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Pancorbo L, Ruipérez-Campillo S, Tormos Á, Guill A, Cervigón R, Alberola A, Chorro FJ, Millet J, Castells F. Vector Field Heterogeneity for the Assessment of Locally Disorganised Cardiac Electrical Propagation Wavefronts From High-Density Multielectrodes. IEEE OPEN JOURNAL OF ENGINEERING IN MEDICINE AND BIOLOGY 2023; 5:32-44. [PMID: 38445238 PMCID: PMC10914212 DOI: 10.1109/ojemb.2023.3344349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 10/22/2023] [Accepted: 11/28/2023] [Indexed: 03/07/2024] Open
Abstract
High-density multielectrode catheters are becoming increasingly popular in cardiac electrophysiology for advanced characterisation of the cardiac tissue, due to their potential to identify impaired sites. These are often characterised by abnormal electrical conduction, which may cause locally disorganised propagation wavefronts. To quantify it, a novel heterogeneity parameter based on vector field analysis is proposed, utilising finite differences to measure direction changes between adjacent cliques. The proposed Vector Field Heterogeneity metric has been evaluated on a set of simulations with controlled levels of organisation in vector maps, and a variety of grid sizes. Furthermore, it has been tested on animal experimental models of isolated Langendorff-perfused rabbit hearts. The proposed parameter exhibited superior capturing ability of heterogeneous propagation wavefronts compared to the classical Spatial Inhomogeneity Index, and simulations proved that the metric effectively captures gradual increments in disorganisation in propagation patterns. Notably, it yielded robust and consistent outcomes for [Formula: see text] grid sizes, underscoring its suitability for the latest generation of orientation-independent cardiac catheters.
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Affiliation(s)
- Lucía Pancorbo
- ITACA InstituteUniversitat Politècnica de València46022ValenciaSpain
| | | | - Álvaro Tormos
- ITACA InstituteUniversitat Politècnica de València46022ValenciaSpain
| | - Antonio Guill
- ITACA InstituteUniversitat Politècnica de València46022ValenciaSpain
| | | | - Antonio Alberola
- Departamento de FisiologíaUniversidad de València46010ValenciaSpain
- Instituto de Investigación INCLIVA46010ValenciaSpain
- CIBER E. Cardiovasculares28029MadridSpain
| | - Francisco Javier Chorro
- CIBER E. Cardiovasculares28029MadridSpain
- Departamento de MedicinaUniversidad de València46010ValenciaSpain
- Instituto de Investigación INCLIVA46010ValenciaSpain
- Servicio de CardiologíaHospital Clínic Universitari de València46010ValenciaSpain
| | - José Millet
- ITACA InstituteUniversitat Politècnica de València46022ValenciaSpain
- Centro de Investigación Biomédica en Red Enfermedades Cardiovascular28029MadridSpain
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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.
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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
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Luengo D, Rios-Munoz G, Elvira V, Sanchez C, Artes-Rodriguez A. Hierarchical Algorithms for Causality Retrieval in Atrial Fibrillation Intracavitary Electrograms. IEEE J Biomed Health Inform 2018; 23:143-155. [PMID: 29994646 DOI: 10.1109/jbhi.2018.2805773] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Multichannel intracavitary electrograms (EGMs) are acquired at the electrophysiology laboratory to guide radio frequency catheter ablation of patients suffering from atrial fibrillation. These EGMs are used by cardiologists to determine candidate areas for ablation (e.g., areas corresponding to high dominant frequencies or complex fractionated electrograms). In this paper, we introduce two hierarchical algorithms to retrieve the causal interactions among these multiple EGMs. Both algorithms are based on Granger causality, but other causality measures can be easily incorporated. In both cases, they start by selecting a root node, but they differ on the way in which they explore the set of signals to determine their cause-effect relationships: either testing the full set of unexplored signals (GS-CaRe) or performing a local search only among the set of neighbor EGMs (LS-CaRe). The ensuing causal model provides important information about the propagation of the electrical signals inside the atria, uncovering wavefronts and activation patterns that can guide cardiologists towards candidate areas for catheter ablation. Numerical experiments, on both synthetic signals and annotated real-world signals, show the good performance of the two proposed approaches.
