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Jimenez-Perez G, Acosta J, Bocanegra-Pérez ÁJ, Arana-Rueda E, Frutos-López M, Sánchez-Brotons JA, Llamas-López H, Di Massa Pezzutti R, González de la Portilla Concha C, Camara O, Pedrote A. Delineation of intracavitary electrograms for the automatic quantification of decrement-evoked potentials in the coronary sinus with deep-learning techniques. Front Physiol 2024; 15:1331852. [PMID: 38818521 PMCID: PMC11138951 DOI: 10.3389/fphys.2024.1331852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 04/10/2024] [Indexed: 06/01/2024] Open
Abstract
Cardiac arrhythmias cause depolarization waves to conduct unevenly on the myocardial surface, potentially delaying local components with respect to a previous beat when stimulated at faster frequencies. Despite the diagnostic value of localizing the distinct local electrocardiogram (EGM) components for identifying regions with decrement-evoked potentials (DEEPs), current software solutions do not perform automatic signal quantification. Electrophysiologists must manually measure distances on the EGM signals to assess the existence of DEEPs during pacing or extra-stimuli protocols. In this work, we present a deep learning (DL)-based algorithm to identify decrement in atrial components (measured in the coronary sinus) with respect to their ventricular counterparts from EGM signals, for disambiguating between accessory pathways (APs) and atrioventricular re-entrant tachycardias (AVRTs). Several U-Net and W-Net neural networks with different configurations were trained on a private dataset of signals from the coronary sinus (312 EGM recordings from 77 patients who underwent AP or AVRT ablation). A second, separate dataset was annotated for clinical validation, with clinical labels associated to EGM fragments in which decremental conduction was elucidated. To alleviate data scarcity, a synthetic data augmentation method was developed for generating EGM recordings. Moreover, two novel loss functions were developed to minimize false negatives and delineation errors. Finally, the addition of self-attention mechanisms and their effect on model performance was explored. The best performing model was a W-Net model with 6 levels, optimized solely with the Dice loss. The model obtained precisions of 91.28%, 77.78% and of 100.0%, and recalls of 94.86%, 95.25% and 100.0% for localizing local field, far field activations, and extra-stimuli, respectively. The clinical validation model demonstrated good overall agreement with respect to the evaluation of decremental properties. When compared to the criteria of electrophysiologists, the automatic exclusion step reached a sensitivity of 87.06% and a specificity of 97.03%. Out of the non-excluded signals, a sensitivity of 96.77% and a specificity of 95.24% was obtained for classifying them into decremental and non-decremental potentials. Current results show great promise while being, to the best of our knowledge, the first tool in the literature allowing the delineation of all local components present in an EGM recording. This is of capital importance at advancing processing for cardiac electrophysiological procedures and reducing intervention times, as many diagnosis procedures are performed by comparing segments or late potentials in subsequent cardiac cycles.
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Affiliation(s)
- Guillermo Jimenez-Perez
- PhySense Research Group, BCN MedTech, Universitat Pompeu Fabra, Barcelona, Spain
- Arrhythmia Unit, Department of Cardiology at Virgen Del Rocío University Hospital, Sevilla, Spain
| | - Juan Acosta
- Arrhythmia Unit, Department of Cardiology at Virgen Del Rocío University Hospital, Sevilla, Spain
| | | | - Eduardo Arana-Rueda
- Arrhythmia Unit, Department of Cardiology at Virgen Del Rocío University Hospital, Sevilla, Spain
| | - Manuel Frutos-López
- Arrhythmia Unit, Department of Cardiology at Virgen Del Rocío University Hospital, Sevilla, Spain
| | - Juan A. Sánchez-Brotons
- Arrhythmia Unit, Department of Cardiology at Virgen Del Rocío University Hospital, Sevilla, Spain
| | - Helena Llamas-López
- Arrhythmia Unit, Department of Cardiology at Virgen Del Rocío University Hospital, Sevilla, Spain
| | | | | | - Oscar Camara
- PhySense Research Group, BCN MedTech, Universitat Pompeu Fabra, Barcelona, Spain
| | - Alonso Pedrote
- Arrhythmia Unit, Department of Cardiology at Virgen Del Rocío University Hospital, Sevilla, Spain
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2
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Escribano P, Ródenas J, García M, Hornero F, Gracia-Baena JM, Alcaraz R, Rieta JJ. Novel Entropy-Based Metrics for Long-Term Atrial Fibrillation Recurrence Prediction Following Surgical Ablation: Insights from Preoperative Electrocardiographic Analysis. ENTROPY (BASEL, SWITZERLAND) 2023; 26:28. [PMID: 38248154 PMCID: PMC11154238 DOI: 10.3390/e26010028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 12/23/2023] [Accepted: 12/26/2023] [Indexed: 01/23/2024]
Abstract
Atrial fibrillation (AF) is a prevalent cardiac arrhythmia often treated concomitantly with other cardiac interventions through the Cox-Maze procedure. This highly invasive intervention is still linked to a long-term recurrence rate of approximately 35% in permanent AF patients. The aim of this study is to preoperatively predict long-term AF recurrence post-surgery through the analysis of atrial activity (AA) organization from non-invasive electrocardiographic (ECG) recordings. A dataset comprising ECGs from 53 patients with permanent AF who had undergone Cox-Maze concomitant surgery was analyzed. The AA was extracted from the lead V1 of these recordings and then characterized using novel predictors, such as the mean and standard deviation of the relative wavelet energy (RWEm and RWEs) across different scales, and an entropy-based metric that computes the stationary wavelet entropy variability (SWEnV). The individual predictors exhibited limited predictive capabilities to anticipate the outcome of the procedure, with the SWEnV yielding a classification accuracy (Acc) of 68.07%. However, the assessment of the RWEs for the seventh scale (RWEs7), which encompassed frequencies associated with the AA, stood out as the most promising individual predictor, with sensitivity (Se) and specificity (Sp) values of 80.83% and 67.09%, respectively, and an Acc of almost 75%. Diverse multivariate decision tree-based models were constructed for prediction, giving priority to simplicity in the interpretation of the forecasting methodology. In fact, the combination of the SWEnV and RWEs7 consistently outperformed the individual predictors and excelled in predicting post-surgery outcomes one year after the Cox-Maze procedure, with Se, Sp, and Acc values of approximately 80%, thus surpassing the results of previous studies based on anatomical predictors associated with atrial function or clinical data. These findings emphasize the crucial role of preoperative patient-specific ECG signal analysis in tailoring post-surgical care, enhancing clinical decision making, and improving long-term clinical outcomes.
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Affiliation(s)
- Pilar Escribano
- Research Group in Electronic, Biomedical and Telecommunication Engineering, University of Castilla-La Mancha, 02071 Albacete, Spain; (P.E.); (J.R.); (M.G.); (R.A.)
| | - Juan Ródenas
- Research Group in Electronic, Biomedical and Telecommunication Engineering, University of Castilla-La Mancha, 02071 Albacete, Spain; (P.E.); (J.R.); (M.G.); (R.A.)
| | - Manuel García
- Research Group in Electronic, Biomedical and Telecommunication Engineering, University of Castilla-La Mancha, 02071 Albacete, Spain; (P.E.); (J.R.); (M.G.); (R.A.)
| | - Fernando Hornero
- Cardiovascular Surgery Department, Hospital Clínico Universitario de Valencia, 46010 Valencia, Spain; (F.H.); (J.M.G.-B.)
| | - Juan M. Gracia-Baena
- Cardiovascular Surgery Department, Hospital Clínico Universitario de Valencia, 46010 Valencia, Spain; (F.H.); (J.M.G.-B.)
| | - Raúl Alcaraz
- Research Group in Electronic, Biomedical and Telecommunication Engineering, University of Castilla-La Mancha, 02071 Albacete, Spain; (P.E.); (J.R.); (M.G.); (R.A.)
| | - José J. Rieta
- BioMIT.org, Electronic Engineering Department, Universitat Politecnica de Valencia, 46022 Valencia, Spain
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3
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Lin CY, Chiang CH, Te ALD, Lin YJ, Lo MT, Lin C, Chang SL, Lo LW, Hu YF, Chung FP, Tuan TC, Chao TF, Liao JN, Chen SA. Characterization and identification of atrial fibrillation drivers in patients with nonparoxysmal atrial fibrillation using simultaneous amplitude frequency electrogram transform. J Cardiovasc Electrophysiol 2023; 34:536-545. [PMID: 36598424 DOI: 10.1111/jce.15806] [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: 08/15/2022] [Revised: 10/08/2022] [Accepted: 12/28/2022] [Indexed: 01/05/2023]
Abstract
INSTRUCTION We hypothesized that real-time simultaneous amplitude frequency electrogram transform (SAFE-T) during sinus rhythm (SR) is able to identify and characterize the drivers of atrial fibrillation (AF) in nonparoxysmal (NP) AF. METHODS Twenty-one NPAF patients (85.71% males, mean age 52 years old) underwent substrate mapping during SR (SAFE-T and voltage) and during AF (complex fractionated atrial electrograms [CFAE] and similarity index [SI]). After pulmonary veins isolation, extensive substrate ablation was performed with the endpoint of procedural termination or elimination of all SI sites (>63% similarities). Sites with procedural termination and non-termination sites were tagged for postablation SR analysis using SAFE-T. RESULTS In 74 CFAE sites identified (average of 3 ± 2 sites per person), 28 (37.84%) were identified as termination sites demonstrating a high SI compared with the non-termination sites (80.11 ± 9.57% vs. 45.96 ± 13.38%, p < .001) during AF. During SR, these termination sites have high SAFE-T values and harbor a highly resonant, localized, repetitive high frequency components superimposed in the low frequency components compared with non-termination sites (5.70 ± 3.04 vs. 1.49 ± 1.66 Hz·mV, p < .001). In the multivariate analysis, the termination sites have higher SAFE-T and SI value (p < .001). CONCLUSION AF procedural termination sites harbored signal characteristics of repetitive, high frequency component of individualized electrogram during SR, which can be masked by the low frequency fractionated electrogram and are difficult to see from the bipolar electrogram. Thus, SAFE-T mapping is feasible in identifying and characterizing sites of AF drivers.
