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Kesavaraja C, Sengottuvel S, Patel R, Selvaraj RJ, Satheesh S, Mani A. Enhancing the efficiency and cost-effectiveness of magnetocardiography by optimal channel selection for cardiac diagnosis. Biomed Phys Eng Express 2024; 10:025023. [PMID: 38277702 DOI: 10.1088/2057-1976/ad233e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 01/26/2024] [Indexed: 01/28/2024]
Abstract
Background. Magnetocardiography (MCG) is a non-invasive and non-contact technique that measures weak magnetic fields generated by the heart. It is highly effective in the diagnosis of heart abnormalities. Multichannel MCG provides detailed spatio-temporal information of the measured magnetic fields. While multichannel MCG systems are costly, usage of the optimal number of measurement channels to characterize cardiac magnetic fields without any appreciable loss of signal information would be economically beneficial and promote the widespread use of MCG technology.Methods. An optimization method based on the sequential selection approach is used to choose channels containing the maximum signal information while avoiding redundancy. The study comprised 40 healthy individuals, along with two subjects having ischemic heart disease and one subject with premature ventricular contraction. MCG measured using a 37 channel MCG system. After revisiting the existing methods of optimization, the mean error and correlation of the optimal set of measurement channels with those of all 37 channels are evaluated for different sets, and it has been found that 18 channels are adequate.Results. The chosen 18 optimal channels exhibited a strong correlation (0.99 ± 0.006) between the original and reconstructed magnetic field maps for a cardiac cycle in healthy subjects. The root mean square error is 0.295 pT, indicating minimal deviation.Conclusion. This selection method provides an efficient approach for choosing MCG, which could be used for minimizing the number of channels as well as in practical unforeseen measurement conditions where few channels are noisy during the measurement.
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Affiliation(s)
- C Kesavaraja
- Indira Gandhi Centre for Atomic Research, A CI of Homi Bhabha National Institute, Kalpakkam-603102, Tamil Nadu, India
| | - S Sengottuvel
- SQUIDs Applications section, SQUID & Detector Technology Division, Materials Science Group, Indira Gandhi Centre for Atomic Research (IGCAR), Kalpakkam-603102, Tamil Nadu, India
| | - Rajesh Patel
- SQUIDs Applications section, SQUID & Detector Technology Division, Materials Science Group, Indira Gandhi Centre for Atomic Research (IGCAR), Kalpakkam-603102, Tamil Nadu, India
| | - Raja J Selvaraj
- Department of Cardiology, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry-605006, India
| | - Santhosh Satheesh
- Department of Cardiology, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry-605006, India
| | - Awadhesh Mani
- Indira Gandhi Centre for Atomic Research, A CI of Homi Bhabha National Institute, Kalpakkam-603102, Tamil Nadu, India
- Condensed Matter Physics Division, Materials Science Group, Indira Gandhi Centre for Atomic Research (IGCAR), Kalpakkam-603102, Tamil Nadu, India
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Robustness of imageless electrocardiographic imaging against uncertainty in atrial morphology and location. J Electrocardiol 2023; 77:58-61. [PMID: 36634462 DOI: 10.1016/j.jelectrocard.2022.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 09/13/2022] [Accepted: 12/23/2022] [Indexed: 01/04/2023]
Abstract
INTRODUCTION Electrocardiographic Imaging is a non-invasive technique that requires cardiac Imaging for the reconstruction of cardiac electrical activity. In this study, we explored imageless ECGI by quantifying the errors of using heart meshes with either an inaccurate location inside the thorax or an inaccurate geometry. METHODS Multiple‑lead body surface recordings of 25 atrial fibrillation (AF) patients were recorded. Cardiac atrial meshes were obtained by segmentation of medical images obtained for each patient. ECGI was computed with each patient's segmented atrial mesh and compared with the ECGI obtained under errors in the atrial mesh used for ECGI estimation. We modeled both the uncertainty in the location of the atria inside the thorax by artificially translating the atria inside the thorax and the geometry of the atrial mesh by using an atrial mesh in a reference database. ECGI signals obtained with the actual meshes and the translated or estimated meshes were compared in terms of their correlation coefficients, relative difference measurement star, and errors in the dominant frequency (DF) estimation in epicardial nodes. RESULTS CC between ECGI signals obtained after translating the actual atrial meshes from the original position by 1 cm was above 0.97. CC between ECGIs obtained with patient specific atrial geometry and estimated atrial geometries was 0.93 ± 0.11. Mean errors in DF estimation using an estimated atrial mesh were 7.6 ± 5.9%. CONCLUSION Imageless ECGI can provide a robust estimation of cardiac electrophysiological parameters such as activation rates even during complex arrhythmias. Furthermore, it can allow more widespread use of ECGI in clinical practice.
