Alessandro Cristoforetti
- Laboratory of Biophysics and Translational Cardiology, Department of Cellular, Computational and Integrative Biology – CIBIO, University of Trento, Trento, Italy
| | - Maurizio Del Greco
- Division of Cardiology, Santa Maria del Carmine Hospital, Rovereto, Italy
| | - Flavia Ravelli
- Laboratory of Biophysics and Translational Cardiology, Department of Cellular, Computational and Integrative Biology – CIBIO, University of Trento, Trento, Italy
- CISMed – Centre for Medical Sciences, University of Trento, Trento, Italy
| |
Collapse
|
8
|
Roney CH, Sillett C, Whitaker J, Lemus JAS, Sim I, Kotadia I, O'Neill M, Williams SE, Niederer SA. Applications of multimodality imaging for left atrial catheter ablation. Eur Heart J Cardiovasc Imaging 2021; 23:31-41. [PMID: 34747450 PMCID: PMC8685603 DOI: 10.1093/ehjci/jeab205] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Indexed: 11/13/2022] Open
Abstract
Atrial arrhythmias, including atrial fibrillation and atrial flutter, may be treated through catheter ablation. The process of atrial arrhythmia catheter ablation, which includes patient selection, pre-procedural planning, intra-procedural guidance, and post-procedural assessment, is typically characterized by the use of several imaging modalities to sequentially inform key clinical decisions. Increasingly, advanced imaging modalities are processed via specialized image analysis techniques and combined with intra-procedural electrical measurements to inform treatment approaches. Here, we review the use of multimodality imaging for left atrial ablation procedures. The article first outlines how imaging modalities are routinely used in the peri-ablation period. We then describe how advanced imaging techniques may inform patient selection for ablation and ablation targets themselves. Ongoing research directions for improving catheter ablation outcomes by using imaging combined with advanced analyses for personalization of ablation targets are discussed, together with approaches for their integration in the standard clinical environment. Finally, we describe future research areas with the potential to improve catheter ablation outcomes.
Collapse
Affiliation(s)
- Caroline H Roney
- School of Biomedical Engineering and Imaging Sciences, King's College, London, UK
| | - Charles Sillett
- School of Biomedical Engineering and Imaging Sciences, King's College, London, UK
| | - John Whitaker
- School of Biomedical Engineering and Imaging Sciences, King's College, London, UK
| | | | - Iain Sim
- School of Biomedical Engineering and Imaging Sciences, King's College, London, UK
| | - Irum Kotadia
- School of Biomedical Engineering and Imaging Sciences, King's College, London, UK
| | - Mark O'Neill
- School of Biomedical Engineering and Imaging Sciences, King's College, London, UK
| | - Steven E Williams
- School of Biomedical Engineering and Imaging Sciences, King's College, London, UK
- Centre for Cardiovascular Science, The University of Edinburgh, Scotland, UK
| | - Steven A Niederer
- School of Biomedical Engineering and Imaging Sciences, King's College, London, UK
| |
Collapse
|
9
|
de Groot NMS, Shah D, Boyle PM, Anter E, Clifford GD, Deisenhofer I, Deneke T, van Dessel P, Doessel O, Dilaveris P, Heinzel FR, Kapa S, Lambiase PD, Lumens J, Platonov PG, Ngarmukos T, Martinez JP, Sanchez AO, Takahashi Y, Valdigem BP, van der Veen AJ, Vernooy K, Casado-Arroyo Co-Chair R. Critical appraisal of technologies to assess electrical activity during atrial fibrillation: a position paper from the European Heart Rhythm Association and European Society of Cardiology Working Group on eCardiology in collaboration with the Heart Rhythm Society, Asia Pacific Heart Rhythm Society, Latin American Heart Rhythm Society and Computing in Cardiology. Europace 2021; 24:313-330. [PMID: 34878119 DOI: 10.1093/europace/euab254] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 09/21/2021] [Indexed: 11/13/2022] Open
Abstract
We aim to provide a critical appraisal of basic concepts underlying signal recording and processing technologies applied for (i) atrial fibrillation (AF) mapping to unravel AF mechanisms and/or identifying target sites for AF therapy and (ii) AF detection, to optimize usage of technologies, stimulate research aimed at closing knowledge gaps, and developing ideal AF recording and processing technologies. Recording and processing techniques for assessment of electrical activity during AF essential for diagnosis and guiding ablative therapy including body surface electrocardiograms (ECG) and endo- or epicardial electrograms (EGM) are evaluated. Discussion of (i) differences in uni-, bi-, and multi-polar (omnipolar/Laplacian) recording modes, (ii) impact of recording technologies on EGM morphology, (iii) global or local mapping using various types of EGM involving signal processing techniques including isochronal-, voltage- fractionation-, dipole density-, and rotor mapping, enabling derivation of parameters like atrial rate, entropy, conduction velocity/direction, (iv) value of epicardial and optical mapping, (v) AF detection by cardiac implantable electronic devices containing various detection algorithms applicable to stored EGMs, (vi) contribution of machine learning (ML) to further improvement of signals processing technologies. Recording and processing of EGM (or ECG) are the cornerstones of (body surface) mapping of AF. Currently available AF recording and processing technologies are mainly restricted to specific applications or have technological limitations. Improvements in AF mapping by obtaining highest fidelity source signals (e.g. catheter-electrode combinations) for signal processing (e.g. filtering, digitization, and noise elimination) is of utmost importance. Novel acquisition instruments (multi-polar catheters combined with improved physical modelling and ML techniques) will enable enhanced and automated interpretation of EGM recordings in the near future.