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Affiliation(s)
- Chin-Yu Lin
- Department of Medicine, Division of Cardiology, Heart Rhythm Center, Taipei Veterans General Hospital, Taipei, Taiwan.,Cardiovascular Research Center, Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chia-Hsin Chiang
- Department of Medicine, Division of Cardiology, Heart Rhythm Center, Taipei Veterans General Hospital, Taipei, Taiwan.,Research Center for Adaptive Analysis, Taoyuan City, Taiwan.,Center for Dynamical Biomarkers and Translational Medicine, National Central University, Chungli, Taiwan
| | - Abigail Louise D Te
- Department of Medicine, Division of Cardiology, Heart Rhythm Center, Taipei Veterans General Hospital, Taipei, Taiwan.,Heart Institute, St. Luke's Medical Center, Global City, Philippines
| | - Yenn-Jiang Lin
- Department of Medicine, Division of Cardiology, Heart Rhythm Center, Taipei Veterans General Hospital, Taipei, Taiwan.,Cardiovascular Research Center, Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Men-Tzung Lo
- Research Center for Adaptive Analysis, Taoyuan City, Taiwan.,Center for Dynamical Biomarkers and Translational Medicine, National Central University, Chungli, Taiwan
| | - Chen Lin
- Center for Dynamical Biomarkers and Translational Medicine, National Central University, Chungli, Taiwan.,Heart Institute, St. Luke's Medical Center, Global City, Philippines
| | - Shih-Lin Chang
- Department of Medicine, Division of Cardiology, Heart Rhythm Center, Taipei Veterans General Hospital, Taipei, Taiwan.,Cardiovascular Research Center, Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Li-Wei Lo
- Department of Medicine, Division of Cardiology, Heart Rhythm Center, Taipei Veterans General Hospital, Taipei, Taiwan.,Cardiovascular Research Center, Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yu-Feng Hu
- Department of Medicine, Division of Cardiology, Heart Rhythm Center, Taipei Veterans General Hospital, Taipei, Taiwan.,Cardiovascular Research Center, Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Fa-Po Chung
- Department of Medicine, Division of Cardiology, Heart Rhythm Center, Taipei Veterans General Hospital, Taipei, Taiwan.,Cardiovascular Research Center, Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Ta-Chuan Tuan
- Department of Medicine, Division of Cardiology, Heart Rhythm Center, Taipei Veterans General Hospital, Taipei, Taiwan.,Cardiovascular Research Center, Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Tze-Fan Chao
- Department of Medicine, Division of Cardiology, Heart Rhythm Center, Taipei Veterans General Hospital, Taipei, Taiwan.,Cardiovascular Research Center, Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Jo-Nan Liao
- Department of Medicine, Division of Cardiology, Heart Rhythm Center, Taipei Veterans General Hospital, Taipei, Taiwan.,Cardiovascular Research Center, Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shih-Ann Chen
- Department of Medicine, Division of Cardiology, Heart Rhythm Center, Taipei Veterans General Hospital, Taipei, Taiwan.,Cardiovascular Research Center, Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Department of Medicine, Division of Cardiology, Taichung Veterans General Hospital, Taichung, Taiwan
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4
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Osorio D, Vraka A, Moreno-Arribas J, Bertomeu-González V, Alcaraz R, Rieta JJ. Comparative Study of Methods for Cycle Length Estimation in Fractionated Electrograms of Atrial Fibrillation. J Pers Med 2022; 12:jpm12101712. [PMID: 36294851 PMCID: PMC9604643 DOI: 10.3390/jpm12101712] [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: 08/25/2022] [Revised: 10/04/2022] [Accepted: 10/11/2022] [Indexed: 11/07/2022] Open
Abstract
Atrial cycle length (CL) is an important feature for the analysis of electrogram (EGM) characteristics acquired during catheter ablation (CA) of atrial fibrillation (AF), the commonest cardiac arrhythmia. Nevertheless, a robust ACL estimator requires the precise detection of local activation waves (LAWs), which still remains a challenge. This work aims to compare the performance in (CL) estimation, especially under fractionated EGMs, of three different LAW detection methods relying on different operation strategies. The methods are based on the hyperbolic tangent (HT) function, an adaptive amplitude threshold (AAT) and a (CL) iteration (ACLI), respectively. For each method, LAW detection has been assessed with respect to manual annotations made by two experts and performance has been estimated by confusion matrix and mean and individual (CL) error calculation by EGM types of fractionation. The influence of EGM length on the individual (CL) error has been additionally considered. For the HT method, accuracy, sensitivity and precision were 92.77–100%, while for the AAT and ACLI methods they were 78.89–99.91% for all EGM types. The CL error on the HT method was lower than AAT and ACLI methods (up to 12 ms versus up to 20 ms), with the difference being more prominent in complex EGMs. The HT method also showed the lowest dependency on EGM length, presenting the lowest and least variable error values. Therefore, the HT method achieves higher performance in (CL) estimation in comparison with previous LAW detection techniques. The high robustness and precision demonstrated by this method suggest its implementation on CA mapping devices for a more successful location of ablation targets and improved results during CA procedures.
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Affiliation(s)
- Diego Osorio
- BioMIT.org, Electronic Engineering Department, Universitat Politecnica de Valencia, 46022 Valencia, Spain
| | - Aikaterini Vraka
- BioMIT.org, Electronic Engineering Department, Universitat Politecnica de Valencia, 46022 Valencia, Spain
| | - José Moreno-Arribas
- Cardiology Department, Saint John’s University Hospital, 03550 Alicante, Spain
| | | | - Raúl Alcaraz
- Research Group in Electronic, Biomedical and Telecommunication Engineering, University of Castilla-La Mancha, 16071 Cuenca, Spain
| | - José J. Rieta
- BioMIT.org, Electronic Engineering Department, Universitat Politecnica de Valencia, 46022 Valencia, Spain
- Correspondence:
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5
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Prudat Y, Luca A, Yazdani S, Derval N, Jaïs P, Roten L, Berte B, Pruvot E, Vesin JM, Pascale P. Evaluation and optimization of novel extraction algorithms for the automatic detection of atrial activations recorded within the pulmonary veins during atrial fibrillation. BMC Med Inform Decis Mak 2022; 22:225. [PMID: 36031620 PMCID: PMC9420290 DOI: 10.1186/s12911-022-01969-5] [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: 04/12/2022] [Accepted: 08/10/2022] [Indexed: 11/13/2022] Open
Abstract
Background and objective The automated detection of atrial activations (AAs) recorded from intracardiac electrograms (IEGMs) during atrial fibrillation (AF) is challenging considering their various amplitudes, morphologies and cycle length. Activation time estimation is further complicated by the constant changes in the IEGM active zones in complex and/or fractionated signals. We propose a new method which provides reliable automatic extraction of intracardiac AAs recorded within the pulmonary veins during AF and an accurate estimation of their local activation times.
Methods First, two recently developed algorithms were evaluated and optimized on 118 recordings of pulmonary vein IEGM taken from 35 patients undergoing ablation of persistent AF. The adaptive mathematical morphology algorithm (AMM) uses an adaptive structuring element to extract AAs based on their morphological features. The relative-energy algorithm (Rel-En) uses short- and long-term energies to enhance and detect the AAs in the IEGM signals. Second, following the AA extraction, the signal amplitude was weighted using statistics of the AA sequences in order to reduce over- and undersensing of the algorithms. The detection capacity of our algorithms was compared with manually annotated activations and with two previously developed algorithms based on the Teager–Kaiser energy operator and the AF cycle length iteration, respectively. Finally, a method based on the barycenter was developed to reduce artificial variations in the activation annotations of complex IEGM signals. Results The best detection was achieved using Rel-En, yielding a false negative rate of 0.76% and a false positive rate of only 0.12% (total error rate 0.88%) against expert annotation. The post-processing further reduced the total error rate of the Rel-En algorithm by 70% (yielding to a final total error rate of 0.28%). Conclusion The proposed method shows reliable detection and robust temporal annotation of AAs recorded within pulmonary veins in AF. The method has low computational cost and high robustness for automatic detection of AAs, which makes it a suitable approach for online use in a procedural context.
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6
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Osorio D, Vraka A, Quesada A, Hornero F, Alcaraz R, Rieta JJ. An Efficient Hybrid Methodology for Local Activation Waves Detection under Complex Fractionated Atrial Electrograms of Atrial Fibrillation. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22145345. [PMID: 35891025 PMCID: PMC9316244 DOI: 10.3390/s22145345] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 07/06/2022] [Accepted: 07/15/2022] [Indexed: 05/04/2023]
Abstract
Local activation waves (LAWs) detection in complex fractionated atrial electrograms (CFAEs) during catheter ablation (CA) of atrial fibrillation (AF), the commonest cardiac arrhythmia, is a complicated task due to their extreme variability and heterogeneity in amplitude and morphology. There are few published works on reliable LAWs detectors, which are efficient for regular or low fractionated bipolar electrograms (EGMs) but lack satisfactory results when CFAEs are analyzed. The aim of the present work is the development of a novel optimized method for LAWs detection in CFAEs in order to assist cardiac mapping and catheter ablation (CA) guidance. The database consists of 119 bipolar EGMs classified by AF types according to Wells' classification. The proposed method introduces an alternative Botteron's preprocessing technique targeting the slow and small-ampitude activations. The lower band-pass filter cut-off frequency is modified to 20 Hz, and a hyperbolic tangent function is applied over CFAEs. Detection is firstly performed through an amplitude-based threshold and an escalating cycle-length (CL) analysis. Activation time is calculated at each LAW's barycenter. Analysis is applied in five-second overlapping segments. LAWs were manually annotated by two experts and compared with algorithm-annotated LAWs. AF types I and II showed 100% accuracy and sensitivity. AF type III showed 92.77% accuracy and 95.30% sensitivity. The results of this study highlight the efficiency of the developed method in precisely detecting LAWs in CFAEs. Hence, it could be implemented on real-time mapping devices and used during CA, providing robust detection results regardless of the fractionation degree of the analyzed recordings.