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McCann A, Luca A, Pascale P, Pruvot E, Vesin JM. Novel spatiotemporal processing tools for body-surface potential map signals for the prediction of catheter ablation outcome in persistent atrial fibrillation. Front Physiol 2022; 13:1001060. [PMID: 36246141 PMCID: PMC9557152 DOI: 10.3389/fphys.2022.1001060] [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: 07/22/2022] [Accepted: 09/08/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Signal processing tools are required to efficiently analyze data collected in body-surface-potential map (BSPM) recordings. A limited number of such tools exist for studying persistent atrial fibrillation (persAF). We propose two novel, spatiotemporal indices for processing BSPM data and test their clinical applicability through a comparison with the recently proposed non-dipolar component index (NDI) for prediction of single-procedure catheter ablation (CA) success rate in persAF patients.Methods: BSPM recordings were obtained with a 252-lead vest in 13 persAF patients (8 men, 63 ± 8 years, 11 ± 13 months sustained AF duration) before undergoing CA. Each recording was divided into seven 1-min segments of high signal quality. Spatiotemporal ventricular activity (VA) cancellation was applied to each segment to isolate atrial activity (AA). The two novel indices, called error-ratio, normalized root-mean-square error (ERNRMSE) and error-ratio, mean-absolute error (ERABSE), were calculated. These indices quantify the capacity of a subset of BSPM vest electrodes to accurately represent the AA, and AA dominant frequency (DF), respectively, on all BSPM electrodes over time, compared to the optimal principal component analysis (PCA) representation. The NDI, quantifying the fraction of energy retained after removal of the three largest PCs, was also calculated. The two novel indices and the NDI were statistically compared between patient groups based on single-procedure clinical CA outcome. Finally, their predictive power for univariate CA outcome classification was assessed using receiver operating characteristic (ROC) analysis with cross-validation for a logistic regression classifier.Results: Patient clinical outcomes were recorded 6 months following procedures, and those who had an arrhythmia recurrence at least 2 months post-CA were defined as having a negative outcome. Clinical outcome information was available for 11 patients, 6 with arrhythmia recurrence. Therefore, a total of 77 1-min AA-BSPM segments were available for analysis. Significant differences were found in the values of the novel indices and NDI between patients with arrhythmia recurrence post-ablation and those without. ROC analysis showed the best CA outcome predictive performance for ERNRMSE (AUC = 0.77 ± 0.08, sensitivity = 76.2%, specificity = 84.8%).Conclusion: Significant association was found between the novel indices and CA success or failure. The novel index ERNRMSE additionally shows good predictive power for single-procedure CA outcome.