Collapse
Affiliation(s)
- Natasja M S de Groot
- Department of Cardiology, Erasmus University Medical Centre, Rotterdam, Delft University of Technology, Delft the Netherlands
| | - Dipen Shah
- Cardiology Service, University Hospitals Geneva, Geneva, Switzerland
| | - Patrick M Boyle
- Department of Bioengineering, University of Washington, Seattle, Washington, USA
| | - Elad Anter
- Cardiac Electrophysiology Section, Department of Cardiovascular Medicine, Cleveland Clinic, Cleveland, Ohio, USA
| | - Gari D Clifford
- Department of Biomedical Informatics, Emory University, Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, USA
| | - Isabel Deisenhofer
- Department of Electrophysiology, German Heart Center Munich and Technical University of Munich, Munich, Germany
| | - Thomas Deneke
- Department of Cardiology, Rhon-klinikum Campus Bad Neustadt, Germany
| | - Pascal van Dessel
- Department of Cardiology, Medisch Spectrum Twente, Twente, the Netherlands
| | - Olaf Doessel
- Karlsruher Institut für Technologie (KIT), Karlsruhe, Germany
| | - Polychronis Dilaveris
- 1st University Department of Cardiology, National & Kapodistrian University of Athens School of Medicine, Hippokration Hospital, Athens, Greece
| | - Frank R Heinzel
- Department of Internal Medicine and Cardiology, Charité-Universitätsmedizin Berlin, Campus Virchow-Klinikum and DZHK (German Centre for Cardiovascular Research), Berlin, Germany
| | - Suraj Kapa
- Department of Cardiology, Mayo Clinic, Rochester, USA
| | | | - Joost Lumens
- Cardiovascular Research Institute Maastricht (CARIM) Maastricht University, Maastricht, the Netherlands
| | - Pyotr G Platonov
- Department of Cardiology, Clinical Sciences, Lund University, Lund, Sweden
| | - Tachapong Ngarmukos
- Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Juan Pablo Martinez
- Aragon Institute of Engineering Research/IIS-Aragon and University of Zaragoza, Zaragoza, Spain, CIBER Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Zaragoza, Spain
| | - Alejandro Olaya Sanchez
- Department of Cardiology, Hospital San José, Fundacion Universitaia de Ciencas de la Salud, Bogota, Colombia
| | - Yoshihide Takahashi
- Department of Cardiovascular Medicine, Tokyo Medical and Dental University, Tokyo, Japan
| | - Bruno P Valdigem
- Department of Cardiology, Hospital Rede D'or São Luiz, hospital Albert einstein and Dante pazzanese heart institute, São Paulo, Brasil
| | - Alle-Jan van der Veen
- Department Circuits and Systems, Delft University of Technology, Delft, the Netherlands
| | - Kevin Vernooy
- Department of Cardiology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Centre, Maastricht, the Netherlands
| | | | | |
Collapse
|
10
|
Irakoze É, Jacquemet V. Multiparameter optimization of nonuniform passive diffusion properties for creating coarse-grained equivalent models of cardiac propagation. Comput Biol Med 2021; 138:104863. [PMID: 34562679 DOI: 10.1016/j.compbiomed.2021.104863] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 09/06/2021] [Accepted: 09/07/2021] [Indexed: 11/30/2022]
Abstract
The arrhythmogenic role of discrete cardiac propagation may be assessed by comparing discrete (fine-grained) and equivalent continuous (coarse-grained) models. We aim to develop an optimization algorithm for estimating the smooth conductivity field that best reproduces the diffusion properties of a given discrete model. Our algorithm iteratively adjusts local conductivity of the coarse-grained continuous model by simulating passive diffusion from white noise initial conditions during 3-10 ms and computing the root mean square error with respect to the discrete model. The coarse-grained conductivity field was interpolated from up to 300 evenly spaced control points. We derived an approximate formula for the gradient of the cost function that required (in two dimensions) only two additional simulations per iteration regardless of the number of estimated parameters. Conjugate gradient solver facilitated simultaneous optimization of multiple conductivity parameters. The method was tested in rectangular anisotropic tissues with uniform and nonuniform conductivity (slow regions with sinusoidal profile) and random diffuse fibrosis, as well as in a monolayer interconnected cable model of the left atrium with spatially-varying fibrosis density. Comparison of activation maps served as validation. The results showed that after convergence the errors in activation time were < 1 ms for rectangular geometries and 1-3 ms in the atrial model. Our approach based on the comparison of passive properties (<10 ms simulation) avoids performing active propagation simulations (>100 ms) at each iteration while reproducing activation maps, with possible applications to investigating the impact of microstructure on arrhythmias.
Collapse
Affiliation(s)
- Éric Irakoze
- Pharmacology and Physiology Department, Institute of Biomedical Engineering, Université de Montréal, Montreal, QC, H3T 1J4, Canada; Hôpital Du Sacré-Cœur de Montréal, Research Center, 5400 Boul. Gouin Ouest, Montreal, QC, H4J 1C5, Canada
| | - Vincent Jacquemet
- Pharmacology and Physiology Department, Institute of Biomedical Engineering, Université de Montréal, Montreal, QC, H3T 1J4, Canada; Hôpital Du Sacré-Cœur de Montréal, Research Center, 5400 Boul. Gouin Ouest, Montreal, QC, H4J 1C5, Canada.
| |
Collapse
|
11
|
van Schie MS, Heida A, Taverne YJHJ, Bogers AJJC, de Groot NMS. Identification of local atrial conduction heterogeneities using high-density conduction velocity estimation. Europace 2021; 23:1815-1825. [PMID: 33970234 PMCID: PMC8576284 DOI: 10.1093/europace/euab088] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 03/29/2021] [Indexed: 12/04/2022] Open
Abstract
Aims Accurate determination of intra-atrial conduction velocity (CV) is essential to identify arrhythmogenic areas. The most optimal, commonly used, estimation methodology to measure conduction heterogeneity, including finite differences (FiD), polynomial surface fitting (PSF), and a novel technique using discrete velocity vectors (DVV), has not been determined. We aim (i) to identify the most suitable methodology to unravel local areas of conduction heterogeneities using high-density CV estimation techniques, (ii) to quantify intra-atrial differences in CV, and (iii) to localize areas of CV slowing associated with paroxysmal atrial fibrillation (PAF). Methods and results Intra-operative epicardial mapping (>5000 sites, interelectrode distances 2 mm) of the right and left atrium and Bachmann’s bundle (BB) was performed during sinus rhythm (SR) in 412 patients with or without PAF. The median atrial CV estimated using the DVV, PSF, and FiD techniques was 90.0 (62.4–116.8), 92.0 (70.6–123.2), and 89.4 (62.5–126.5) cm/s, respectively. The largest difference in CV estimates was found between PSF and DVV which was caused by smaller CV magnitudes detected only by the DVV technique. Using DVV, a lower CV at BB was found in PAF patients compared with those without atrial fibrillation (AF) [79.1 (72.2–91.2) vs. 88.3 (79.3–97.2) cm/s; P < 0.001]. Conclusions Areas of local conduction heterogeneities were most accurately identified using the DVV technique, whereas PSF and FiD techniques smoothen wavefront propagation thereby masking local areas of conduction slowing. Comparing patients with and without AF, slower wavefront propagation during SR was found at BB in PAF patients, indicating structural remodelling.