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Affiliation(s)
- Diego Osorio
- BioMIT.org, Electronic Engineering Department, Universitat Politecnica de Valencia, 46022 Valencia, Spain; (D.O.); (A.V.)
| | - Aikaterini Vraka
- BioMIT.org, Electronic Engineering Department, Universitat Politecnica de Valencia, 46022 Valencia, Spain; (D.O.); (A.V.)
| | - Aurelio Quesada
- Arrhythmia Unit, Cardiology Department, General University Hospital Consortium of Valencia, 46014 Valencia, Spain;
| | - Fernando Hornero
- Cardiovascular Surgery Department, Hospital Clínico Universitario de Valencia, 46010 Valencia, Spain;
| | - Raúl Alcaraz
- Research Group in Electronic, Biomedical and Telecommunication Engineering, University of Castilla-La Mancha, 16071 Cuenca, Spain;
| | - José J. Rieta
- BioMIT.org, Electronic Engineering Department, Universitat Politecnica de Valencia, 46022 Valencia, Spain; (D.O.); (A.V.)
- Correspondence:
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7
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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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8
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O'Shea C, Winter J, Holmes AP, Johnson DM, Correia JN, Kirchhof P, Fabritz L, Rajpoot K, Pavlovic D. Temporal irregularity quantification and mapping of optical action potentials using wave morphology similarity. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2020; 157:84-93. [PMID: 31899215 PMCID: PMC7607254 DOI: 10.1016/j.pbiomolbio.2019.12.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 11/08/2019] [Accepted: 12/20/2019] [Indexed: 01/14/2023]
Abstract
BACKGROUND Cardiac optical mapping enables direct and high spatio-temporal resolution recording of action potential (AP) morphology. Temporal alterations in AP morphology are both predictive and consequent of arrhythmia. Here we sought to test if methods that quantify regularity of recorded waveforms could be applied to detect and quantify periods of temporal instability in optical mapping datasets in a semi-automated, user-unbiased manner. METHODS AND RESULTS We developed, tested and applied algorithms to quantify optical wave similarity (OWS) to study morphological temporal similarity of optically recorded APs. Unlike other measures (e.g. alternans ratio, beat-to-beat variability, arrhythmia scoring), the quantification of OWS is achieved without a restrictive definition of specific signal points/features and is instead derived by analysing the complete morphology from the entire AP waveform. Using model datasets, we validated the ability of OWS to measure changes in AP morphology, and tested OWS mapping in guinea pig hearts and mouse atria. OWS successfully detected and measured alterations in temporal regularity in response to several proarrhythmic stimuli, including alterations in pacing frequency, premature contractions, alternans and ventricular fibrillation. CONCLUSION OWS mapping provides an effective measure of temporal regularity that can be applied to optical datasets to detect and quantify temporal alterations in action potential morphology. This methodology provides a new metric for arrhythmia inducibility and scoring in optical mapping datasets.
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Affiliation(s)
- Christopher O'Shea
- Institute of Cardiovascular Sciences, University of Birmingham, UK; EPSRC Centre for Doctoral Training in Physical Sciences for Health, School of Chemistry, University of Birmingham, UK; School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK
| | - James Winter
- Institute of Cardiovascular Sciences, University of Birmingham, UK
| | - Andrew P Holmes
- Institute of Cardiovascular Sciences, University of Birmingham, UK; Institute of Clinical Sciences, University of Birmingham, UK
| | - Daniel M Johnson
- Institute of Cardiovascular Sciences, University of Birmingham, UK
| | - Joao N Correia
- Institute of Microbiology and Infection, School of Biosciences, University of Birmingham, UK
| | - Paulus Kirchhof
- Institute of Cardiovascular Sciences, University of Birmingham, UK; Department of Cardiology, UHB NHS Foundation Trust, Birmingham, UK; Cardiology Specialty, SWBH NHS Trust, Birmingham, UK
| | - Larissa Fabritz
- Institute of Cardiovascular Sciences, University of Birmingham, UK; Department of Cardiology, UHB NHS Foundation Trust, Birmingham, UK
| | - Kashif Rajpoot
- School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK.
| | - Davor Pavlovic
- Institute of Cardiovascular Sciences, University of Birmingham, UK.
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9
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Corino VDA, Iozzia L, Scarpini G, Mainardi LT, Lombardi F. A simple model to detect atrial fibrillation via visual imaging. BIOMED ENG-BIOMED TE 2020; 65:/j/bmte.ahead-of-print/bmt-2019-0153/bmt-2019-0153.xml. [PMID: 32663168 DOI: 10.1515/bmt-2019-0153] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Accepted: 02/21/2020] [Indexed: 11/15/2022]
Abstract
Automatic detection of atrial fibrillation (AF) is a challenging issue. In this study we proposed and validated a model to identify AF by using facial video recordings. We analyzed photoplethysmographic imaging (PPGi) signals, extracted from video of a subject's face. Sixty-eight patients were included: 30 in sinus rhythm (SR), 25 in AF and 13 presenting with atrial flutter or frequent ectopic beats (ARR). Twenty-six indexes were computed. The dataset was divided in three subsets: the training, validation, and test set, containing, respectively, 58, 29, and 13% of the data. Mean of inter-systolic interval series (M), Local Maxima Similarity (LMS), and pulse harmonic strength (PHS) indexes were significantly different among all groups. Variability and irregularity parameters had the lowest values in SR, the highest in AF, with intermediate values in ARR. The PHS was higher in SR than in ARR, and higher in ARR than in AF. The LMS index was the highest in SR, intermediate in ARR and the lowest in AF. Similarity indexes were higher in SR than in AF and ARR. A model with three features, namely M, Similarity1 and LMS was chosen. With this model, the accuracy for the validation set was 0.947±0.007 for SR, 0.954±0.004 for AF and 0.919±0.006 for ARR; for the test set (never-seen data), accuracy was 0.876±0.021 for SR, 0.870±0.030 for AF and 0.863±0.029 for ARR. A contactless video-based monitoring can be used to detect AF, differentiating it from SR and from frequent ectopies.
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Affiliation(s)
- Valentina D A Corino
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Luca Iozzia
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Giorgio Scarpini
- Fondazione IRCCS Ca Granda Ospedale Maggiore Policlinico, U.O.C. di Malattie Cardiovascolari, Università degli Studi di Milano, Dipartimento di Scienze Cliniche e di Comunità, Milan, Italy
| | - Luca T Mainardi
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Federico Lombardi
- Fondazione IRCCS Ca Granda Ospedale Maggiore Policlinico, U.O.C. di Malattie Cardiovascolari, Università degli Studi di Milano, Dipartimento di Scienze Cliniche e di Comunità, Milan, Italy
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10
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Classification of intracavitary electrograms in atrial fibrillation using information and complexity measures. Biomed Signal Process Control 2020. [DOI: 10.1016/j.bspc.2019.101753] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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11
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Lim B, Kim J, Hwang M, Song JS, Lee JK, Yu HT, Kim TH, Uhm JS, Joung B, Lee MH, Pak HN. In situ procedure for high-efficiency computational modeling of atrial fibrillation reflecting personal anatomy, fiber orientation, fibrosis, and electrophysiology. Sci Rep 2020; 10:2417. [PMID: 32051487 PMCID: PMC7016008 DOI: 10.1038/s41598-020-59372-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Accepted: 11/06/2019] [Indexed: 12/22/2022] Open
Abstract
We previously reported the feasibility and efficacy of a simulation-guided clinical catheter ablation of atrial fibrillation (AF) in an in-silico AF model. We developed a highly efficient realistic AF model reflecting the patient endocardial voltage and local conduction and tested its clinical feasibility. We acquired > 500 endocardial bipolar electrograms during right atrial pacing at the beginning of the AF ablation procedures. Based on the clinical bipolar electrograms, we generated simulated voltage maps by applying fibrosis and local activation maps adjusted for the fiber orientation. The software's accuracy (CUVIA2.5) was retrospectively tested in 17 patients and feasibility prospectively in 10 during clinical AF ablation. Results: We found excellent correlations between the clinical and simulated voltage maps (R = 0.933, p < 0.001) and clinical and virtual local conduction (R = 0.958, p < 0.001). The proportion of virtual local fibrosis was 15.4, 22.2, and 36.9% in the paroxysmal AF, persistent AF, and post-pulmonary vein isolation (PVI) states, respectively. The reconstructed virtual bipolar electrogram exhibited a relatively good similarities of morphology to the local clinical bipolar electrogram (R = 0.60 ± 0.08, p < 0.001). Feasibility testing revealed an in situ procedural computing time from the clinical data acquisition to wave-dynamics analyses of 48.2 ± 4.9 min. All virtual analyses were successfully achieved during clinical PVI procedures. We developed a highly efficient, realistic, in situ procedural simulation model reflective of individual anatomy, fiber orientation, fibrosis, and electrophysiology that can be applied during AF ablation.