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Affiliation(s)
- Anna McCann
- Applied Signal Processing Group, Department of Electrical Engineering, Swiss Federal Institute of Technology, Lausanne, Switzerland
- *Correspondence: Anna McCann,
| | - Adrian Luca
- Service of Cardiology, Lausanne University Hospital, Lausanne, Switzerland
| | - Patrizio Pascale
- Service of Cardiology, Lausanne University Hospital, Lausanne, Switzerland
| | - Etienne Pruvot
- Service of Cardiology, Lausanne University Hospital, Lausanne, Switzerland
| | - Jean-Marc Vesin
- Applied Signal Processing Group, Department of Electrical Engineering, Swiss Federal Institute of Technology, Lausanne, Switzerland
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Molero R, González-Ascaso A, Hernández-Romero I, Lundback-Mompó D, Climent AM, Guillem MS. Effects of torso mesh density and electrode distribution on the accuracy of electrocardiographic imaging during atrial fibrillation. Front Physiol 2022; 13:908364. [PMID: 36105286 PMCID: PMC9465032 DOI: 10.3389/fphys.2022.908364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 08/01/2022] [Indexed: 11/30/2022] Open
Abstract
Introduction: Electrocardiographic Imaging (ECGI) allows computing the electrical activity in the heart non-invasively using geometrical information of the patient and multiple body surface signals. In the present study we investigate the influence of the number of nodes of geometrical meshes and recording ECG electrodes distribution to compute ECGI during atrial fibrillation (AF). Methods: Torso meshes from 100 to 2000 nodes heterogeneously and homogeneously distributed were compared. Signals from nine AF realistic mathematical simulations were used for computing the ECGI. Results for each torso mesh were compared with the ECGI computed with a 4,000 nodes reference torso. In addition, real AF recordings from 25 AF patients were used to compute ECGI in torso meshes from 100 to 1,000 nodes. Results were compared with a reference torso of 2000 nodes. Torsos were remeshed either by reducing the number of nodes while maximizing the overall shape preservation and then assigning the location of the electrodes as the closest node in the new mesh or by forcing the remesher to place a node at each electrode location. Correlation coefficients, relative difference measurements and relative difference of dominant frequencies were computed to evaluate the impact on signal morphology of each torso mesh. Results: For remeshed torsos where electrodes match with a geometrical node in the mesh, all mesh densities presented similar results. On the other hand, in torsos with electrodes assigned to closest nodes in remeshed geometries performance metrics were dependent on mesh densities, with correlation coefficients ranging from 0.53 ± 0.06 to 0.92 ± 0.04 in simulations or from 0.42 ± 0.38 to 0.89 ± 0.2 in patients. Dominant frequency relative errors showed the same trend with values from 1.14 ± 0.26 to 0.55 ± 0.21 Hz in simulations and from 0.91 ± 0.56 to 0.45 ± 0.41 Hz in patients. Conclusion: The effect of mesh density in ECGI is minimal when the location of the electrode is preserved as a node in the mesh. Torso meshes constructed without imposing electrodes to constitute nodes in the torso geometry should contain at least 400 nodes homogeneously distributed so that a distance between nodes is below 4 cm.
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Affiliation(s)
- Rubén Molero
- ITACA Institute, Universitat Politècnica de València, València, Spain
- *Correspondence: Rubén Molero,
| | | | | | | | - Andreu M. Climent
- ITACA Institute, Universitat Politècnica de València, València, Spain
| | - María S. Guillem
- ITACA Institute, Universitat Politècnica de València, València, Spain
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Molero R, Soler Torro JM, Martínez Alzamora N, M Climent A, Guillem MS. Higher reproducibility of phase derived metrics from electrocardiographic imaging during atrial fibrillation in patients remaining in sinus rhythm after pulmonary vein isolation. Comput Biol Med 2021; 139:104934. [PMID: 34688171 DOI: 10.1016/j.compbiomed.2021.104934] [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: 05/26/2021] [Revised: 10/08/2021] [Accepted: 10/08/2021] [Indexed: 11/18/2022]
Abstract
BACKGROUND Electrocardiographic imaging (ECGI) allows evaluating the complexity of the reentrant activity of atrial fibrillation (AF) patients. In this study, we evaluated the ability of ECGI metrics to predict the success of pulmonary vein isolation (PVI) to treat AF. METHODS ECGI of 24 AF patients (6 males, 13 paroxysmal, 61.8 ± 14 years) was recorded prior to PVI. Patients were distributed into two groups based on their PVI outcome 6 months after ablation (sinus vs. arrhythmia recurrence). Metrics derived from phase analysis of ECGI signals were computed for two different temporal segments before ablation. Correlation analysis and variability over time were studied between the two recorded segments and were compared between patient groups. RESULTS Temporal variability of both rotor duration and spatial entropy of the rotor histogram presented statistical differences between groups with different PVI outcome (p < 0.05). The reproducibility of reentrant metrics was higher (R2 > 0.8) in patients with good outcome rather than arrhythmia recurrence patients (R2 < 0.62). Prediction of PVI success based on ECGI temporal variability metrics allows for an increased specificity over the classification into paroxysmal or persistent (0.85 vs. 0.64). CONCLUSIONS Patients with favorable PVI outcome present ECGI metrics more reproducible over time than patients with AF recurrence. These results suggest that ECGI derived metrics may allow selecting which patients would benefit from ablation therapies.