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Spatio-temporal Organization During Ventricular Fibrillation in the Human Heart. Ann Biomed Eng 2018; 46:864-876. [PMID: 29546467 PMCID: PMC5934463 DOI: 10.1007/s10439-018-2007-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2017] [Accepted: 03/07/2018] [Indexed: 11/11/2022]
Abstract
In this paper, we present a novel approach to quantify the spatio-temporal organization of electrical activation during human ventricular fibrillation (VF). We propose three different methods based on correlation analysis, graph theoretical measures and hierarchical clustering. Using the proposed approach, we quantified the level of spatio-temporal organization during three episodes of VF in ten patients, recorded using multi-electrode epicardial recordings with 30 s coronary perfusion, 150 s global myocardial ischaemia and 30 s reflow. Our findings show a steady decline in spatio-temporal organization from the onset of VF with coronary perfusion. We observed transient increases in spatio-temporal organization during global myocardial ischaemia. However, the decline in spatio-temporal organization continued during reflow. Our results were consistent across all patients, and were consistent with the numbers of phase singularities. Our findings show that the complex spatio-temporal patterns can be studied using complex network analysis.
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Granger Causality and Jensen-Shannon Divergence to Determine Dominant Atrial Area in Atrial Fibrillation. ENTROPY 2018; 20:e20010057. [PMID: 33265143 PMCID: PMC7512253 DOI: 10.3390/e20010057] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/15/2017] [Revised: 12/27/2017] [Accepted: 01/05/2018] [Indexed: 01/08/2023]
Abstract
Atrial fibrillation (AF) is already the most commonly occurring arrhythmia. Catheter pulmonary vein ablation has emerged as a treatment that is able to make the arrhythmia disappear; nevertheless, recurrence to arrhythmia is very frequent. In this study, it is proposed to perform an analysis of the electrical signals recorded from bipolar catheters at three locations, pulmonary veins and the right and left atria, before to and during the ablation procedure. Principal Component Analysis (PCA) was applied to reduce data dimension and Granger causality and divergence techniques were applied to analyse connectivity along the atria, in three main regions: pulmonary veins, left atrium (LA) and right atrium (RA). The results showed that, before the procedure, patients with recurrence in the arrhythmia had greater connectivity between atrial areas. Moreover, during the ablation procedure, in patients with recurrence in the arrhythmial both atria were more connected than in patients that maintained sinus rhythms. These results can be helpful for procedures designing to end AF.
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Biton Y, Rabinovitch A, Braunstein D, Aviram I, Campbell K, Mironov S, Herron T, Jalife J, Berenfeld O. Causality analysis of leading singular value decomposition modes identifies rotor as the dominant driving normal mode in fibrillation. CHAOS (WOODBURY, N.Y.) 2018; 28:013128. [PMID: 29390625 PMCID: PMC5786449 DOI: 10.1063/1.5021261] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2017] [Accepted: 12/28/2017] [Indexed: 06/07/2023]
Abstract
Cardiac fibrillation is a major clinical and societal burden. Rotors may drive fibrillation in many cases, but their role and patterns are often masked by complex propagation. We used Singular Value Decomposition (SVD), which ranks patterns of activation hierarchically, together with Wiener-Granger causality analysis (WGCA), which analyses direction of information among observations, to investigate the role of rotors in cardiac fibrillation. We hypothesized that combining SVD analysis with WGCA should reveal whether rotor activity is the dominant driving force of fibrillation even in cases of high complexity. Optical mapping experiments were conducted in neonatal rat cardiomyocyte monolayers (diameter, 35 mm), which were genetically modified to overexpress the delayed rectifier K+ channel IKr only in one half of the monolayer. Such monolayers have been shown previously to sustain fast rotors confined to the IKr overexpressing half and driving fibrillatory-like activity in the other half. SVD analysis of the optical mapping movies revealed a hierarchical pattern in which the primary modes corresponded to rotor activity in the IKr overexpressing region and the secondary modes corresponded to fibrillatory activity elsewhere. We then applied WGCA to evaluate the directionality of influence between modes in the entire monolayer using clear and noisy movies of activity. We demonstrated that the rotor modes influence the secondary fibrillatory modes, but influence was detected also in the opposite direction. To more specifically delineate the role of the rotor in fibrillation, we decomposed separately the respective SVD modes of the rotor and fibrillatory domains. In this case, WGCA yielded more information from the rotor to the fibrillatory domains than in the opposite direction. In conclusion, SVD analysis reveals that rotors can be the dominant modes of an experimental model of fibrillation. Wiener-Granger causality on modes of the rotor domains confirms their preferential driving influence on fibrillatory modes.