Collapse
Affiliation(s)
- Mathijs S van Schie
- Unit Translational Electrophysiology, Department of Cardiology, Erasmus Medical Centre, Dr. Molewaterplein 40, 3015GD Rotterdam, the Netherlands
| | - Annejet Heida
- Unit Translational Electrophysiology, Department of Cardiology, Erasmus Medical Centre, Dr. Molewaterplein 40, 3015GD Rotterdam, the Netherlands
| | - Yannick J H J Taverne
- Department of Cardiothoracic Surgery, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - Ad J J C Bogers
- Department of Cardiothoracic Surgery, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - Natasja M S de Groot
- Unit Translational Electrophysiology, Department of Cardiology, Erasmus Medical Centre, Dr. Molewaterplein 40, 3015GD Rotterdam, the Netherlands
| |
Collapse
|
12
|
Koneshloo A, Du D, Du Y. An Uncertainty Modeling Framework for Intracardiac Electrogram Analysis. Bioengineering (Basel) 2020; 7:E62. [PMID: 32604784 PMCID: PMC7355499 DOI: 10.3390/bioengineering7020062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 06/22/2020] [Accepted: 06/24/2020] [Indexed: 11/16/2022] Open
Abstract
Intracardiac electrograms (EGMs) are electrical signals measured within the chambers of the heart, which can be used to locate abnormal cardiac tissue and guide catheter ablations to treat cardiac arrhythmias. EGMs may contain large amounts of uncertainty and irregular variations, which pose significant challenges in data analysis. This study aims to introduce a statistical approach to account for the data uncertainty while analyzing EGMs for abnormal electrical impulse identification. The activation order of catheter sensors was modeled with a multinomial distribution, and maximum likelihood estimations were done to track the electrical wave conduction path in the presence of uncertainty. Robust optimization was performed to locate the electrical impulses based on the local conduction velocity and the geodesic distances between catheter sensors. The proposed algorithm can identify the focal sources when the electrical conduction is initiated by irregular electrical impulses and involves wave collisions, breakups, and spiral waves. The statistical modeling framework can efficiently deal with data uncertainties and provide a reliable estimation of the focal source locations. This shows the great potential of a statistical approach for the quantitative analysis of the stochastic activity of electrical waves in cardiac disorders and suggests future investigations integrating statistical methods with a deterministic geometry-based method to achieve advanced diagnostic performance.
Collapse
Affiliation(s)
- Amirhossein Koneshloo
- Department of Industrial, Manufacturing and Systems Engineering, Texas Tech University, Lubbock, TX 79409, USA
| | - Dongping Du
- Department of Industrial, Manufacturing and Systems Engineering, Texas Tech University, Lubbock, TX 79409, USA
| | - Yuncheng Du
- Department of Chemical & Biomolecular Engineering, Clarkson University, Potsdam, NY 13699, USA
| |
Collapse
|
13
|
Pappone C, Ciconte G, Vicedomini G, Mangual JO, Li W, Conti M, Giannelli L, Lipartiti F, McSpadden L, Ryu K, Guazzi M, Menicanti L, Santinelli V. Clinical Outcome of Electrophysiologically Guided Ablation for Nonparoxysmal Atrial Fibrillation Using a Novel Real-Time 3-Dimensional Mapping Technique: Results From a Prospective Randomized Trial. Circ Arrhythm Electrophysiol 2019. [PMID: 29535136 DOI: 10.1161/circep.117.005904] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Clinical outcomes after ablation of persistent atrial fibrillation remain suboptimal. Identification of AF drivers using a novel integrated mapping technique may be crucial to ameliorate the clinical outcome. METHODS AND RESULTS Persistent AF patients were prospectively enrolled to undergo high-density electrophysiological mapping to identify repetitive-regular activities (RRas) before modified circumferential pulmonary vein (PV) ablation. They have been randomly assigned (1:1 ratio) to ablation of RRa followed by modified circumferential PV ablation (mapping group; n=41) or modified circumferential PV ablation alone (control group; n=40). The primary end point was freedom from arrhythmic recurrences at 1 year. In total, 81 persistent AF patients (74% male; mean age, 61.7±10.6 years) underwent mapping/ablation procedure. The regions exhibiting RRa were 479 in 81 patients (5.9±2.4 RRa per patient): 232 regions in the mapping group (n=41) and 247 in the control group (n=40). Overall, 185 of 479 (39%) RRas were identified within the PVs, whereas 294 of 479 (61%) in non-PV regions. Mapping-guided ablation resulted in higher arrhythmia termination rate when compared with conventional strategy (25/41, 61% versus 12/40, 30%; P<0.007). Total radiofrequency duration (P=0.38), mapping (P=0.46), and fluoroscopy times (P=0.69) were not significantly different between the groups. No major procedure-related adverse events occurred. After 1 year, 73.2% of mapping group patients were free from recurrences versus 50% of control group (P=0.03). CONCLUSIONS Targeted ablation of regions showing RRa provided an adjunctive benefit in terms of arrhythmia freedom at 1-year follow-up in the treatment of persistent AF. These findings might support a patient-tailored strategy in subjects with nonparoxysmal AF and should be confirmed by additional larger, randomized, multicenter studies. CLINICAL TRIAL REGISTRATION URL: https://www.clinicaltrials.gov. Unique identifier NCT02571218.
Collapse
Affiliation(s)
- Carlo Pappone
- From the Department of Arrhythmology and Electrophysiology (C.P., G.C., G.V., M.C., L.G., F.L., V.S.), Department of Cardiac Surgery (L.M.), and Heart Failure Unit (M.G.), IRCCS Policlinico San Donato, San Donato Milanese, Italy; and Abbott, Sylmar, Los Angeles, CA (J.O.M., W.L., L.M., K.R.).
| | - Giuseppe Ciconte
- From the Department of Arrhythmology and Electrophysiology (C.P., G.C., G.V., M.C., L.G., F.L., V.S.), Department of Cardiac Surgery (L.M.), and Heart Failure Unit (M.G.), IRCCS Policlinico San Donato, San Donato Milanese, Italy; and Abbott, Sylmar, Los Angeles, CA (J.O.M., W.L., L.M., K.R.)
| | - Gabriele Vicedomini
- From the Department of Arrhythmology and Electrophysiology (C.P., G.C., G.V., M.C., L.G., F.L., V.S.), Department of Cardiac Surgery (L.M.), and Heart Failure Unit (M.G.), IRCCS Policlinico San Donato, San Donato Milanese, Italy; and Abbott, Sylmar, Los Angeles, CA (J.O.M., W.L., L.M., K.R.)
| | - Jan O Mangual
- From the Department of Arrhythmology and Electrophysiology (C.P., G.C., G.V., M.C., L.G., F.L., V.S.), Department of Cardiac Surgery (L.M.), and Heart Failure Unit (M.G.), IRCCS Policlinico San Donato, San Donato Milanese, Italy; and Abbott, Sylmar, Los Angeles, CA (J.O.M., W.L., L.M., K.R.)
| | - Wenwen Li
- From the Department of Arrhythmology and Electrophysiology (C.P., G.C., G.V., M.C., L.G., F.L., V.S.), Department of Cardiac Surgery (L.M.), and Heart Failure Unit (M.G.), IRCCS Policlinico San Donato, San Donato Milanese, Italy; and Abbott, Sylmar, Los Angeles, CA (J.O.M., W.L., L.M., K.R.)
| | - Manuel Conti
- From the Department of Arrhythmology and Electrophysiology (C.P., G.C., G.V., M.C., L.G., F.L., V.S.), Department of Cardiac Surgery (L.M.), and Heart Failure Unit (M.G.), IRCCS Policlinico San Donato, San Donato Milanese, Italy; and Abbott, Sylmar, Los Angeles, CA (J.O.M., W.L., L.M., K.R.)