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Affiliation(s)
- Byounghyun Lim
- Yonsei University Health System, Seoul, Republic of Korea
| | - Jaehyeok Kim
- Yonsei University Health System, Seoul, Republic of Korea
| | - Minki Hwang
- Yonsei University Health System, Seoul, Republic of Korea
| | - Jun-Seop Song
- Yonsei University Health System, Seoul, Republic of Korea
| | - Jung Ki Lee
- Yonsei University Health System, Seoul, Republic of Korea
| | - Hee-Tae Yu
- Yonsei University Health System, Seoul, Republic of Korea
| | - Tae-Hoon Kim
- Yonsei University Health System, Seoul, Republic of Korea
| | - Jae-Sun Uhm
- Yonsei University Health System, Seoul, Republic of Korea
| | - Boyoung Joung
- Yonsei University Health System, Seoul, Republic of Korea
| | - Moon-Hyung Lee
- Yonsei University Health System, Seoul, Republic of Korea
| | - Hui-Nam Pak
- Yonsei University Health System, Seoul, Republic of Korea.
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Martínez-Iniesta M, Ródenas J, Rieta JJ, Alcaraz R. The stationary wavelet transform as an efficient reductor of powerline interference for atrial bipolar electrograms in cardiac electrophysiology. Physiol Meas 2019; 40:075003. [PMID: 31239416 DOI: 10.1088/1361-6579/ab2cb8] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE The most relevant source of signal contamination in the cardiac electrophysiology (EP) laboratory is the ubiquitous powerline interference (PLI). To reduce this perturbation, algorithms including common fixed-bandwidth and adaptive-notch filters have been proposed. Although such methods have proven to add artificial fractionation to intra-atrial electrograms (EGMs), they are still frequently used. However, such morphological alteration can conceal the accurate interpretation of EGMs, specially to evaluate the mechanisms supporting atrial fibrillation (AF), which is the most common cardiac arrhythmia. Given the clinical relevance of AF, a novel algorithm aimed at reducing PLI on highly contaminated bipolar EGMs and, simultaneously, preserving their morphology is proposed. APPROACH The method is based on the wavelet shrinkage and has been validated through customized indices on a set of synthesized EGMs to accurately quantify the achieved level of PLI reduction and signal morphology alteration. Visual validation of the algorithm's performance has also been included for some real EGM excerpts. MAIN RESULTS The method has outperformed common filtering-based and wavelet-based strategies in the analyzed scenario. Moreover, it possesses advantages such as insensitivity to amplitude and frequency variations in the PLI, and the capability of joint removal of several interferences. SIGNIFICANCE The use of this algorithm in routine cardiac EP studies may enable improved and truthful evaluation of AF mechanisms.
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Affiliation(s)
- Miguel Martínez-Iniesta
- Research Group in Electronic, Biomedical and Telecommunication Engineering, University of Castilla-La Mancha, Albacete, Spain
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13
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Orozco-Duque A, Tobón C, Ugarte JP, Morillo C, Bustamante J. Electroanatomical mapping based on discrimination of electrograms clusters for localization of critical sites in atrial fibrillation. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2019; 141:37-46. [DOI: 10.1016/j.pbiomolbio.2018.07.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Revised: 05/07/2018] [Accepted: 07/03/2018] [Indexed: 11/30/2022]
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14
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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.
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15
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Feature subset selection and classification of intracardiac electrograms during atrial fibrillation. Biomed Signal Process Control 2017. [DOI: 10.1016/j.bspc.2017.06.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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16
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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]
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17
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Hummel JP, Baher A, Buck B, Fanarjian M, Webber CL, Akar JG. A method for quantifying recurrent patterns of local wavefront direction during atrial fibrillation. Comput Biol Med 2017; 89:497-504. [PMID: 28889077 DOI: 10.1016/j.compbiomed.2017.08.027] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Revised: 08/24/2017] [Accepted: 08/25/2017] [Indexed: 10/18/2022]
Abstract
INTRODUCTION Spiral wave reentry is a potential mechanism of atrial fibrillation (AF), but is difficult to differentiate clinically from multiple wavelet breakup using standard bipolar recordings. We developed a new methodology using bipolar recordings to estimate the direction of local activation wavefronts during AF by calculating the electrogram conformation (Egm-C). We subsequently used recurrence quantification analysis (RQA) of Egm-C to differentiate regions of spiral wave reentry from wavelet breakup. METHODS A 2D computer simulation was created with regions containing a stable spiral wave and also regions of wavebreak. A grid of 40 × 40 unipolar electrodes was superimposed. At each site, the actual wavefront direction (WD) was determined by comparing relative activation timings of the local intracellular recordings, and the estimated wavefront direction (Egm-C) was determined from the morphology of the local bipolar electrogram. RQA of Egm-C was compared to RQA of actual WD in order to differentiate AF mechanisms. RESULTS RQA of actual WD and Egm-C both distinguished regions of spiral wave reentry from wavelet breakup with high correlation between the two methods (recurrence rate, r = 0.96; determinism, r = 0.61; line max, r = 0.95; entropy, r = 0.84; p < 0.001 for all). In areas of stable spiral wave reentry, the recurrence plots of both Egm-C and actual WD demonstrated stable, periodic dynamics, while regions of wavelet breakup demonstrated chaotic behavior largely devoid of repetitive activation patterns. CONCLUSION Calculation of Egm-C allows RQA to be performed on bipolar electrograms during AF and differentiates regions of spiral wave reentry from multiple wavelet breakup.
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Affiliation(s)
- James P Hummel
- Division of Cardiology, University of North Carolina, Chapel Hill, NC, USA.
| | - Alex Baher
- The Section of Cardiovascular Medicine, Department of Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Ben Buck
- Division of Cardiology, University of North Carolina, Chapel Hill, NC, USA
| | - Manuel Fanarjian
- Division of Cardiology, University of North Carolina, Chapel Hill, NC, USA
| | - Charles L Webber
- Department of Cell and Molecular Physiology, Loyola University Chicago - Health Sciences Division, Maywood, IL, USA
| | - Joseph G Akar
- The Section of Cardiovascular Medicine, Department of Medicine, Yale University School of Medicine, New Haven, CT, 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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19
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Masè M, Disertori M, Marini M, Ravelli F. Characterization of rate and regularity of ventricular response during atrial tachyarrhythmias. Insight on atrial and nodal determinants. Physiol Meas 2017; 38:800-818. [DOI: 10.1088/1361-6579/aa6388] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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20
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Corino VDA, Laureanti R, Ferranti L, Scarpini G, Lombardi F, Mainardi LT. Detection of atrial fibrillation episodes using a wristband device. Physiol Meas 2017; 38:787-799. [DOI: 10.1088/1361-6579/aa5dd7] [Citation(s) in RCA: 65] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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21
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Waveform Integrity in Atrial Fibrillation: The Forgotten Issue of Cardiac Electrophysiology. Ann Biomed Eng 2017; 45:1890-1907. [PMID: 28421394 DOI: 10.1007/s10439-017-1832-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2016] [Accepted: 04/05/2017] [Indexed: 01/17/2023]
Abstract
Atrial fibrillation (AF) is the most common arrhythmia in clinical practice with an increasing prevalence of about 15% in the elderly. Despite other alternatives, catheter ablation is currently considered as the first-line therapy for the treatment of AF. This strategy relies on cardiac electrophysiology systems, which use intracardiac electrograms (EGM) as the basis to determine the cardiac structures contributing to sustain the arrhythmia. However, the noise-free acquisition of these recordings is impossible and they are often contaminated by different perturbations. Although suppression of nuisance signals without affecting the original EGM pattern is essential for any other later analysis, not much attention has been paid to this issue, being frequently considered as trivial. The present work introduces the first thorough study on the significant fallout that regular filtering, aimed at reducing acquisition noise, provokes on EGM pattern morphology. This approach has been compared with more refined denoising strategies. Performance has been assessed both in time and frequency by well established parameters for EGM characterization. The study comprised synthesized and real EGMs with unipolar and bipolar recordings. Results reported that regular filtering altered substantially atrial waveform morphology and was unable to remove moderate amounts of noise, thus turning time and spectral characterization of the EGM notably inaccurate. Methods based on Wavelet transform provided the highest ability to preserve EGM morphology with improvements between 20 and beyond 40%, to minimize dominant atrial frequency estimation error with up to 25% reduction, as well as to reduce huge levels of noise with up to 10 dB better reduction. Consequently, these algorithms are recommended as a replacement of regular filtering to avoid significant alterations in the EGMs. This could lead to more accurate and truthful analyses of atrial activity dynamics aimed at understanding and locating the sources of AF.