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Affiliation(s)
- Yaacov Biton
- Physics Department, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
| | - Avinoam Rabinovitch
- Physics Department, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
| | - Doron Braunstein
- Physics Department, Sami Shamoon College of Engineering, Beer-Sheva 84100, Israel
| | - Ira Aviram
- Physics Department, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
| | - Katherine Campbell
- Center for Arrhythmia Research, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Sergey Mironov
- Center for Arrhythmia Research, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Todd Herron
- Center for Arrhythmia Research, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - José Jalife
- Center for Arrhythmia Research, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Omer Berenfeld
- Center for Arrhythmia Research, University of Michigan, Ann Arbor, Michigan 48109, USA
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Alcaine A, Mase M, Cristoforetti A, Ravelli F, Nollo G, Laguna P, Martinez JP, Faes L. A Multi-Variate Predictability Framework to Assess Invasive Cardiac Activity and Interactions During Atrial Fibrillation. IEEE Trans Biomed Eng 2017; 64:1157-1168. [DOI: 10.1109/tbme.2016.2592953] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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8
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Separating the effect of respiration on the heart rate variability using Granger's causality and linear filtering. Biomed Signal Process Control 2017. [DOI: 10.1016/j.bspc.2016.07.014] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Rodrigo M, Climent AM, Liberos A, Calvo D, Fernández-Avilés F, Berenfeld O, Atienza F, Guillem MS. Identification of Dominant Excitation Patterns and Sources of Atrial Fibrillation by Causality Analysis. Ann Biomed Eng 2016; 44:2364-2376. [PMID: 26850022 DOI: 10.1007/s10439-015-1534-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2015] [Accepted: 12/11/2015] [Indexed: 01/18/2023]
Abstract
Burden of atrial fibrillation (AF) can be reduced by ablation of sources of electrical impulses driving AF but driver identification is still challenging. This study presents a new methodology based on causality analysis that allows identifying the hierarchically dominant areas driving AF. Identification of dominant propagation patterns was achieved by computing causal relations between intracardiac multi-electrode catheter recordings of four paroxysmal AF patients during sinus rhythm, pacing and AF. In addition, realistic mathematical models of the atria during AF were used to validate the methodology both in the presence and absence of dominant frequency (DF) gradients. During electrical pacing, sources of propagation patterns detected by causality analysis were consistent with the location of the stimulating catheter. During AF, propagation patterns presented temporal variability, but a dominant direction accounted for significantly more propagations than other directions (49 ± 15% vs. 14 ± 13% or less, p < 0.01). Both in patients with a DF gradient and in mathematical models, causal maps allowed the identification of sites responsible for maintenance of AF. Causal maps allowed the identification of atrial dominant sites. In particular, causality analysis resulted in stable dominant cause-effect propagation directions during AF and could serve as a guide for performing ablation procedures in AF patients.
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Affiliation(s)
- Miguel Rodrigo
- ITACA, Universitat Politècnica de Valencia, 1ªplanta, Edificio 8G, Ciudad Politécnica de la Innovación, Camino de Vera s/n, 46022, Valencia, Spain
| | - Andreu M Climent
- Cardiology Department, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón, Calle Dr Esquerdo 46, 28007, Madrid, Spain
| | - Alejandro Liberos
- ITACA, Universitat Politècnica de Valencia, 1ªplanta, Edificio 8G, Ciudad Politécnica de la Innovación, Camino de Vera s/n, 46022, Valencia, Spain
| | - David Calvo
- Cardiology Department, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón, Calle Dr Esquerdo 46, 28007, Madrid, Spain
- Hospital Universitario Central de Asturias, Avd de Roma sn, 33006, Oviedo, Spain
| | - Francisco Fernández-Avilés
- Cardiology Department, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón, Calle Dr Esquerdo 46, 28007, Madrid, Spain
- Facultad de Medicina, Universidad Complutense de Madrid, Pza. Ramón y Cajal, s/n, Ciudad Universitaria, 28040, Madrid, Spain
| | - Omer Berenfeld
- Center for Arrhythmia Research, University of Michigan, 2800 Plymouth Road, Ann Arbor, MI, 48109, USA
| | - Felipe Atienza
- Cardiology Department, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón, Calle Dr Esquerdo 46, 28007, Madrid, Spain
- Facultad de Medicina, Universidad Complutense de Madrid, Pza. Ramón y Cajal, s/n, Ciudad Universitaria, 28040, Madrid, Spain
| | - Maria S Guillem
- ITACA, Universitat Politècnica de Valencia, 1ªplanta, Edificio 8G, Ciudad Politécnica de la Innovación, Camino de Vera s/n, 46022, Valencia, Spain.