| | - Luigi Giannelli
- From the Department of Arrhythmology and Electrophysiology (C.P., G.C., G.V., M.C., L.G., F.L., V.S.), Department of Cardiac Surgery (L.M.), and Heart Failure Unit (M.G.), IRCCS Policlinico San Donato, San Donato Milanese, Italy; and Abbott, Sylmar, Los Angeles, CA (J.O.M., W.L., L.M., K.R.)
| | - Felicia Lipartiti
- From the Department of Arrhythmology and Electrophysiology (C.P., G.C., G.V., M.C., L.G., F.L., V.S.), Department of Cardiac Surgery (L.M.), and Heart Failure Unit (M.G.), IRCCS Policlinico San Donato, San Donato Milanese, Italy; and Abbott, Sylmar, Los Angeles, CA (J.O.M., W.L., L.M., K.R.)
| | - Luke McSpadden
- From the Department of Arrhythmology and Electrophysiology (C.P., G.C., G.V., M.C., L.G., F.L., V.S.), Department of Cardiac Surgery (L.M.), and Heart Failure Unit (M.G.), IRCCS Policlinico San Donato, San Donato Milanese, Italy; and Abbott, Sylmar, Los Angeles, CA (J.O.M., W.L., L.M., K.R.)
| | - Kyungmoo Ryu
- From the Department of Arrhythmology and Electrophysiology (C.P., G.C., G.V., M.C., L.G., F.L., V.S.), Department of Cardiac Surgery (L.M.), and Heart Failure Unit (M.G.), IRCCS Policlinico San Donato, San Donato Milanese, Italy; and Abbott, Sylmar, Los Angeles, CA (J.O.M., W.L., L.M., K.R.)
| | - Marco Guazzi
- From the Department of Arrhythmology and Electrophysiology (C.P., G.C., G.V., M.C., L.G., F.L., V.S.), Department of Cardiac Surgery (L.M.), and Heart Failure Unit (M.G.), IRCCS Policlinico San Donato, San Donato Milanese, Italy; and Abbott, Sylmar, Los Angeles, CA (J.O.M., W.L., L.M., K.R.)
| | - Lorenzo Menicanti
- From the Department of Arrhythmology and Electrophysiology (C.P., G.C., G.V., M.C., L.G., F.L., V.S.), Department of Cardiac Surgery (L.M.), and Heart Failure Unit (M.G.), IRCCS Policlinico San Donato, San Donato Milanese, Italy; and Abbott, Sylmar, Los Angeles, CA (J.O.M., W.L., L.M., K.R.)
| | - Vincenzo Santinelli
- From the Department of Arrhythmology and Electrophysiology (C.P., G.C., G.V., M.C., L.G., F.L., V.S.), Department of Cardiac Surgery (L.M.), and Heart Failure Unit (M.G.), IRCCS Policlinico San Donato, San Donato Milanese, Italy; and Abbott, Sylmar, Los Angeles, CA (J.O.M., W.L., L.M., K.R.)
| |
Collapse
|
14
|
Ganesan P, Salmin A, Cherry EM, Huang DT, Pertsov AM, Ghoraani B. Iterative navigation of multipole diagnostic catheters to locate repeating-pattern atrial fibrillation drivers. J Cardiovasc Electrophysiol 2019; 30:758-768. [PMID: 30725499 PMCID: PMC6554033 DOI: 10.1111/jce.13872] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Revised: 01/16/2019] [Accepted: 01/31/2019] [Indexed: 01/01/2023]
Abstract
Introduction Targeting repeating‐pattern atrial fibrillation (AF) sources (reentry or focal drivers) can help in patient‐specific ablation therapy for AF; however, the development of reliable and accurate tools for locating such sources remains a major challenge. We describe iterative catheter navigation (ICAN) algorithm to locate AF drivers using a conventional circular Lasso catheter. Methods and Results At each step, the algorithm analyzes 10 bipolar electrograms recoded at a given catheter location and the history of previous catheter movements to determine if the source is inside the catheter loop. If not, it calculates new coordinates and selects a new position for the catheter. The process continues until a source is located. The algorithm was evaluated in a computer model of atrial tissue with various degrees of fibrosis under a broad range of arrhythmia scenarios. The latter included slow and fast reentry, macroreentry, figure‐of‐eight reentry, and fibrillatory conduction. Depending on the initial distance of the catheter from the source and scenario, it took about 3 to 16 steps to localize an AF source. In 94% of cases, the identified location was within 4 mm from the source, independently of the initial position of the catheter. The algorithm worked equally well in the presence of patchy fibrosis, low‐voltage areas, fragmented electrograms, and dominant‐frequency gradients. Conclusions AF repeating‐pattern sources can be localized using circular catheters without the need to map the entire tissue. The proposed algorithm has the potential to become a useful tool for patient‐specific ablation of AF sources located outside the pulmonary veins.
Collapse
Affiliation(s)
- Prasanth Ganesan
- Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, Florida
| | - Anthony Salmin
- School of Mathematical Sciences, Rochester Institute of Technology, Rochester, New York
| | - Elizabeth M Cherry
- School of Mathematical Sciences, Rochester Institute of Technology, Rochester, New York
| | - David T Huang
- Department of Cardiology, University of Rochester Medical Center, Rochester, New York
| | - Arkady M Pertsov
- Department of Pharmacology, SUNY Upstate Medical Center, Syracuse, New York
| | - Behnaz Ghoraani
- Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, Florida
| |
Collapse
|
15
|
Loewe A, Poremba E, Oesterlein T, Luik A, Schmitt C, Seemann G, Dössel O. Patient-Specific Identification of Atrial Flutter Vulnerability-A Computational Approach to Reveal Latent Reentry Pathways. Front Physiol 2019; 9:1910. [PMID: 30692934 PMCID: PMC6339942 DOI: 10.3389/fphys.2018.01910] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2018] [Accepted: 12/18/2018] [Indexed: 11/23/2022] Open
Abstract
Atypical atrial flutter (AFlut) is a reentrant arrhythmia which patients frequently develop after ablation for atrial fibrillation (AF). Indeed, substrate modifications during AF ablation can increase the likelihood to develop AFlut and it is clinically not feasible to reliably and sensitively test if a patient is vulnerable to AFlut. Here, we present a novel method based on personalized computational models to identify pathways along which AFlut can be sustained in an individual patient. We build a personalized model of atrial excitation propagation considering the anatomy as well as the spatial distribution of anisotropic conduction velocity and repolarization characteristics based on a combination of a priori knowledge on the population level and information derived from measurements performed in the individual patient. The fast marching scheme is employed to compute activation times for stimuli from all parts of the atria. Potential flutter pathways are then identified by tracing loops from wave front collision sites and constricting them using a geometric snake approach under consideration of the heterogeneous wavelength condition. In this way, all pathways along which AFlut can be sustained are identified. Flutter pathways can be instantiated by using an eikonal-diffusion phase extrapolation approach and a dynamic multifront fast marching simulation. In these dynamic simulations, the initial pattern eventually turns into the one driven by the dominant pathway, which is the only pathway that can be observed clinically. We assessed the sensitivity of the flutter pathway maps with respect to conduction velocity and its anisotropy. Moreover, we demonstrate the application of tailored models considering disease-specific repolarization properties (healthy, AF-remodeled, potassium channel mutations) as well as applicabiltiy on a clinical dataset. Finally, we tested how AFlut vulnerability of these substrates is modulated by exemplary antiarrhythmic drugs (amiodarone, dronedarone). Our novel method allows to assess the vulnerability of an individual patient to develop AFlut based on the personal anatomical, electrophysiological, and pharmacological characteristics. In contrast to clinical electrophysiological studies, our computational approach provides the means to identify all possible AFlut pathways and not just the currently dominant one. This allows to consider all relevant AFlut pathways when tailoring clinical ablation therapy in order to reduce the development and recurrence of AFlut.