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22
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Song JS, Lee YS, Hwang M, Lee JK, Li C, Joung B, Lee MH, Shim EB, Pak HN. Spatial reproducibility of complex fractionated atrial electrogram depending on the direction and configuration of bipolar electrodes: an in-silico modeling study. THE KOREAN JOURNAL OF PHYSIOLOGY & PHARMACOLOGY : OFFICIAL JOURNAL OF THE KOREAN PHYSIOLOGICAL SOCIETY AND THE KOREAN SOCIETY OF PHARMACOLOGY 2016; 20:507-14. [PMID: 27610037 PMCID: PMC5014997 DOI: 10.4196/kjpp.2016.20.5.507] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/09/2016] [Revised: 07/08/2016] [Accepted: 07/11/2016] [Indexed: 12/02/2022]
Abstract
Although 3D-complex fractionated atrial electrogram (CFAE) mapping is useful in radiofrequency catheter ablation for persistent atrial fibrillation (AF), the directions and configuration of the bipolar electrodes may affect the electrogram. This study aimed to compare the spatial reproducibility of CFAE by changing the catheter orientations and electrode distance in an in-silico left atrium (LA). We conducted this study by importing the heart CT image of a patient with AF into a 3D-homogeneous human LA model. Electrogram morphology, CFAE-cycle lengths (CLs) were compared for 16 different orientations of a virtual bipolar conventional catheter (conv-cath: size 3.5 mm, inter-electrode distance 4.75 mm). Additionally, the spatial correlations of CFAE-CLs and the percentage of consistent sites with CFAE-CL<120 ms were analyzed. The results from the conv-cath were compared with that obtained using a mini catheter (mini-cath: size 1 mm, inter-electrode distance 2.5 mm). Depending on the catheter orientation, the electrogram morphology and CFAE-CLs varied (conv-cath: 11.5±0.7% variation, mini-cath: 7.1±1.2% variation), however the mini-cath produced less variation of CFAE-CL than conv-cath (p<0.001). There were moderate spatial correlations among CFAE-CL measured at 16 orientations (conv-cath: r=0.3055±0.2194 vs. mini-cath: 0.6074±0.0733, p<0.001). Additionally, the ratio of consistent CFAE sites was higher for mini catheter than conventional one (38.3±4.6% vs. 22.3±1.4%, p<0.05). Electrograms and CFAE distribution are affected by catheter orientation and electrode configuration in the in-silico LA model. However, there was moderate spatial consistency of CFAE areas, and narrowly spaced bipolar catheters were less influenced by catheter direction than conventional catheters.
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Affiliation(s)
- Jun-Seop Song
- Division of Cardiology, Yonsei University Health System, Seoul 03722, Korea
| | - Young-Seon Lee
- Division of Cardiology, Yonsei University Health System, Seoul 03722, Korea
| | - Minki Hwang
- Division of Cardiology, Yonsei University Health System, Seoul 03722, Korea
| | - Jung-Kee Lee
- Division of Cardiology, Yonsei University Health System, Seoul 03722, Korea
| | - Changyong Li
- Division of Cardiology, Yonsei University Health System, Seoul 03722, Korea
| | - Boyoung Joung
- Division of Cardiology, Yonsei University Health System, Seoul 03722, Korea
| | - Moon-Hyoung Lee
- Division of Cardiology, Yonsei University Health System, Seoul 03722, Korea
| | - Eun Bo Shim
- Department of Mechanical and Biomedical Engineering, Kangwon National University, Chuncheon 24341, Korea
| | - Hui-Nam Pak
- Division of Cardiology, Yonsei University Health System, Seoul 03722, Korea
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Orozco-Duque A, Bustamante J, Castellanos-Dominguez G. Semi-supervised clustering of fractionated electrograms for electroanatomical atrial mapping. Biomed Eng Online 2016; 15:44. [PMID: 27117088 PMCID: PMC4845510 DOI: 10.1186/s12938-016-0154-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2015] [Accepted: 04/01/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Electrogram-guided ablation procedures have been proposed as an alternative strategy consisting of either mapping and ablating focal sources or targeting complex fractionated electrograms in atrial fibrillation (AF). However, the incomplete understanding of the mechanism of AF makes difficult the decision of detecting the target sites. To date, feature extraction from electrograms is carried out mostly based on the time-domain morphology analysis and non-linear features. However, their combination has been reported to achieve better performance. Besides, most of the inferring approaches applied for identifying the levels of fractionation are supervised, which lack of an objective description of fractionation. This aspect complicates their application on EGM-guided ablation procedures. METHODS This work proposes a semi-supervised clustering method of four levels of fractionation. In particular, we make use of the spectral clustering that groups a set of widely used features extracted from atrial electrograms. We also introduce a new atrial-deflection-based feature to quantify the fractionated activity. Further, based on the sequential forward selection, we find the optimal subset that provides the highest performance in terms of the cluster validation. The method is tested on external validation of a labeled database. The generalization ability of the proposed training approach is tested to aid semi-supervised learning on unlabeled dataset associated with anatomical information recorded from three patients. RESULTS A joint set of four extracted features, based on two time-domain morphology analysis and two non-linear dynamics, are selected. To discriminate between four considered levels of fractionation, validation on a labeled database performs a suitable accuracy (77.6 %). Results show a congruence value of internal validation index among tested patients that is enough to reconstruct the patterns over the atria to located critical sites with the benefit of avoiding previous manual classification of AF types. CONCLUSIONS To the best knowledge of the authors, this is the first work reporting semi-supervised clustering for distinguishing patterns in fractionated electrograms. The proposed methodology provides high performance for the detection of unknown patterns associated with critical EGM morphologies. Particularly, obtained results of semi-supervised training show the advantage of demanding fewer labeled data and less training time without significantly compromising accuracy. This paper introduces a new method, providing an objective scheme that enables electro-physiologist to recognize the diverse EGM morphologies reliably.
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Affiliation(s)
- Andres Orozco-Duque
- Bioengineering Center, Universidad Pontificia Bolivariana, Medellin, Colombia. .,GI2B, Instituto Tecnologico Metropolitano, Medellin, Colombia.
| | - John Bustamante
- Bioengineering Center, Universidad Pontificia Bolivariana, Medellin, Colombia
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Orozco-Duque A, Novak D, Kremen V, Bustamante J. Multifractal analysis for grading complex fractionated electrograms in atrial fibrillation. Physiol Meas 2015; 36:2269-84. [DOI: 10.1088/0967-3334/36/11/2269] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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25
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Julián M, Alcaraz R, Rieta JJ. Application of Hurst exponents to assess atrial reverse remodeling in paroxysmal atrial fibrillation. Physiol Meas 2015; 36:2231-46. [DOI: 10.1088/0967-3334/36/11/2231] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
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26
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Alfonsi E, Cosentino G, Mainardi L, Schindler A, Fresia M, Brighina F, Benazzo M, Moglia A, Alvisi E, Fierro B, Sandrini G. Electrophysiological Investigations of Shape and Reproducibility of Oropharyngeal Swallowing: Interaction with Bolus Volume and Age. Dysphagia 2015; 30:540-50. [PMID: 26271609 DOI: 10.1007/s00455-015-9634-1] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2014] [Accepted: 06/30/2015] [Indexed: 11/28/2022]
Abstract
Electrophysiological assessment provides valuable information on physiological and pathophysiological characteristics of human swallowing. Here, new electrophysiological measures for the evaluation of oropharyngeal swallowing were assessed: (1) the activation pattern of the submental/suprahyoid EMG activity (SHEMG); (2) the reproducibility of the oral and pharyngeal phases of swallowing, by calculating the similarity index (SI) of the SHEMG (SI-SHEMG) and of the laryngeal-pharyngeal mechanogram (SI-LPM) during repeated swallows; and (3) kinesiological measures related to the LPM. An electrophysiological-mechanical method for measuring the activation pattern of the SHEMG, the SI-SHEMG, and the SI-LPM, and maximal LPM velocity and acceleration during swallowing was applied in 65 healthy subjects divided into three age groups (18-39, 40-59, 60 years or over). All the measures were assessed during three trials of eight consecutive swallows of different liquid bolus volumes (3, 12, and 20 ml). A high overall reproducibility of oropharyngeal swallowing in healthy humans was recorded. However, while values of SI-SHEMG were similar in all the age groups, the SI-LPM was found to fall significantly in the older age group. Both the SI-SHEMG and the SI-LPM were found to fall with increasing bolus volumes. The activation pattern of the SHEMG and the LPM kinesiological measures were differently modified by bolus volume and age in the older subjects with respect to the others. We describe a new approach to the electrophysiological study of swallowing based on computed semi-automatic analyses. Our findings provide insight into some previously uninvestigated aspects of oropharyngeal swallowing physiology, considered in relation to bolus volume and age. The new electrophysiological measures here described could prove useful in the clinical setting, as it is likely that they could be differently affected in patients with different kinds of dysphagia.
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Affiliation(s)
- Enrico Alfonsi
- Department of Neurophysiopathology and Neurorehabilitation, National Institute of Neurology, "C. Mondino" Foundation IRCCS, University of Pavia, Pavia, Italy.