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Affiliation(s)
- Rubén Molero
- ITACA Institute, Universitat Politècnica de València, València, Spain.
| | - José Manuel Soler Torro
- Department of Applied Statistics and Operational Research and Quality, Universitat Politècnica de València, València, Spain.
| | - Nieves Martínez Alzamora
- Department of Applied Statistics and Operational Research and Quality, Universitat Politècnica de València, València, Spain.
| | - Andreu M Climent
- ITACA Institute, Universitat Politècnica de València, València, Spain.
| | - María S Guillem
- ITACA Institute, Universitat Politècnica de València, València, Spain.
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Salinet J, Molero R, Schlindwein FS, Karel J, Rodrigo M, Rojo-Álvarez JL, Berenfeld O, Climent AM, Zenger B, Vanheusden F, Paredes JGS, MacLeod R, Atienza F, Guillem MS, Cluitmans M, Bonizzi P. Electrocardiographic Imaging for Atrial Fibrillation: A Perspective From Computer Models and Animal Experiments to Clinical Value. Front Physiol 2021; 12:653013. [PMID: 33995122 PMCID: PMC8120164 DOI: 10.3389/fphys.2021.653013] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 03/22/2021] [Indexed: 01/16/2023] Open
Abstract
Electrocardiographic imaging (ECGI) is a technique to reconstruct non-invasively the electrical activity on the heart surface from body-surface potential recordings and geometric information of the torso and the heart. ECGI has shown scientific and clinical value when used to characterize and treat both atrial and ventricular arrhythmias. Regarding atrial fibrillation (AF), the characterization of the electrical propagation and the underlying substrate favoring AF is inherently more challenging than for ventricular arrhythmias, due to the progressive and heterogeneous nature of the disease and its manifestation, the small volume and wall thickness of the atria, and the relatively large role of microstructural abnormalities in AF. At the same time, ECGI has the advantage over other mapping technologies of allowing a global characterization of atrial electrical activity at every atrial beat and non-invasively. However, since ECGI is time-consuming and costly and the use of electrical mapping to guide AF ablation is still not fully established, the clinical value of ECGI for AF is still under assessment. Nonetheless, AF is known to be the manifestation of a complex interaction between electrical and structural abnormalities and therefore, true electro-anatomical-structural imaging may elucidate important key factors of AF development, progression, and treatment. Therefore, it is paramount to identify which clinical questions could be successfully addressed by ECGI when it comes to AF characterization and treatment, and which questions may be beyond its technical limitations. In this manuscript we review the questions that researchers have tried to address on the use of ECGI for AF characterization and treatment guidance (for example, localization of AF triggers and sustaining mechanisms), and we discuss the technological requirements and validation. We address experimental and clinical results, limitations, and future challenges for fruitful application of ECGI for AF understanding and management. We pay attention to existing techniques and clinical application, to computer models and (animal or human) experiments, to challenges of methodological and clinical validation. The overall objective of the study is to provide a consensus on valuable directions that ECGI research may take to provide future improvements in AF characterization and treatment guidance.