Collapse
Affiliation(s)
- Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Emanuel Poremba
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Tobias Oesterlein
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Armin Luik
- Medizinische Klinik IV, Städtisches Klinikum Karlsruhe, Karlsruhe, Germany
| | - Claus Schmitt
- Medizinische Klinik IV, Städtisches Klinikum Karlsruhe, Karlsruhe, Germany
| | - Gunnar Seemann
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg Bad Krozingen, Freiburg, Germany
- Faculty of Medicine, Albert-Ludwigs University, Freiburg, Germany
| | - Olaf Dössel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| |
Collapse
|
16
|
Roney CH, Whitaker J, Sim I, O'Neill L, Mukherjee RK, Razeghi O, Vigmond EJ, Wright M, O'Neill MD, Williams SE, Niederer SA. A technique for measuring anisotropy in atrial conduction to estimate conduction velocity and atrial fibre direction. Comput Biol Med 2019; 104:278-290. [PMID: 30415767 PMCID: PMC6506689 DOI: 10.1016/j.compbiomed.2018.10.019] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Revised: 10/17/2018] [Accepted: 10/17/2018] [Indexed: 01/04/2023]
Abstract
BACKGROUND Cardiac conduction properties exhibit large variability, and affect patient-specific arrhythmia mechanisms. However, it is challenging to clinically measure conduction velocity (CV), anisotropy and fibre direction. Our aim is to develop a technique to estimate conduction anisotropy and fibre direction from clinically available electrical recordings. METHODS We developed and validated automated algorithms for estimating cardiac CV anisotropy, from any distribution of recording locations on the atrial surface. The first algorithm is for elliptical wavefront fitting to a single activation map (method 1), which works well close to the pacing location, but decreases in accuracy further from the pacing location (due to spatial heterogeneity in the conductivity and fibre fields). As such, we developed a second methodology for measuring local conduction anisotropy, using data from two or three activation maps (method 2: ellipse fitting to wavefront propagation velocity vectors from multiple activation maps). RESULTS Ellipse fitting to CV vectors from two activation maps (method 2) leads to an improved estimation of longitudinal and transverse CV compared to method 1, but fibre direction estimation is still relatively poor. Using three activation maps with method 2 provides accurate estimation, with approximately 70% of atrial fibres estimated within 20∘. We applied the technique to clinical activation maps to demonstrate the presence of heterogeneous conduction anisotropy, and then tested the effects of this conduction anisotropy on predicted arrhythmia dynamics using computational simulation. CONCLUSIONS We have developed novel algorithms for calculating CV and measuring the direction dependency of atrial activation to estimate atrial fibre direction, without the need for specialised pacing protocols, using clinically available electrical recordings.
Collapse
Affiliation(s)
- Caroline H Roney
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.
| | - John Whitaker
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Iain Sim
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Louisa O'Neill
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Rahul K Mukherjee
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Orod Razeghi
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Edward J Vigmond
- LIRYC Electrophysiology and Heart Modeling Institute, Campus Xavier Arnozan, Avenue du Haut Lévêque, 33600, Pessac, France; Univ. Bordeaux, IMB, UMR 5251, F-33400, Talence, France
| | - Matthew Wright
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Mark D O'Neill
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Steven E Williams
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Steven A Niederer
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| |
Collapse
|
17
|
Alagoz C, Guez A, Cohen A, Bullinga JR. Spiral wave classification using normalized compression distance: Towards atrial tissue spatiotemporal electrophysiological behavior characterization. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2018; 2015:4503-6. [PMID: 26737295 DOI: 10.1109/embc.2015.7319395] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Analysis of electrical activation patterns such as re-entries during atrial fibrillation (Afib) is crucial in understanding arrhythmic mechanisms and assessment of diagnostic measures. Spiral waves are a phenomena that provide intuitive basis for re-entries occurring in cardiac tissue. Distinct spiral wave behaviors such as stable spiral waves, meandering spiral waves, and spiral wave break-up may have distinct electrogram manifestations on a mapping catheter. Hence, it is desirable to have an automated classification of spiral wave behavior based on catheter recordings for a qualitative characterization of spatiotemporal electrophysiological activity on atrial tissue. In this study, we propose a method for classification of spatiotemporal characteristics of simulated atrial activation patterns in terms of distinct spiral wave behaviors during Afib using two different techniques: normalized compressed distance (NCD) and normalized FFT (NFFTD). We use a phenomenological model for cardiac electrical propagation to produce various simulated spiral wave behaviors on a 2D grid and labeled them as stable, meandering, or breakup. By mimicking commonly used catheter types, a star shaped and a circular shaped both of which do the local readings from atrial wall, monopolar and bipolar intracardiac electrograms are simulated. Virtual catheters are positioned at different locations on the grid. The classification performance for different catheter locations, types and for monopolar or bipolar readings were also compared. We observed that the performance for each case differed slightly. However, we found that NCD performance is superior to NFFTD. Through the simulation study, we showed the theoretical validation of the proposed method. Our findings suggest that a qualitative wavefront activation pattern can be assessed during Afib without the need for highly invasive mapping techniques such as multisite simultaneous electrogram recordings.
Collapse
|
18
|
Hajimolahoseini H, Hashemi J, Gazor S, Redfearn D. Inflection point analysis: A machine learning approach for extraction of IEGM active intervals during atrial fibrillation. Artif Intell Med 2018; 85:7-15. [PMID: 29503040 DOI: 10.1016/j.artmed.2018.02.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Revised: 01/11/2018] [Accepted: 02/15/2018] [Indexed: 10/17/2022]
Abstract
OBJECTIVE In this paper, we propose a novel algorithm to extract the active intervals of intracardiac electrograms during atrial fibrillation. METHODS First, we show that the characteristics of the signal waveform at its inflection points are prominent features that are implicitly used by human annotators for distinguishing between active and inactive intervals of IEGMs. Then, we show that the natural logarithm of features corresponding to active and inactive intervals exhibits a mixture of two Gaussian distributions in three dimensional feature space. An Expectation Maximization algorithm for Gaussian mixtures is then applied for automatic clustering of the features into two categories. RESULTS The absolute error in onset and offset estimation of active intervals is 6.1ms and 10.7ms, respectively, guaranteeing a high resolution. The true positive rate for the proposed method is also 98.1%, proving the high reliability. CONCLUSION The proposed method can extract the active intervals of IEGMs during AF with a high accuracy and resolution close to manually annotated results. SIGNIFICANCE In contrast with some of the conventional methods, no windowing technique is required in our approach resulting in significantly higher resolution in estimating the onset and offset of active intervals. Furthermore, since the signal characteristics at inflection points are analyzed instead of signal samples, the computational time is significantly low, ensuring the real-time application of our algorithm. The proposed method is also robust to noise and baseline variations thanks to the Laplacian of Gaussian filter employed for extraction of inflection points.