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10
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Rodrigo M, Climent AM, Liberos A, Fernández-Avilés F, Berenfeld O, Atienza F, Guillem MS. Atrial sources identification by causality analysis during atrial fibrillation. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2016; 2015:3783-6. [PMID: 26737117 DOI: 10.1109/embc.2015.7319217] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Ablation of electrical drivers during atrial fibrillation (AF) has been proved as an effective therapy to prevent recurrence of fibrillatory episodes. This study presents a new methodology based on causality analysis that is able to identify the hierarchical dominance of atrial areas driving AF. Realistic mathematical models of the atrial electrical activity during AF were used to assess the validity of our method. Identification of the dominant atrial propagation patterns was achieved by computing causal relations between multiple electrogram signals. The causal relationships between atrial areas during the fibrillatory processes were summarized into a recurrence map, highlighting the hierarchy and dominant areas. Recurrence maps computed from causality analysis allowed the identification of sites responsible for maintenance of the arrhythmia. These maps were able to locate the position of the atrial driver in fibrillatory processes with a single rotor, with 2 rotors or with several drivers. Additionally, the correspondence between the nodal values of the recurrence map and the distance to the rotor core has been established. Causal analysis consistently estimated propagation patterns and location of atrial drivers during AF. This methodology could guide ablation procedures in AF patients.
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11
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Zhang L, Yang C, Nie Z. Quantitative assessment of synchronization during atrial fibrillation based on a novel index. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2015; 2014:998-1001. [PMID: 25570129 DOI: 10.1109/embc.2014.6943761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Atrial Fibrillation (AF), a chaotic rhythm classically considered with random electrical activity, is now demonstrated to show a certain degree of organization and synchronization. Rather than those traditional indices which always focus on the pairwise properties of adjacent signals, a new synchronization index-S estimator-is introduced in this paper to quantify the synchronization level for all the signals in a selected area. By evaluating a complement of the entropy of the normalized eigenvalues of the corresponding correlation matrix, S estimator is designed to be proportional to the amount of synchronization. 400 episodes of 64-channel epicardial signals acquired from four living mongrels were studied under normal sinus rhythm (SN) and AF. The results showed that there were significant decreases of S estimator for both anterior left atrium and anterior right atrium with the rhythm changing from SN to AF. After dividing the research area into eight subparts, S estimator is also capable to demonstrate the different synchronization level for each subpart and revealed the electrophysiology individual difference among four experimental subjects. In conclusion, S estimator succeeds in estimating the synchronization degree for multi-channel signals in a selected area, with no limits to the number of the signals to be analyzed. It can help us to distinguish the region with a high synchronization level during AF, which would be helpful to the clinical AF treatment and enhance our understanding of underlying mechanisms of AF.
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12
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Rodrigo M, Pedrón-Torecilla J, Hernández I, Liberos A, Climent AM, Guillem MS. Data analysis in cardiac arrhythmias. Methods Mol Biol 2014; 1246:217-35. [PMID: 25417089 DOI: 10.1007/978-1-4939-1985-7_14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2023]
Abstract
Cardiac arrhythmias are an increasingly present in developed countries and represent a major health and economic burden. The occurrence of cardiac arrhythmias is closely linked to the electrical function of the heart. Consequently, the analysis of the electrical signal generated by the heart tissue, either recorded invasively or noninvasively, provides valuable information for the study of cardiac arrhythmias. In this chapter, novel cardiac signal analysis techniques that allow the study and diagnosis of cardiac arrhythmias are described, with emphasis on cardiac mapping which allows for spatiotemporal analysis of cardiac signals.Cardiac mapping can serve as a diagnostic tool by recording cardiac signals either in close contact to the heart tissue or noninvasively from the body surface, and allows the identification of cardiac sites responsible of the development or maintenance of arrhythmias. Cardiac mapping can also be used for research in cardiac arrhythmias in order to understand their mechanisms. For this purpose, both synthetic signals generated by computer simulations and animal experimental models allow for more controlled physiological conditions and complete access to the organ.