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Affiliation(s)
- João Salinet
- Biomedical Engineering, Centre for Engineering, Modelling and Applied Social Sciences (CECS), Federal University of ABC, São Bernardo do Campo, Brazil
| | - Rubén Molero
- ITACA Institute, Universitat Politècnica de València, València, Spain
| | - Fernando S. Schlindwein
- School of Engineering, University of Leicester, United Kingdom and National Institute for Health Research, Leicester Cardiovascular Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Joël Karel
- Department of Data Science and Knowledge Engineering, Maastricht University, Maastricht, Netherlands
| | - Miguel Rodrigo
- Electronic Engineering Department, Universitat de València, València, Spain
| | - José Luis Rojo-Álvarez
- Department of Signal Theory and Communications and Telematic Systems and Computation, University Rey Juan Carlos, Madrid, Spain
| | - Omer Berenfeld
- Center for Arrhythmia Research, University of Michigan, Ann Arbor, MI, United States
| | - Andreu M. Climent
- ITACA Institute, Universitat Politècnica de València, València, Spain
| | - Brian Zenger
- Biomedical Engineering Department, Scientific Computing and Imaging Institute (SCI), and Cardiovascular Research and Training Institute (CVRTI), The University of Utah, Salt Lake City, UT, United States
| | - Frederique Vanheusden
- Department of Engineering, School of Science and Technology, Nottingham Trent University, Nottingham, United Kingdom
| | - Jimena Gabriela Siles Paredes
- Biomedical Engineering, Centre for Engineering, Modelling and Applied Social Sciences (CECS), Federal University of ABC, São Bernardo do Campo, Brazil
| | - Rob MacLeod
- Biomedical Engineering Department, Scientific Computing and Imaging Institute (SCI), and Cardiovascular Research and Training Institute (CVRTI), The University of Utah, Salt Lake City, UT, United States
| | - Felipe Atienza
- Cardiology Department, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón, and Facultad de Medicina, Universidad Complutense de Madrid, Madrid, Spain
| | - María S. Guillem
- ITACA Institute, Universitat Politècnica de València, València, Spain
| | - Matthijs Cluitmans
- Department of Cardiology, Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, Netherlands
| | - Pietro Bonizzi
- Department of Data Science and Knowledge Engineering, Maastricht University, Maastricht, Netherlands
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Rodrigo M, Climent AM, Hernández-Romero I, Liberos A, Baykaner T, Rogers AJ, Alhusseini M, Wang PJ, Fernández-Avilés F, Guillem MS, Narayan SM, Atienza F. Noninvasive Assessment of Complexity of Atrial Fibrillation: Correlation With Contact Mapping and Impact of Ablation. Circ Arrhythm Electrophysiol 2020; 13:e007700. [PMID: 32078374 DOI: 10.1161/circep.119.007700] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BACKGROUND It is difficult to noninvasively phenotype atrial fibrillation (AF) in a way that reflects clinical end points such as response to therapy. We set out to map electrical patterns of disorganization and regions of reentrant activity in AF from the body surface using electrocardiographic imaging, calibrated to panoramic intracardiac recordings and referenced to AF termination by ablation. METHODS Bi-atrial intracardiac electrograms of 47 patients with AF at ablation (30 persistent, 29 male, 63±9 years) were recorded with 64-pole basket catheters and simultaneous 57-lead body surface ECGs. Atrial epicardial electrical activity was reconstructed and organized sites were invasively and noninvasively tracked in 3-dimension using phase singularity. In a subset of 17 patients, sites of AF organization were targeted for ablation. RESULTS Body surface mapping showed greater AF organization near intracardially detected drivers than elsewhere, both in phase singularity density (2.3±2.1 versus 1.9±1.6; P=0.02) and number of drivers (3.2±2.3 versus 2.7±1.7; P=0.02). Complexity, defined as the number of stable AF reentrant sites, was concordant between noninvasive and invasive methods (r2=0.5; CC=0.71). In the subset receiving targeted ablation, AF complexity showed lower values in those in whom AF terminated than those in whom AF did not terminate (P<0.01). CONCLUSIONS AF complexity tracked noninvasively correlates well with organized and disorganized regions detected by panoramic intracardiac mapping and correlates with the acute outcome by ablation. This approach may assist in bedside monitoring of therapy or in improving the efficacy of ongoing ablation procedures.
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Affiliation(s)
- Miguel Rodrigo
- ITACA Institute, Universitat Politècnica de València (M.R., A.M.C., A.L., M.S.G.)
- Cardiology Department, Hospital General Universitario Gregorio Marañón, Instituto de Investigacion Sanitaria Gregorio Marañon (IISGM) (M.R., A.M.C., I.H.-R., A.L., F.F.-A., F.A.), Madrid, Spain
- Cardiac Electrophysiology and Arrhythmia Service, Division of Cardiovascular Medicine, Stanford University School of Medicine, CA (M.R., T.B., A.J.R., M.A., P.J.W., S.M.N.)
| | - Andreu M Climent
- ITACA Institute, Universitat Politècnica de València (M.R., A.M.C., A.L., M.S.G.)