Collapse
|
19
|
Shariat MH, Gazor S, Redfearn DP. Bipolar Intracardiac Electrogram Active Interval Extraction During Atrial Fibrillation. IEEE Trans Biomed Eng 2017; 64:2122-2133. [DOI: 10.1109/tbme.2016.2630604] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
20
|
Cabrera-Lozoya R, Berte B, Cochet H, Jais P, Ayache N, Sermesant M. Image-Based Biophysical Simulation of Intracardiac Abnormal Ventricular Electrograms. IEEE Trans Biomed Eng 2017; 64:1446-1454. [DOI: 10.1109/tbme.2016.2562918] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
21
|
Ccoffinn: Automated Wave Tracking in Cultured Cardiac Monolayers. Biophys J 2017; 111:1595-1599. [PMID: 27760347 DOI: 10.1016/j.bpj.2016.08.049] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2016] [Revised: 08/19/2016] [Accepted: 08/26/2016] [Indexed: 11/23/2022] Open
Abstract
Cardiac arrhythmias are one of the most frequent causes of death worldwide. A popular biological model used to study arrhythmogenesis is the cultured cardiac cell monolayer, which provides a good trade-off between physiological relevance and experimental access. Excitation wave patterns are imaged using high-bandwidth detectors, producing large data sets that are typically analyzed manually. To make such analysis less time consuming and less subjective, we have designed and implemented a toolkit for segmentation and tracking of cardiac waves in optical mapping recordings. The toolkit is optimized for high-resolution detectors to accommodate the growing availability of inexpensive high-resolution detectors for life science imaging applications (e.g., scientific CMOS cameras). The software extracts key features of propagating waves, such as wavefront speed and entropy. The methods have been validated using synthetic data, and real-world examples are provided, showing a difference in conduction velocity between two different types of cardiac cell cultures.
Collapse
|
22
|
Deno DC, Balachandran R, Morgan D, Ahmad F, Masse S, Nanthakumar K. Orientation-Independent Catheter-Based Characterization of Myocardial Activation. IEEE Trans Biomed Eng 2017; 64:1067-1077. [DOI: 10.1109/tbme.2016.2589158] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
|
23
|
Niederer SA, Smith NP. Using physiologically based models for clinical translation: predictive modelling, data interpretation or something in-between? J Physiol 2016; 594:6849-6863. [PMID: 27121495 PMCID: PMC5134392 DOI: 10.1113/jp272003] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2015] [Accepted: 03/13/2016] [Indexed: 02/02/2023] Open
Abstract
Heart disease continues to be a significant clinical problem in Western society. Predictive models and simulations that integrate physiological understanding with patient information derived from clinical data have huge potential to contribute to improving our understanding of both the progression and treatment of heart disease. In particular they provide the potential to improve patient selection and optimisation of cardiovascular interventions across a range of pathologies. Currently a significant proportion of this potential is still to be realised. In this paper we discuss the opportunities and challenges associated with this realisation. Reviewing the successful elements of model translation for biophysically based models and the emerging supporting technologies, we propose three distinct modes of clinical translation. Finally we outline the challenges ahead that will be fundamental to overcome if the ultimate goal of fully personalised clinical cardiac care is to be achieved.
Collapse
Affiliation(s)
- Steven A. Niederer
- Department of Biomedical Engineering and Imaging SciencesSt Thomas’ HospitalKing's College LondonThe Rayne Institute4th Floor Lambeth WingLondonSE1 7EHUK
| | - Nic P. Smith
- Department of Biomedical Engineering and Imaging SciencesSt Thomas’ HospitalKing's College LondonThe Rayne Institute4th Floor Lambeth WingLondonSE1 7EHUK
- Engineering School Block 1University of AucklandLevel 5, 20 Symonds StreetAuckland101New Zealand
| |
Collapse
|
24
|
Reich C, Oesterlein T, Rottmann M, Seemann G, Dössel O. Classification of cardiac excitation patterns during atrial fibrillation. CURRENT DIRECTIONS IN BIOMEDICAL ENGINEERING 2016. [DOI: 10.1515/cdbme-2016-0037] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
AbstractThe goal of this research was to classify cardiac excitation patterns during atrial fibrillation (AFib). For this purpose, virtual models of intracardiac mapping catheters were moved across in-silico cardiac tissue to extract local activation times (LATs) of each catheter electrode from simulated cardiac action potential (AP) signals. The resulting LAT patterns consisting of the LATs of all electrodes resemble patterns measured in clinical cases. The LATs represent the input information for features that were used to separate four different excitation patterns during AFib. Those four excitation patterns were plane wave, ectopic focus (spherical wave), rotor (spiral wave) and block. A feature selection algorithm was used to investigate the features concerning their power to classify the different simulated excitation patterns. The scores of the selected features were used to train and optimize a support vector machine (SVM). The optimized and cross-validated SVM was then used to classify the simulated cardiac excitation patterns. The achieved overall classification accuracy of this SVM model was 98.4 %.
Collapse
Affiliation(s)
- Christian Reich
- 1Karlsruhe Institute of Technology, Institute of Biomedical Engineering, Karlsruhe, Germany
| | - Tobias Oesterlein
- 1Karlsruhe Institute of Technology, Institute of Biomedical Engineering, Karlsruhe, Germany
| | - Markus Rottmann
- 1Karlsruhe Institute of Technology, Institute of Biomedical Engineering, Karlsruhe, Germany
| | - Gunnar Seemann
- 1Karlsruhe Institute of Technology, Institute of Biomedical Engineering, Karlsruhe, Germany
- 2Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg ⋅ Bad Krozingen, Freiburg, Germany
| | - Olaf Dössel
- 1Karlsruhe Institute of Technology, Institute of Biomedical Engineering, Karlsruhe, Germany
| |
Collapse
|
25
|
Roney CH, Cantwell CD, Qureshi NA, Ali RL, Chang ETY, Lim PB, Sherwin SJ, Peters NS, Siggers JH, Ng FS. An automated algorithm for determining conduction velocity, wavefront direction and origin of focal cardiac arrhythmias using a multipolar catheter. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2016; 2014:1583-6. [PMID: 25570274 DOI: 10.1109/embc.2014.6943906] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
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.