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Affiliation(s)
- Miguel Rodrigo
- BIO-ITACA, Universitat Politècnica de València, Edificio 8G, Camino de Vera, S/N, 46022, Valencia, Spain
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13
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Keller MW, Schuler S, Wilhelms M, Lenis G, Seemann G, Schmitt C, Dössel O, Luik A. Characterization of radiofrequency ablation lesion development based on simulated and measured intracardiac electrograms. IEEE Trans Biomed Eng 2014; 61:2467-78. [PMID: 24816474 DOI: 10.1109/tbme.2014.2322515] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Radiofrequency ablation (RFA) therapy is the gold standard in interventional treatment of many cardiac arrhythmias. A major obstacle is nontransmural lesions, leading to recurrence of arrhythmias. Recent clinical studies have suggested intracardiac electrogram (EGM) criteria as a promising marker to evaluate lesion development. Seeking for a deeper understanding of underlying mechanisms, we established a simulation approach for acute RFA lesions. Ablation lesions were modeled by a passive necrotic core surrounded by a borderzone with properties of heated myocardium. Herein, conduction velocity and electrophysiological properties were altered. We simulated EGMs during RFA to study the relation between lesion formation and EGM changes using the bidomain model. Simulations were performed on a three-dimensional setup including a geometrically detailed representation of the catheter with highly conductive electrodes. For validation, EGMs recorded during RFA procedures in five patients were analyzed and compared to simulation results. Clinical data showed major changes in the distal unipolar EGM. During RFA, the negative peak amplitude decreased up to 104% and maximum negative deflection was up to 88% smaller at the end of the ablation sequence. These changes mainly occurred in the first 10 s after ablation onset. Simulated unipolar EGMs reproduced the clinical changes, reaching up to 83% negative peak amplitude reduction and 80% decrease in maximum negative deflection for transmural lesions. In future studies, the established model may enable the development of further EGM criteria for transmural lesions even for complex geometries in order to support clinical therapy.
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14
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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]
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15
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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
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16
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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.
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17
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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.
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Affiliation(s)
- Martin W Krueger
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, 76131, Karlsruhe, Germany,
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18
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Bai B, Wang Y, Yang C. Predicting atrial fibrillation inducibility in a canine model by multi-threshold spectra of the recurrence complex network. Med Eng Phys 2012; 35:668-75. [PMID: 22925583 DOI: 10.1016/j.medengphy.2012.07.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2011] [Revised: 07/19/2012] [Accepted: 07/21/2012] [Indexed: 10/28/2022]
Abstract
The purpose of this study is to predict atrial fibrillation (AF) from epicardial signals by investigating the recurrence property of atrial activity dynamic system before AF. A novel scheme is proposed to predict AF by using multi-threshold spectra of the recurrence complex network. Firstly, epicardial signals are transformed into the recurrence complex network to quantify structural properties of the recurrence in the phase space. Spectral parameters with multi-threshold are used to characterize the global structure of the network. Then the feature sequential forward searching algorithm and mutual information based Maximum Relevance Minimum Redundancy criterion are used to find the optimal feature set. Finally, a support vector machine is used to predict the occurrence of AF. This method is assessed on the pre-AF epicardial signals of canine which includes the normal group A (no further AF will happen), the mild group B (the following AF time is less than 180s) and the severe group C (the following AF time is more than 180s). 25 optimal features are selected out of 180 features from each sample. With these features, sensitivity, specificity and accuracy are 99.40%, 99.70% and 99.60%, respectively, which are the best among the recurrence based methods. The results suggest that the proposed method can predict AF accurately and thus can be prospectively used in the postoperative evaluation.
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Affiliation(s)
- Baodan Bai
- Department of Electronic Engineering, Fudan University, 220 Handan Road, Shanghai 200433, China.
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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: 80] [Impact Index Per Article: 6.7] [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.
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Affiliation(s)
- Olaf Dössel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Karlsruhe, Germany.
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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]
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Spatial complexity and spectral distribution variability of atrial activity in surface ECG recordings of atrial fibrillation. Med Biol Eng Comput 2012; 50:439-46. [DOI: 10.1007/s11517-012-0878-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2011] [Accepted: 02/07/2012] [Indexed: 10/28/2022]
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Richter U, Faes L, Ravelli F, Sörnmo L. Propagation pattern analysis during atrial fibrillation based on the adaptive group LASSO. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2011; 2011:5535-5538. [PMID: 22255592 DOI: 10.1109/iembs.2011.6091412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
The present study introduces sparse modeling for the estimation of propagation patterns in intracardiac atrial fibrillation (AF) signals. The estimation is based on the partial directed coherence (PDC) function, derived from fitting a multivariate autoregressive model to the observed signals. A sparse optimization method is proposed for estimation of the model parameters, namely, the adaptive group least absolute selection and shrinkage operator (aLASSO). In simulations aLASSO was found superior to the commonly used least-squares (LS) estimation with respect to estimation performance. The normalized error between the true and estimated model parameters dropped from 0.20 ± 0.04 for LS estimation to 0.03 ± 0.01 for aLASSO when the number of available data samples exceeded the number of model parameters by a factor of 5. The error reduction was more pronounced for short data segments. Propagation patterns were also studied on intracardiac AF data, the results showing that the identification of propagation patterns is substantially simplified by the sparsity assumption.
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Affiliation(s)
- Ulrike Richter
- Signal Processing Group, Department of Electrical and Information Technology, Lund University.
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