| | - Giuseppe Cosentino
- Department of Experimental Biomedicine and Clinical Neurosciences (BioNeC), University of Palermo, Palermo, Italy
| | - Luca Mainardi
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Antonio Schindler
- Department of Otorhinolaryngology, "L. Sacco" Hospital, University of Milan, Milan, Italy
| | - Mauro Fresia
- Department of Neurophysiopathology and Neurorehabilitation, National Institute of Neurology, "C. Mondino" Foundation IRCCS, University of Pavia, Pavia, Italy
| | - Filippo Brighina
- Department of Experimental Biomedicine and Clinical Neurosciences (BioNeC), University of Palermo, Palermo, Italy
| | - Marco Benazzo
- Department of Otorhinolaryngology, "San Matteo" Hospital, University of Pavia, Pavia, Italy
| | - Arrigo Moglia
- Department of Neurophysiopathology and Neurorehabilitation, National Institute of Neurology, "C. Mondino" Foundation IRCCS, University of Pavia, Pavia, Italy
| | - Elena Alvisi
- Department of Neurophysiopathology and Neurorehabilitation, National Institute of Neurology, "C. Mondino" Foundation IRCCS, University of Pavia, Pavia, Italy
| | - Brigida Fierro
- Department of Experimental Biomedicine and Clinical Neurosciences (BioNeC), University of Palermo, Palermo, Italy
| | - Giorgio Sandrini
- Department of Neurophysiopathology and Neurorehabilitation, National Institute of Neurology, "C. Mondino" Foundation IRCCS, University of Pavia, Pavia, Italy
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Masè M, Marini M, Disertori M, Ravelli F. Dynamics of AV coupling during human atrial fibrillation: role of atrial rate. Am J Physiol Heart Circ Physiol 2015; 309:H198-205. [DOI: 10.1152/ajpheart.00726.2014] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2014] [Accepted: 04/21/2015] [Indexed: 11/22/2022]
Abstract
The causal relationship between atrial and ventricular activities during human atrial fibrillation (AF) is poorly understood. This study analyzed the effects of an increase in atrial rate on the link between atrial and ventricular activities during AF. Atrial and ventricular time series were determined in 14 patients during the spontaneous acceleration of the atrial rhythm at AF onset. The dynamic relationship between atrial and ventricular activities was quantified in terms of atrioventricular (AV) coupling by AV synchrogram analysis. The technique identified n: m coupling patterns ( n atrial beats in m ventricular cycles), quantifying their percentage, maximal length, and conduction ratio (= m/ n). Simulations with a difference-equation AV model were performed to correlate the observed dynamics to specific atrial/nodal properties. The atrial rate increase significantly affected AV coupling and ventricular response during AF. The shortening of atrial intervals from 185 ± 32 to 165 ± 24 ms ( P < 0.001) determined transitions toward AV patterns with progressively decreasing m/ n ratios (from conduction ratio = 0.34 ± 0.09 to 0.29 ± 0.08, P < 0.01), lower occurrence (from percentage of coupled beats = 27.1 ± 8.0 to 21.8 ± 6.9%, P < 0.05), and higher instability (from maximal length = 3.9 ± 1.5 to 2.8 ± 0.7 s, P < 0.01). Advanced levels of AV block and coupling instability at higher atrial rates were associated with increased ventricular interval variability (from 123 ± 52 to 133 ± 55 ms, P < 0.05). AV pattern transitions and coupling instability in patients were predicted, assuming the filtering of high-rate irregular atrial beats by the slow recovery of nodal excitability. These results support the role of atrial rate in determining AV coupling and ventricular response and may have implications for rate control in AF.
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Affiliation(s)
- M. Masè
- Department of Physics, University of Trento, Povo-Trento, Italy
| | - M. Marini
- Division of Cardiology, Santa Chiara Hospital, Trento, Italy; and
| | - M. Disertori
- Division of Cardiology, Santa Chiara Hospital, Trento, Italy; and
- Healthcare Research and Innovation Program, PAT-FBK, Trento, Italy
| | - F. Ravelli
- Department of Physics, University of Trento, Povo-Trento, Italy
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Developing a New Computer-Aided Clinical Decision Support System for Prediction of Successful Postcardioversion Patients with Persistent Atrial Fibrillation. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2015; 2015:527815. [PMID: 26120354 PMCID: PMC4450306 DOI: 10.1155/2015/527815] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2014] [Revised: 02/12/2015] [Accepted: 02/17/2015] [Indexed: 11/17/2022]
Abstract
We propose a new algorithm to predict the outcome of direct-current electric (DCE) cardioversion for atrial fibrillation (AF) patients. AF is the most common cardiac arrhythmia and DCE cardioversion is a noninvasive treatment to end AF and return the patient to sinus rhythm (SR). Unfortunately, there is a high risk of AF recurrence in persistent AF patients; hence clinically it is important to predict the DCE outcome in order to avoid the procedure's side effects. This study develops a feature extraction and classification framework to predict AF recurrence patients from the underlying structure of atrial activity (AA). A multiresolution signal decomposition technique, based on matching pursuit (MP), was used to project the AA over a dictionary of wavelets. Seven novel features were derived from the decompositions and were employed in a quadratic discrimination analysis classification to predict the success of post-DCE cardioversion in 40 patients with persistent AF. The proposed algorithm achieved 100% sensitivity and 95% specificity, indicating that the proposed computational approach captures detailed structural information about the underlying AA and could provide reliable information for effective management of AF.
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Iravanian S, Langberg JJ. Spatiotemporal organization during ablation of persistent atrial fibrillation. Heart Rhythm 2015; 12:1937-44. [PMID: 25916566 DOI: 10.1016/j.hrthm.2015.04.027] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2015] [Indexed: 10/23/2022]
Abstract
BACKGROUND Targeting complex fractionated atrial electrograms improves the outcome of ablation of persistent atrial fibrillation (AF); however, the mechanism(s) responsible for the generation of complex fractionated atrial electrogram signals and efficacy of ablation is not clear. OBJECTIVE The aim of this study was to gain mechanistic insight into ablation of persistent AF by evaluating the spatiotemporal patterns of atrial organization during ablation. METHODS Intracardiac recordings from 18 ablation procedures were analyzed. Signals recorded by right atrial/coronary sinus catheters were processed. We quantified atrial organization using recurrence maps and recurrence percentage (Rec%) methodology and generated temporally dense time series of cycle lengths and Rec%. RESULTS A total of 162 intra-atrial recordings were categorized into type I (sudden jump in Rec%), type II (gradual increase), and type III (no increase). Type I was the most common form and was seen in 57% ± 4% of the recordings. A typical pattern was the initial appearance of local organization, which then expanded to adjacent channels in discrete jumps until eventually an organized atrial flutter emerged. This pattern is consistent with the atrial organization signature expected from ablation of a single spiral wave with fibrillatory conduction to the rest of atria. CONCLUSION Temporally dense spatiotemporal assessment of atrial organization during the ablation of persistent AF is feasible and provides complementary information to cycle length measurements. Atrial organization starts locally and expands spatially in discrete jumps. The regularization of AF to atrial flutter exhibits characteristics of phase transition in complex systems.
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Affiliation(s)
- Shahriar Iravanian
- Division of Cardiology-Section of Electrophysiology, Emory University School of Medicine, Atlanta, Georgia
| | - Jonathan J Langberg
- Division of Cardiology-Section of Electrophysiology, Emory University School of Medicine, Atlanta, Georgia.
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Abstract
The sequence of myocardial electrical activation during fibrillation is complex and changes with each cycle. Phase analysis represents the electrical activation-recovery process as an angle. Lines of equal phase converge at a phase singularity at the center of rotation of a reentrant wave, and the identification of reentry and tracking of reentrant wavefronts can be automated. We examine the basic ideas behind phase analysis. With the exciting prospect of using phase analysis of atrial electrograms to guide ablation in the human heart, we highlight several recent developments in preprocessing electrograms so that phase can be estimated reliably.
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Affiliation(s)
- Richard H Clayton
- Insigneo Institute for in-silico medicine and Department of Computer Science, University of Sheffield, Regent Court, 211 Portobello Street, Sheffield S1 4DP, UK.
| | - Martyn P Nash
- Auckland Bioengineering Institute and Engineering Science, University of Auckland, Uniservices House, Level 7, Room 439-715, 70 Symonds Street, Auckland 1010, New Zealand
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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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Alcaine A, Soto-Iglesias D, Calvo M, Guiu E, Andreu D, Fernandez-Armenta J, Berruezo A, Laguna P, Camara O, Martinez JP. A Wavelet-Based Electrogram Onset Delineator for Automatic Ventricular Activation Mapping. IEEE Trans Biomed Eng 2014; 61:2830-9. [DOI: 10.1109/tbme.2014.2330847] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Ravelli F, Masè M, Cristoforetti A, Marini M, Disertori M. The logical operator map identifies novel candidate markers for critical sites in patients with atrial fibrillation. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2014; 115:186-97. [PMID: 25077410 DOI: 10.1016/j.pbiomolbio.2014.07.006] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2014] [Accepted: 07/17/2014] [Indexed: 11/28/2022]
Abstract
The identification of suitable markers for critical patterns during atrial fibrillation (AF) may be crucial to guide an effective ablation treatment. Single parameter maps, based on dominant frequency and complex fractionated electrograms, have been proposed as a tool for electrogram-guided ablation, however the specificity of these markers is debated. Experimental studies suggest that AF critical patterns may be identified on the basis of specific rate and organization features, where rapid organized and rapid fragmented activities characterize respectively localized sources and critical substrates. In this paper we introduce the logical operator map, a novel mapping tool for a point-by-point identification and localization of AF critical sites. Based on advanced signal and image processing techniques, the approach combines in a single map electrogram-derived rate and organization features with tomographic anatomical detail. The construction of the anatomically-detailed logical operator map is based on the time-domain estimation of atrial rate and organization in terms of cycle length and wave-similarity, the logical combination of these indexes to obtain suitable markers of critical sites, and the multimodal integration of electrophysiological and anatomical information by segmentation and registration techniques. Logical operator maps were constructed in 14 patients with persistent AF, showing the capability of the combined rate and organization markers to identify with high selectivity the subset of electrograms associated with localized sources and critical substrates. The precise anatomical localization of these critical sites revealed the confinement of rapid organized sources in the left atrium with organization and rate gradients towards the surrounding tissue, and the presence of rapid fragmented electrograms in proximity of the sources. By merging in a single map the most relevant electrophysiological and anatomical features of the AF process, the logical operator map may have significant clinical impact as a direct, comprehensive tool to understand arrhythmia mechanisms in the single patient and guide more conservative, step-wise ablation.