Collapse
|
26
|
Oesterlein TG, Schmid J, Bauer S, Jadidi A, Schmitt C, Dössel O, Luik A. Analysis and visualization of intracardiac electrograms in diagnosis and research: Concept and application of KaPAVIE. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2016; 127:165-173. [PMID: 26774236 DOI: 10.1016/j.cmpb.2015.12.007] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2015] [Revised: 12/11/2015] [Accepted: 12/17/2015] [Indexed: 06/05/2023]
Abstract
BACKGROUND AND OBJECTIVE Progress in biomedical engineering has improved the hardware available for diagnosis and treatment of cardiac arrhythmias. But although huge amounts of intracardiac electrograms (EGMs) can be acquired during electrophysiological examinations, there is still a lack of software aiding diagnosis. The development of novel algorithms for the automated analysis of EGMs has proven difficult, due to the highly interdisciplinary nature of this task and hampered data access in clinical systems. Thus we developed a software platform, which allows rapid implementation of new algorithms, verification of their functionality and suitable visualization for discussion in the clinical environment. METHODS A software for visualization was developed in Qt5 and C++ utilizing the class library of VTK. The algorithms for signal analysis were implemented in MATLAB. Clinical data for analysis was exported from electroanatomical mapping systems. RESULTS The visualization software KaPAVIE (Karlsruhe Platform for Analysis and Visualization of Intracardiac Electrograms) was implemented and tested on several clinical datasets. Both common and novel algorithms were implemented which address important clinical questions in diagnosis of different arrhythmias. It proved useful in discussions with clinicians due to its interactive and user-friendly design. Time after export from the clinical mapping system to visualization is below 5min. CONCLUSION KaPAVIE(2) is a powerful platform for the development of novel algorithms in the clinical environment. Simultaneous and interactive visualization of measured EGM data and the results of analysis will aid diagnosis and help understanding the underlying mechanisms of complex arrhythmias like atrial fibrillation.
Collapse
Affiliation(s)
- Tobias Georg Oesterlein
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
| | - Jochen Schmid
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
| | - Silvio Bauer
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
| | - Amir Jadidi
- Universitäts-Herzzentrum Freiburg-Bad Krozingen, Germany.
| | | | - Olaf Dössel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
| | - Armin Luik
- Städtisches Klinikum Karlsruhe, Karlsruhe, Germany.
| |
Collapse
|
27
|
Cantwell CD, Roney CH, Ng FS, Siggers JH, Sherwin SJ, Peters NS. Techniques for automated local activation time annotation and conduction velocity estimation in cardiac mapping. Comput Biol Med 2015; 65:229-42. [PMID: 25978869 PMCID: PMC4593301 DOI: 10.1016/j.compbiomed.2015.04.027] [Citation(s) in RCA: 114] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2015] [Revised: 04/13/2015] [Accepted: 04/16/2015] [Indexed: 11/24/2022]
Abstract
Measurements of cardiac conduction velocity provide valuable functional and structural insight into the initiation and perpetuation of cardiac arrhythmias, in both a clinical and laboratory context. The interpretation of activation wavefronts and their propagation can identify mechanistic properties of a broad range of electrophysiological pathologies. However, the sparsity, distribution and uncertainty of recorded data make accurate conduction velocity calculation difficult. A wide range of mathematical approaches have been proposed for addressing this challenge, often targeted towards specific data modalities, species or recording environments. Many of these algorithms require identification of activation times from electrogram recordings which themselves may have complex morphology or low signal-to-noise ratio. This paper surveys algorithms designed for identifying local activation times and computing conduction direction and speed. Their suitability for use in different recording contexts and applications is assessed.
Collapse
Affiliation(s)
- C D Cantwell
- Department of Aeronautics, Imperial College London, South Kensington Campus, London, UK; National Heart and Lung Institute, Imperial College London, South Kensington Campus, London, UK.
| | - C H Roney
- Department of Bioengineering, Imperial College London, South Kensington Campus, London, UK; National Heart and Lung Institute, Imperial College London, South Kensington Campus, London, UK
| | - F S Ng
- National Heart and Lung Institute, Imperial College London, South Kensington Campus, London, UK
| | - J H Siggers
- Department of Bioengineering, Imperial College London, South Kensington Campus, London, UK
| | - S J Sherwin
- Department of Aeronautics, Imperial College London, South Kensington Campus, London, UK
| | - N S Peters
- National Heart and Lung Institute, Imperial College London, South Kensington Campus, London, UK
| |
Collapse
|
28
|
Ravelli F, Masè M. Computational mapping in atrial fibrillation: how the integration of signal-derived maps may guide the localization of critical sources. ACTA ACUST UNITED AC 2014; 16:714-23. [DOI: 10.1093/europace/eut376] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
|
29
|
CASTELLS FRANCISCO, CERVIGÓN RAQUEL, MILLET JOSÉ. On the Preprocessing of Atrial Electrograms in Atrial Fibrillation: Understanding Botteron's Approach. PACING AND CLINICAL ELECTROPHYSIOLOGY: PACE 2013; 37:133-43. [DOI: 10.1111/pace.12288] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2013] [Revised: 07/20/2013] [Accepted: 08/14/2013] [Indexed: 11/29/2022]
Affiliation(s)
| | - RAQUEL CERVIGÓN
- Escuela Politécnica de Cuenca; Universidad de Castilla la Mancha; Cuenca Spain
| | - JOSÉ MILLET
- ITACA Institute; Universitat Politècnica de València; València Spain
| |
Collapse
|
30
|
Keller MW, Schuler S, Luik A, Seemann G, Schilling C, Schmitt C, Dössel O. Comparison of simulated and clinical intracardiac electrograms. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2013; 2013:6858-6861. [PMID: 24111320 DOI: 10.1109/embc.2013.6611133] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Intracardiac electrograms are the key in understanding, interpretation and treatment of cardiac arrhythmias. However, electrogram morphologies are strongly variable due to catheter position, orientation and contact. Simulations of intracardiac electrograms can improve comprehension and quantification of influencing parameters and therefore reduce misinterpretations. In this study simulated intracardiac electrograms are analyzed regarding tilt angles of the catheter relative to the propagation direction, electrode tissue distances as well as clinical filter settings. Catheter signals are computed on a realistic 3D catheter geometry using bidomain simulations of cardiac electrophysiology. Thereby high conductivities of the catheter electrodes are taken into account. For validation, simulated electrograms are compared with in vivo electrograms recorded during an EP-study with direct annotation of catheter orientation and tissue contact. Good agreement was reached regarding timing and signal width of simulated and measured electrograms. Correlation was 0.92±0.07 for bipolar, 0.92±0.05 for unipolar distal and 0.80 ± 0.12 for unipolar proximal electrograms for different catheter orientations and locations.