- Cardiology Department, Hospital General Universitario Gregorio Marañón, Instituto de Investigacion Sanitaria Gregorio Marañon (IISGM) (M.R., A.M.C., I.H.-R., A.L., F.F.-A., F.A.), Madrid, Spain
- CIBERCV, Centro de Investigacion Biomedica en Red de Enfermedades Cardiovasculares (A.M.C., F.F.-A., F.A.), Madrid, Spain
| | - Ismael Hernández-Romero
- Cardiology Department, Hospital General Universitario Gregorio Marañón, Instituto de Investigacion Sanitaria Gregorio Marañon (IISGM) (M.R., A.M.C., I.H.-R., A.L., F.F.-A., F.A.), Madrid, Spain
- Department of Signal Theory and Communications, Rey Juan Carlos University (I.H.-R.), Madrid, Spain
| | - Alejandro Liberos
- ITACA Institute, Universitat Politècnica de València (M.R., A.M.C., A.L., M.S.G.)
- Cardiology Department, Hospital General Universitario Gregorio Marañón, Instituto de Investigacion Sanitaria Gregorio Marañon (IISGM) (M.R., A.M.C., I.H.-R., A.L., F.F.-A., F.A.), Madrid, Spain
| | - Tina Baykaner
- Cardiac Electrophysiology and Arrhythmia Service, Division of Cardiovascular Medicine, Stanford University School of Medicine, CA (M.R., T.B., A.J.R., M.A., P.J.W., S.M.N.)
| | - Albert J Rogers
- Cardiac Electrophysiology and Arrhythmia Service, Division of Cardiovascular Medicine, Stanford University School of Medicine, CA (M.R., T.B., A.J.R., M.A., P.J.W., S.M.N.)
| | - Mahmood Alhusseini
- Cardiac Electrophysiology and Arrhythmia Service, Division of Cardiovascular Medicine, Stanford University School of Medicine, CA (M.R., T.B., A.J.R., M.A., P.J.W., S.M.N.)
| | - Paul J Wang
- Cardiac Electrophysiology and Arrhythmia Service, Division of Cardiovascular Medicine, Stanford University School of Medicine, CA (M.R., T.B., A.J.R., M.A., P.J.W., S.M.N.)
| | - Francisco Fernández-Avilés
- Cardiology Department, Hospital General Universitario Gregorio Marañón, Instituto de Investigacion Sanitaria Gregorio Marañon (IISGM) (M.R., A.M.C., I.H.-R., A.L., F.F.-A., F.A.), Madrid, Spain
- CIBERCV, Centro de Investigacion Biomedica en Red de Enfermedades Cardiovasculares (A.M.C., F.F.-A., F.A.), Madrid, Spain
- Facultad de Medicina, Universidad Complutense (F.F.-A., F.A.), Madrid, Spain
| | - Maria S Guillem
- ITACA Institute, Universitat Politècnica de València (M.R., A.M.C., A.L., M.S.G.)
| | - Sanjiv M Narayan
- Cardiac Electrophysiology and Arrhythmia Service, Division of Cardiovascular Medicine, Stanford University School of Medicine, CA (M.R., T.B., A.J.R., M.A., P.J.W., S.M.N.)
| | - Felipe Atienza
- Cardiology Department, Hospital General Universitario Gregorio Marañón, Instituto de Investigacion Sanitaria Gregorio Marañon (IISGM) (M.R., A.M.C., I.H.-R., A.L., F.F.-A., F.A.), Madrid, Spain
- CIBERCV, Centro de Investigacion Biomedica en Red de Enfermedades Cardiovasculares (A.M.C., F.F.-A., F.A.), Madrid, Spain
- Facultad de Medicina, Universidad Complutense (F.F.-A., F.A.), Madrid, Spain
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Rodrigo M, Climent AM, Liberos A, Fernández-Aviles F, Atienza F, Guillem MS, Berenfeld O. Minimal configuration of body surface potential mapping for discrimination of left versus right dominant frequencies during atrial fibrillation. PACING AND CLINICAL ELECTROPHYSIOLOGY: PACE 2017; 40:940-946. [PMID: 28586103 DOI: 10.1111/pace.13133] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2017] [Revised: 05/02/2017] [Accepted: 05/26/2017] [Indexed: 02/03/2023]
Abstract
BACKGROUND Ablation of drivers maintaining atrial fibrillation (AF) has been demonstrated as an effective therapy. Drivers in the form of rapidly activated atrial regions can be noninvasively localized to either left or right atria (LA, RA) with body surface potential mapping (BSPM) systems. This study quantifies the accuracy of dominant frequency (DF) measurements from reduced-leads BSPM systems and assesses the minimal configuration required for ablation guidance. METHODS Nine uniformly distributed lead sets of eight to 66 electrodes were evaluated. BSPM signals were registered simultaneously with intracardiac electrocardiograms (EGMs) in 16 AF patients. DF activity was analyzed on the surface potentials for the nine leads configurations, and the noninvasive measures were compared with the EGM recordings. RESULTS Surface DF measurements presented similar values than panoramic invasive EGM recordings, showing the highest DF regions in corresponding locations. The noninvasive DFs measures had a high correlation with the invasive discrete recordings; they presented a deviation of <0.5 Hz for the highest DF and a correlation coefficient of >0.8 for leads configurations with 12 or more electrodes. CONCLUSIONS Reduced-leads BSPM systems enable noninvasive discrimination between LA versus RA DFs with similar results as higher-resolution 66-leads system. Our findings demonstrate the possible incorporation of simplified BSPM systems into clinical planning procedures for AF ablation.