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Affiliation(s)
- Flavia Ravelli
- Department of Physics, University of Trento, Povo-Trento, Italy.
| | - Michela Masè
- Department of Physics, University of Trento, Povo-Trento, Italy
| | | | | | - Marcello Disertori
- Division of Cardiology, S. Chiara Hospital, Trento, Italy; Healthcare Research and Innovation Program, PAT-FBK, Trento, Italy
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El Haddad M, Houben R, Stroobandt R, Van Heuverswyn F, Tavernier R, Duytschaever M. Novel Algorithmic Methods in Mapping of Atrial and Ventricular Tachycardia. Circ Arrhythm Electrophysiol 2014; 7:463-72. [DOI: 10.1161/circep.113.000833] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Milad El Haddad
- From the Department of Electrophysiology, Heart Center, Ghent University Hospital, Ghent, Belgium (M.E.H., R.S., F.V.H., M.D.); Cardiology Unit, Applied Biomedical Systems, Maastricht, The Netherlands (R.H.); and Department of Cardiology, Sint-Jan Hospital Bruges, Bruges, Belgium (R.T., M.D.)
| | - Richard Houben
- From the Department of Electrophysiology, Heart Center, Ghent University Hospital, Ghent, Belgium (M.E.H., R.S., F.V.H., M.D.); Cardiology Unit, Applied Biomedical Systems, Maastricht, The Netherlands (R.H.); and Department of Cardiology, Sint-Jan Hospital Bruges, Bruges, Belgium (R.T., M.D.)
| | - Roland Stroobandt
- From the Department of Electrophysiology, Heart Center, Ghent University Hospital, Ghent, Belgium (M.E.H., R.S., F.V.H., M.D.); Cardiology Unit, Applied Biomedical Systems, Maastricht, The Netherlands (R.H.); and Department of Cardiology, Sint-Jan Hospital Bruges, Bruges, Belgium (R.T., M.D.)
| | - Frederic Van Heuverswyn
- From the Department of Electrophysiology, Heart Center, Ghent University Hospital, Ghent, Belgium (M.E.H., R.S., F.V.H., M.D.); Cardiology Unit, Applied Biomedical Systems, Maastricht, The Netherlands (R.H.); and Department of Cardiology, Sint-Jan Hospital Bruges, Bruges, Belgium (R.T., M.D.)
| | - Rene Tavernier
- From the Department of Electrophysiology, Heart Center, Ghent University Hospital, Ghent, Belgium (M.E.H., R.S., F.V.H., M.D.); Cardiology Unit, Applied Biomedical Systems, Maastricht, The Netherlands (R.H.); and Department of Cardiology, Sint-Jan Hospital Bruges, Bruges, Belgium (R.T., M.D.)
| | - Mattias Duytschaever
- From the Department of Electrophysiology, Heart Center, Ghent University Hospital, Ghent, Belgium (M.E.H., R.S., F.V.H., M.D.); Cardiology Unit, Applied Biomedical Systems, Maastricht, The Netherlands (R.H.); and Department of Cardiology, Sint-Jan Hospital Bruges, Bruges, Belgium (R.T., M.D.)
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Hernández A, Alcaraz R, Hornero F, Rieta JJ. Preoperative study of the surface ECG for the prognosis of atrial fibrillation maze surgery outcome at discharge. Physiol Meas 2014; 35:1409-23. [PMID: 24875277 DOI: 10.1088/0967-3334/35/7/1409] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The Cox-maze surgery is an effective procedure for terminating atrial fibrillation (AF) in patients requiring open-heart surgery associated with another heart disease. After the intervention, regardless of the patient's rhythm, all are treated with oral anticoagulants and antiarrhythmic drugs prior to discharge. Furthermore, patients maintaining AF before discharge could also be treated with electrical cardioversion (ECV). In view of this, a preoperative prognosis of the patient's rhythm at discharge would be helpful for optimizing drug therapy planning as well as for advancing ECV therapy. This work analyzes 30 preoperative electrocardiograms (ECGs) from patients suffering from AF in order to predict the Cox-maze surgery outcome at discharge. Two different characteristics of the AF pattern have been studied. On the one hand, the atrial activity (AA) organization, which provides information about the number of propagating wavelets in the atria, was investigated. AA organization has been successfully used in previous studies related to spontaneous reversion of paroxysmal AF and to the outcome of ECV. To assess organization, the dominant atrial frequency (DAF) and sample entropy (SampEn) have been computed. On the other hand, the second characteristic studied was the fibrillatory wave (f-wave) amplitude, which has been demonstrated to be a valuable indicator of the Cox-maze surgery outcome in previous studies. Moreover, this parameter has been obtained through a new methodology, based on computing the f-wave average power (fWP). Finally, all the computed indices were combined in a decision tree in order to improve prediction capability. Results for the DAF yielded a sensitivity (Se), a specificity (Sp) and an accuracy (Acc) of 61.54%, 82.35% and 73.33%, respectively. For SampEn the values were 69.23%, 76.00% and 73.33%, respectively, and for fWP they were 92.31%, 82.35% and 86.67%, respectively. Finally, the decision tree combining the three parameters analyzed improved the preoperative prognosis of the Cox-maze outcome with values of Se, Sp and Acc of 100%, 82.35% and 90%, respectively. As a consequence, the analysis of parameters related to the f-wave pattern, extracted from the preoperative ECG, has provided a considerable ability to predict the outcome of AF Cox-maze surgery at discharge.
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Affiliation(s)
- Antonio Hernández
- Biomedical Synergy, Electronic Engineering Department, Universidad Politécnica de Valencia, Valencia, Spain
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36
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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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37
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Caravaca J, Soria-Olivas E, Bataller M, Serrano AJ, Such-Miquel L, Vila-Francés J, Guerrero JF. Application of machine learning techniques to analyse the effects of physical exercise in ventricular fibrillation. Comput Biol Med 2014; 45:1-7. [DOI: 10.1016/j.compbiomed.2013.11.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2013] [Revised: 11/13/2013] [Accepted: 11/18/2013] [Indexed: 11/25/2022]
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38
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Ng J, Sehgal V, Ng JK, Gordon D, Goldberger JJ. Iterative Method to Detect Atrial Activations and Measure Cycle Length From Electrograms During Atrial Fibrillation. IEEE Trans Biomed Eng 2014; 61:273-8. [DOI: 10.1109/tbme.2013.2290003] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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39
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TUAN TACHUAN, LO MENTZUNG, LIN YENNJIANG, HSIEH WANHSIN, LIN CHEN, HUANG NORDENE, LO LIWEI, CHAO TZEFAN, LIAO JONAN, HSIEH YUCHENG, WU TSUJUEY, CHEN SHIHANN. The Use of Signal Analyses of Ventricular Tachycardia Electrograms to Predict the Response of Antitachycardia Pacing in Patients with Implantable Cardioverter-Defibrillators. J Cardiovasc Electrophysiol 2014; 25:411-417. [DOI: 10.1111/jce.12340] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2013] [Revised: 11/11/2013] [Accepted: 11/26/2013] [Indexed: 11/29/2022]
Affiliation(s)
- TA-CHUAN TUAN
- Division of Cardiology; Department of Medicine; Taipei Veterans General Hospital; Taipei Taiwan
- Faculty of Medicine and Institute of Clinical Medicine; National Yang-Ming University; School of Medicine; Taipei Taiwan
- Division of Cardiology, Taipei Municipal Gan-Dau Hospital; Taipei Taiwan
| | - MEN-TZUNG LO
- Research Center for Adaptive Data Analysis; Analysis and Center for Dynamical Biomarkers and Translational Medicine; National Central University; Jhongli Taiwan R.O.C
| | - YENN-JIANG LIN
- Division of Cardiology; Department of Medicine; Taipei Veterans General Hospital; Taipei Taiwan
- Faculty of Medicine and Institute of Clinical Medicine; National Yang-Ming University; School of Medicine; Taipei Taiwan
| | - WAN-HSIN HSIEH
- Research Center for Adaptive Data Analysis; Analysis and Center for Dynamical Biomarkers and Translational Medicine; National Central University; Jhongli Taiwan R.O.C
- Medical Biodynamics Program; Division of Sleep Medicine; Brigham and Women's Hospital; Harvard Medical School; Boston Massachusetts USA
| | - CHEN LIN
- Research Center for Adaptive Data Analysis; Analysis and Center for Dynamical Biomarkers and Translational Medicine; National Central University; Jhongli Taiwan R.O.C
- Department of Psychiatry and Behavioral Sciences; Stanford University School of Medicine; Palo Alto California USA
| | - NORDEN E. HUANG
- Research Center for Adaptive Data Analysis; Analysis and Center for Dynamical Biomarkers and Translational Medicine; National Central University; Jhongli Taiwan R.O.C
| | - LI-WEI LO
- Division of Cardiology; Department of Medicine; Taipei Veterans General Hospital; Taipei Taiwan
- Faculty of Medicine and Institute of Clinical Medicine; National Yang-Ming University; School of Medicine; Taipei Taiwan
| | - TZE-FAN CHAO
- Division of Cardiology; Department of Medicine; Taipei Veterans General Hospital; Taipei Taiwan
- Faculty of Medicine and Institute of Clinical Medicine; National Yang-Ming University; School of Medicine; Taipei Taiwan
| | - JO-NAN LIAO
- Division of Cardiology; Department of Medicine; Taipei Veterans General Hospital; Taipei Taiwan
- Faculty of Medicine and Institute of Clinical Medicine; National Yang-Ming University; School of Medicine; Taipei Taiwan
| | - YU-CHENG HSIEH
- Division of Cardiology; Department of Medicine; Taipei Veterans General Hospital; Taipei Taiwan
- Cardiovascular Center; Taichung Veterans General Hospital; Taichung Taiwan
| | - TSU-JUEY WU
- Division of Cardiology; Department of Medicine; Taipei Veterans General Hospital; Taipei Taiwan
- Cardiovascular Center; Taichung Veterans General Hospital; Taichung Taiwan
| | - SHIH-ANN CHEN
- Division of Cardiology; Department of Medicine; Taipei Veterans General Hospital; Taipei Taiwan
- Faculty of Medicine and Institute of Clinical Medicine; National Yang-Ming University; School of Medicine; Taipei Taiwan
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40
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El Haddad M, Houben R, Stroobandt R, Van Heuverswyn F, Tavernier R, Duytschaever M. Algorithmic detection of the beginning and end of bipolar electrograms: Implications for novel methods to assess local activation time during atrial tachycardia. Biomed Signal Process Control 2013. [DOI: 10.1016/j.bspc.2012.11.005] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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41
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Masè M, Glass L, Disertori M, Ravelli F. The AV synchrogram: A novel approach to quantify atrioventricular coupling during atrial arrhythmias. Biomed Signal Process Control 2013. [DOI: 10.1016/j.bspc.2013.01.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Corino VDA, Rivolta MW, Sassi R, Lombardi F, Mainardi LT. Ventricular activity cancellation in electrograms during atrial fibrillation with constraints on residuals' power. Med Eng Phys 2013; 35:1770-7. [PMID: 23962727 DOI: 10.1016/j.medengphy.2013.07.010] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2012] [Revised: 06/27/2013] [Accepted: 07/27/2013] [Indexed: 11/25/2022]
Abstract
During atrial fibrillation (AF), cancellation of ventricular activity from atrial electrograms (AEG) is commonly performed by template matching and subtraction (TMS): a running template, built in correspondence of QRSs, is subtracted from the AEG to uncover atrial activity (AA). However, TMS can produce poor cancellation, leaving high-power residues. In this study, we propose to modulate the templates before subtraction, in order to make the residuals as similar as possible to the nearby atrial activity, avoiding high-power ones. The coefficients used to modulate the template are estimated by maximizing, via Multi-swarm Particle Swarm Optimization, a fitness function. The modulated TMS method (mTMS) was tested on synthetic and real AEGs. Cancellation performances were assessed using: normalized mean squared error (NMSE, computed on simulated data only), reduction of ventricular activity (VDR), and percentage of segments (PP) whose power was outside the standard range of the atrial power. All testings suggested that mTMS is an improvement over TMS alone, being, on simulated data, NMSE and PP significantly decreased while VDR significantly increased. Similar results were obtained on real electrograms (median values of CS1 recordings PP: 2.44 vs. 0.38 p < 0.001; VDR: 6.71 vs. 8.15 p < 0.001).