Collapse
|
31
|
Krueger MW, Schulze WHW, Rhode KS, Razavi R, Seemann G, Dössel O. Towards personalized clinical in-silico modeling of atrial anatomy and electrophysiology. Med Biol Eng Comput 2012; 51:1251-60. [PMID: 23070728 DOI: 10.1007/s11517-012-0970-0] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2012] [Accepted: 09/26/2012] [Indexed: 12/21/2022]
Abstract
Computational atrial models aid the understanding of pathological mechanisms and therapeutic measures in basic research. The use of biophysical models in a clinical environment requires methods to personalize the anatomy and electrophysiology (EP). Strategies for the automation of model generation and for evaluation are needed. In this manuscript, the current efforts of clinical atrial modeling in the euHeart project are summarized within the context of recent publications in this field. Model-based segmentation methods allow for the automatic generation of ready-to-simulate patient-specific anatomical models. EP models can be adapted to patient groups based on a-priori knowledge and to the individual without significant further data acquisition. ECG and intracardiac data build the basis for excitation personalization. Information from late enhancement (LE) MRI can be used to evaluate the success of radio-frequency ablation (RFA) procedures and interactive virtual atria pave the way for RFA planning. Atrial modeling is currently in a transition from the sole use in basic research to future clinical applications. The proposed methods build the framework for model-based diagnosis and therapy evaluation and planning. Complex models allow to understand biophysical mechanisms and enable the development of simplified models for clinical applications.
Collapse
Affiliation(s)
- Martin W Krueger
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, 76131, Karlsruhe, Germany,
| | | | | | | | | | | |
Collapse
|
32
|
Dössel O, Krueger MW, Weber FM, Schilling C, Schulze WHW, Seemann G. A framework for personalization of computational models of the human atria. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2012; 2011:4324-8. [PMID: 22255296 DOI: 10.1109/iembs.2011.6091073] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
A framework for step-by-step personalization of a computational model of human atria is presented. Beginning with anatomical modeling based on CT or MRI data, next fiber structure is superimposed using a rule-based method. If available, late-enhancement-MRI images can be considered in order to mark fibrotic tissue. A first estimate of individual electrophysiology is gained from BSPM data solving the inverse problem of ECG. A final adjustment of electrophysiology is realized using intracardiac measurements. The framework is applied using several patient data. First clinical application will be computer assisted planning of RF-ablation for treatment of atrial flutter and atrial fibrillation.
Collapse
Affiliation(s)
- Olaf Dössel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany.
| | | | | | | | | | | |
Collapse
|
33
|
Dössel O, Krueger MW, Weber FM, Wilhelms M, Seemann G. Computational modeling of the human atrial anatomy and electrophysiology. Med Biol Eng Comput 2012; 50:773-99. [PMID: 22718317 DOI: 10.1007/s11517-012-0924-6] [Citation(s) in RCA: 72] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2011] [Accepted: 05/21/2012] [Indexed: 01/08/2023]
Abstract
This review article gives a comprehensive survey of the progress made in computational modeling of the human atria during the last 10 years. Modeling the anatomy has emerged from simple "peanut"-like structures to very detailed models including atrial wall and fiber direction. Electrophysiological models started with just two cellular models in 1998. Today, five models exist considering e.g. details of intracellular compartments and atrial heterogeneity. On the pathological side, modeling atrial remodeling and fibrotic tissue are the other important aspects. The bridge to data that are measured in the catheter laboratory and on the body surface (ECG) is under construction. Every measurement can be used either for model personalization or for validation. Potential clinical applications are briefly outlined and future research perspectives are suggested.
Collapse
Affiliation(s)
- Olaf Dössel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Karlsruhe, Germany.
| | | | | | | | | |
Collapse
|
34
|
Richter U, Faes L, Ravelli F, Sornmo L. Propagation Pattern Analysis During Atrial Fibrillation Based on Sparse Modeling. IEEE Trans Biomed Eng 2012; 59:1319-28. [DOI: 10.1109/tbme.2012.2187054] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
35
|
Herlin A, Jacquemet V. Eikonal-based initiation of fibrillatory activity in thin-walled cardiac propagation models. CHAOS (WOODBURY, N.Y.) 2011; 21:043136. [PMID: 22225373 DOI: 10.1063/1.3670060] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Reentrant arrhythmias can be simulated in electrophysiological models of electrical impulse propagation governed by a reaction-diffusion system. To facilitate the initiation of a large number of independent episodes of simulated arrhythmias with controllable level of complexity, a new approach is proposed for thin-walled geometries in which depolarization wave dynamics is essentially two-dimensional. Points representing phase singularities are first randomly distributed over the epicardial surface and are assigned a topological charge (direction of rotation). A qualitatively-correct phase map is then reconstructed on the whole surface by interpolation. The eikonal-diffusion equation is used to iteratively regularize the phase map based on a priori information on wavefront propagation. An initial condition for the reaction-diffusion model is created from the resulting phase map with multiple functional/anatomical reentries. Results in an atrial model demonstrate the ability to generate statistical realizations of the same dynamics and to vary the level of complexity measured by the number of phase singularities. A library of 100 simulations with an average number of phase singularities ranging from 1 to 10 is created. An extension to volumetric patient-specific atrial models including fiber orientation and a fast conducting system is presented to illustrate possible applications.
Collapse
Affiliation(s)
- Antoine Herlin
- Institut de Génie Biomédical, Department of Physiology, Faculty of Medicine, Université de Montréal, Montréal, Canada
| | | |
Collapse
|
36
|
Weber FM, Luik A, Schilling C, Seemann G, Krueger MW, Lorenz C, Schmitt C, Dossel O. Conduction velocity restitution of the human atrium--an efficient measurement protocol for clinical electrophysiological studies. IEEE Trans Biomed Eng 2011; 58:2648-55. [PMID: 21708491 DOI: 10.1109/tbme.2011.2160453] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Conduction velocity (CV) and CV restitution are important substrate parameters for understanding atrial arrhythmias. The aim of this work is to (i) present a simple but feasible method to measure CV restitution in-vivo using standard circular catheters, and (ii) validate its feasibility with data measured during incremental pacing. From five patients undergoing catheter ablation, we analyzed eight datasets from sinus rhythm and incremental pacing sequences. Every wavefront was measured with a circular catheter and the electrograms were analyzed with a cosine-fit method that calculated the local CV. For each pacing cycle length, the mean local CV was determined. Furthermore, changes in global CV were estimated from the time delay between pacing stimulus and wavefront arrival. Comparing local and global CV between pacing at 500 and 300 ms, we found significant changes in seven of eight pacing sequences. On average, local CV decreased by 20 ± 15% and global CV by 17 ± 13%. The method allows for in-vivo measurements of absolute CV and CV restitution during standard clinical procedures. Such data may provide valuable insights into mechanisms of atrial arrhythmias. This is important both for improving cardiac models and also for clinical applications, such as characterizing arrhythmogenic substrates during sinus rhythm.
Collapse
Affiliation(s)
- Frank M Weber
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany.
| | | | | | | | | | | | | | | |
Collapse
|