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Affiliation(s)
- M Rodrigo
- ITACA, Universitat Politècnica de València, Valencia, Spain
| | - A M Climent
- CIBERCV, Hospital General Universitario Gregorio Marañón, Instituto de investigación sanitaria Gregorio Marañón, Madrid, Spain
| | - A Liberos
- CIBERCV, Hospital General Universitario Gregorio Marañón, Instituto de investigación sanitaria Gregorio Marañón, Madrid, Spain
| | - F Fernández-Aviles
- CIBERCV, Hospital General Universitario Gregorio Marañón, Instituto de investigación sanitaria Gregorio Marañón, Madrid, Spain.,Facultad de Medicina. Universidad Complutense de Madrid, Spain
| | - F Atienza
- CIBERCV, Hospital General Universitario Gregorio Marañón, Instituto de investigación sanitaria Gregorio Marañón, Madrid, Spain.,Facultad de Medicina. Universidad Complutense de Madrid, Spain
| | - M S Guillem
- ITACA, Universitat Politècnica de València, Valencia, Spain
| | - O Berenfeld
- Center for Arrhythmia Research, University of Michigan, Ann Arbor, MI
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Ferrer A, Sebastián R, Sánchez-Quintana D, Rodríguez JF, Godoy EJ, Martínez L, Saiz J. Detailed Anatomical and Electrophysiological Models of Human Atria and Torso for the Simulation of Atrial Activation. PLoS One 2015; 10:e0141573. [PMID: 26523732 PMCID: PMC4629897 DOI: 10.1371/journal.pone.0141573] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2015] [Accepted: 10/09/2015] [Indexed: 01/24/2023] Open
Abstract
Atrial arrhythmias, and specifically atrial fibrillation (AF), induce rapid and irregular activation patterns that appear on the torso surface as abnormal P-waves in electrocardiograms and body surface potential maps (BSPM). In recent years both P-waves and the BSPM have been used to identify the mechanisms underlying AF, such as localizing ectopic foci or high-frequency rotors. However, the relationship between the activation of the different areas of the atria and the characteristics of the BSPM and P-wave signals are still far from being completely understood. In this work we developed a multi-scale framework, which combines a highly-detailed 3D atrial model and a torso model to study the relationship between atrial activation and surface signals in sinus rhythm. Using this multi scale model, it was revealed that the best places for recording P-waves are the frontal upper right and the frontal and rear left quadrants of the torso. Our results also suggest that only nine regions (of the twenty-one structures in which the atrial surface was divided) make a significant contribution to the BSPM and determine the main P-wave characteristics.