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Affiliation(s)
- Valentina D A Corino
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy.
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Ravelli F, Masè M, Cristoforetti A, Del Greco M, Centonze M, Marini M, Disertori M. Anatomic localization of rapid repetitive sources in persistent atrial fibrillation: fusion of biatrial CT images with wave similarity/cycle length maps. JACC Cardiovasc Imaging 2013; 5:1211-20. [PMID: 23236970 DOI: 10.1016/j.jcmg.2012.07.016] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2012] [Revised: 07/12/2012] [Accepted: 08/01/2012] [Indexed: 11/15/2022]
Abstract
OBJECTIVES The aim of this study was to investigate the anatomic distribution of critical sources in patients with atrial fibrillation (AF) by fusion of biatrial computed tomography (CT) images with cycle length (CL) and wave similarity (WS) maps. BACKGROUND Experimental and clinical studies show that atrial fibrillation (AF) may originate from rapid and repetitive (RR) sources of activation. Localization of RR sources may be crucial for an effective ablation treatment. Atrial electrograms showing rapid and repetitive activations can be identified by combining WS and CL analysis. METHODS Patients with persistent AF underwent biatrial electroanatomic mapping and pre-procedural CT cardiac imaging. WS and CL maps were constructed in 17 patients by calculating the degree of repetitiveness of activation waveforms (similarity index [S]) and the cycle length at each atrial site. WS/CL maps were then integrated with biatrial 3-dimensional CT reconstructions by a stochastic approach. RESULTS Repetitive sources of activation (S ≥ 0.5) were present in most patients with persistent AF (94%) and were mainly located at the pulmonary veins (82% of patients), at the superior caval vein (41%), on the anterior wall of the right atrium (23%), and at the left atrial appendage (23%). Potential driver sources showing both rapid and repetitive activations (CL = 140.7 ± 25.1 ms, S = 0.65 ± 0.15) were present only in a subset of patients (65%) and were confined to the pulmonary vein region (47% of patients) and left atrial appendage (12%). Differently, the repetitive activity of the superior caval vein was characterized by a slow activation rate (CL = 184.7 ± 14.6 ms). CONCLUSIONS The identification and localization of RR sources is feasible by fusion of biatrial anatomic images with WS/CL maps. Potential driver sources are present only in a subset of patients with persistent AF and are mainly located in the pulmonary vein region.
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Affiliation(s)
- Flavia Ravelli
- Department of Physics, University of Trento, Trento, Italy.
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44
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Alcaraz R, Hornero F, Rieta JJ. Dynamic time warping applied to estimate atrial fibrillation temporal organization from the surface electrocardiogram. Med Eng Phys 2013; 35:1341-8. [PMID: 23566715 DOI: 10.1016/j.medengphy.2013.03.004] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2011] [Revised: 03/01/2013] [Accepted: 03/09/2013] [Indexed: 11/30/2022]
Abstract
Atrial fibrillation (AF) is the most commonly diagnosed arrhythmia in clinical practice. However, the mechanisms responsible for its induction and maintenance still are not fully understood. To this respect, analysis of the electrical activity organization within the atria could play an important role in their proper interpretation. Although many algorithms to quantify AF organization from invasive electrograms can be found in the literature, a reduced number of indirect estimators from the standard ECG have been proposed to date. Furthermore, these surface methods can only yield a global AF organization assessment, blurring the possible information that each individual fibrillatory (f) wave may provide. To this respect, the present manuscript proposes a novel method for direct and short-time AF organization estimation from single-lead surface ECG recordings. Through the computation of morphological variations among f waves, the temporal arrhythmia organization is estimated. The f waves are individually extracted and delineated from the atrial activity signal, making use of a dynamic time warping approach. The proposed algorithm was tested on real AF surface recordings in order to discriminate atrial signals with different organization degrees, obtaining a diagnostic accuracy higher than 88%. In addition, its performance was validated by comparison with two temporal organization measures from invasive unipolar electrograms of both atria, providing statistically significant linear correlations between invasive and non-invasive estimates. As a consequence, new standpoints are opened through this work in the non-invasive analysis of AF, where the individualized study of each f wave could assess short-time AF organization, would improve the understanding of AF mechanisms and become useful for its clinical treatment.
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Affiliation(s)
- Raúl Alcaraz
- Innovation in Bioengineering Research Group, University of Castilla-La Mancha, Spain.
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45
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Such-Miquel L, Chorro FJ, Guerrero J, Trapero I, Brines L, Zarzoso M, Parra G, Soler C, del Canto I, Alberola A, Such L. Evaluación de la complejidad de la activación miocárdica durante la fibrilación ventricular. Estudio experimental. Rev Esp Cardiol 2013. [DOI: 10.1016/j.recesp.2012.08.014] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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46
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Treo EF, Cervantes DO, Ciaccio EJ. Automated detection and mapping of electrical activation when electrogram morphology is complex. Biomed Signal Process Control 2013. [DOI: 10.1016/j.bspc.2012.04.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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47
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Evaluation of the complexity of myocardial activation during ventricular fibrillation. An experimental study. ACTA ACUST UNITED AC 2012; 66:177-84. [PMID: 24775451 DOI: 10.1016/j.rec.2012.08.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2012] [Accepted: 08/31/2012] [Indexed: 11/23/2022]
Abstract
INTRODUCTION AND OBJECTIVES An experimental model is used to analyze the characteristics of ventricular fibrillation in situations of variable complexity, establishing relationships among the data produced by different methods for analyzing the arrhythmia. METHODS In 27 isolated rabbit heart preparations studied under the action of drugs (propranolol and KB-R7943) or physical procedures (stretching) that produce different degrees of change in the complexity of myocardial activation during ventricular fibrillation, use was made of spectral, morphological, and mapping techniques to process the recordings obtained with epicardial multielectrodes. RESULTS The complexity of ventricular fibrillation assessed by mapping techniques was related to the dominant frequency, normalized spectral energy, signal regularity index, and their corresponding coefficients of variation, as well as the area of the regions of interest identified on the basis of these parameters. In the multivariate analysis, we used as independent variables the area of the regions of interest related to the spectral energy and the coefficient of variation of the energy (complexity index=-0.005×area of the spectral energy regions -2.234×coefficient of variation of the energy+1.578; P=.0001; r=0.68). CONCLUSIONS The spectral and morphological indicators and, independently, those derived from the analysis of normalized energy regions of interest provide a reliable approach to the evaluation of the complexity of ventricular fibrillation as an alternative to complex mapping techniques.
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LIN YENNJIANG, LO MENTZUNG, LIN CHEN, CHANG SHIHLIN, LO LIWEI, HU YUFENG, CHAO TZEFAN, LI CHENGHUNG, CHANG YICHUNG, HSIEH WANHSIN, CHUNG FAPO, TSAO HSUANMING, CHANG HUNGYU, HUANG NORDENE, CHEN SHIHANN. Nonlinear Analysis of Fibrillatory Electrogram Similarity to Optimize the Detection of Complex Fractionated Electrograms During Persistent Atrial Fibrillation. J Cardiovasc Electrophysiol 2012; 24:280-9. [DOI: 10.1111/jce.12019] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Alcaraz R, Hornero F, Martínez A, Rieta JJ. Short-time regularity assessment of fibrillatory waves from the surface ECG in atrial fibrillation. Physiol Meas 2012; 33:969-84. [DOI: 10.1088/0967-3334/33/6/969] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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