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Affiliation(s)
- Ana Ferrer
- Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València, Valencia, Spain
- * E-mail:
| | - Rafael Sebastián
- Computational Multiscale Physiology Lab (CoMMLab), Department of Computer Science, Universitat de Valencia, Valencia, Spain
| | - Damián Sánchez-Quintana
- Department of Anatomy and Cell Biology, Faculty of Medicine, Universidad de Extremadura, Badajoz, Spain
| | - José F. Rodríguez
- Applied Mechanics and Bioengineering Group (AMB), Universidad de Zaragoza, Zaragoza, Spain, and Dipartimento di Chimica, Materiali e Ingegneria Chimica “Giulio Natta”, Politecnico di Milano, Milano, Italy
| | - Eduardo J. Godoy
- Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València, Valencia, Spain
| | - Laura Martínez
- Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València, Valencia, Spain
| | - Javier Saiz
- Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València, Valencia, Spain
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Martis RJ, Acharya UR, Adeli H, Prasad H, Tan JH, Chua KC, Too CL, Yeo SWJ, Tong L. Computer aided diagnosis of atrial arrhythmia using dimensionality reduction methods on transform domain representation. Biomed Signal Process Control 2014. [DOI: 10.1016/j.bspc.2014.04.001] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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11
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Application of higher order statistics for atrial arrhythmia classification. Biomed Signal Process Control 2013. [DOI: 10.1016/j.bspc.2013.08.008] [Citation(s) in RCA: 78] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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CERVIGÓN RAQUEL, MORENO JAVIER, PÉREZ-VILLACASTÍN JULIÁN, CASTELLS FRANCISCO. Profound Sedation with Propofol Modifies Atrial Fibrillation Dynamics. PACING AND CLINICAL ELECTROPHYSIOLOGY: PACE 2013; 36:1176-88. [DOI: 10.1111/pace.12137] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2012] [Revised: 01/17/2013] [Accepted: 02/14/2013] [Indexed: 11/27/2022]
Affiliation(s)
- RAQUEL CERVIGÓN
- Universidad de Castilla7#x02010;La Mancha, DIEEAC, UCLM; Bioengineering Innovation Research Group (GIBI); Cuenca Spain
| | - JAVIER MORENO
- Unidad de Arritmias; Hospital Clínico San Carlos; Madrid Spain
| | | | - FRANCISCO CASTELLS
- Universidad Politécnica de Valencia; Bioengineering Electronic Telemedicine (BET); DIE; Valencia Spain
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Pedrón-Torrecilla J, Climent AM, Millet J, Berné P, Brugada J, Brugada R, Guillem MS. Characteristics of inverse-computed epicardial electrograms of Brugada syndrome patients. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2011; 2011:235-238. [PMID: 22254293 DOI: 10.1109/iembs.2011.6090044] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Brugada syndrome (BrS) causes sudden death in patients with structurally normal hearts. Manifestation of BrS in the ECG is dynamic and most patients do not show unequivocal signs of the syndrome during ECG screening. Electrograms (EGMs) of BrS patients show conduction delay and fractionation at the right ventricular outflow tract area (RVOT) and thus could be used for diagnosis, but their recording requires an invasive procedure. We have obtained 67-lead body surface potential mapping recordings (BSPM) of 6 BrS patients and 6 controls and computed their EGMs by solving the inverse problem of electrocardiography by using Tikhonov's regularization method. Inverse-computed EGMs presented similar activation times and durations in controls and BrS patients for apex and septum. However, RVOT EGMs showed a later activation in BrS patients than in controls (58 ± 7 vs. 39 ± 5 ms, p<0.01) and EGMs were longer (122 ± 22 vs. 85 ± 8 ms, p<0.01). Inverse-computed EGMs of BrS patients showed abnormalities consistent with those observed in electrophysiological studies and could be used for a non-invasive diagnosis and characterization of Brugada syndrome.
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Guillem MS, Climent AM, Millet J, Berne P, Ramos R, Brugada J, Brugada R. Conduction abnormalities in the right ventricular outflow tract in Brugada syndrome detected body surface potential mapping. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2010; 2010:2537-40. [PMID: 21096440 DOI: 10.1109/iembs.2010.5626869] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Brugada syndrome (BrS) causes sudden death in patients with structurally normal hearts. Manifestation of BrS in the ECG is dynamical and most patients do not show unequivocal signs of the syndrome during ECG screening. We have obtained 67-lead body surface potential mapping recordings of 25 patients with BrS and analyzed their spatial distribution of surface potentials during ventricular activation. Six patients presented spontaneous type I ECGs during the recording. These patients showed non-dipolarities in isopotential maps at the right ventricular outflow tract (RVOT) region during the development of terminal R waves in right precordial leads. Same finding was observed in 95% of BrS patients not presenting a type I ECG. Conduction delay in the RVOT may be a consistent finding in BrS patients that can be identified by Body Surface Potential Mapping.
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Affiliation(s)
- Maria S Guillem
- BIO-ITACA at Universidad Politécnica de Valencia, 46022, Spain.
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