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Ragot D, Nayyar S, Massin SZ, Ha ACT, Singh SM, Labos C, Suszko A, Dalvi R, Chauhan VS. Unipolar electrogram-based voltage mapping with far-field cancellation to improve detection of abnormal atrial substrate during atrial fibrillation. J Cardiovasc Electrophysiol 2021; 32:1572-1583. [PMID: 33694221 DOI: 10.1111/jce.14999] [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: 11/02/2020] [Revised: 02/18/2021] [Accepted: 03/03/2021] [Indexed: 11/27/2022]
Abstract
INTRODUCTION An important substrate for atrial fibrillation (AF) is fibrotic atrial myopathy. Identifying low voltage, myopathic regions during AF using traditional bipolar voltage mapping is limited by the directional dependency of wave propagation. Our objective was to evaluate directionally independent unipolar voltage mapping, but with far-field cancellation, to identify low-voltage regions during AF. METHODS In 12 patients undergoing pulmonary vein isolation for AF, high-resolution voltage mapping was performed in the left atrium during sinus rhythm and AF using a roving 20-pole circular catheter. Bipolar electrograms (EGMs) (Bi) < 0.5 mV in sinus rhythm identified low-voltage regions. During AF, bipolar voltage and unipolar voltage maps were created, the latter with (uni-res) and without (uni-orig) far-field cancellation using a novel, validated least-squares algorithm. RESULTS Uni-res voltage was ~25% lower than uni-orig for both low voltage and normal atrial regions. Far-field EGM had a dominant frequency (DF) of 4.5-6.0 Hz, and its removal resulted in a lower DF for uni-orig compared with uni-res (5.1 ± 1.5 vs. 4.8 ± 1.5 Hz; p < .001). Compared with Bi, uni-res had a significantly greater area under the receiver operator curve (0.80 vs. 0.77; p < .05), specificity (86% vs. 76%; p < .001), and positive predictive value (43% vs. 30%; p < .001) for detecting low-voltage during AF. Similar improvements in specificity and positive predictive value were evident for uni-res versus uni-orig. CONCLUSION Far-field EGM can be reliably removed from uni-orig using our novel, least-squares algorithm. Compared with Bi and uni-orig, uni-res is more accurate in detecting low-voltage regions during AF. This approach may improve substrate mapping and ablation during AF, and merits further study.
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Affiliation(s)
- Don Ragot
- Peter Munk Cardiac Center, Division of Cardiology, Toronto General Hospital, University Health Network, Toronto, Canada
| | - Sachin Nayyar
- Peter Munk Cardiac Center, Division of Cardiology, Toronto General Hospital, University Health Network, Toronto, Canada
| | - Sophia Z Massin
- Peter Munk Cardiac Center, Division of Cardiology, Toronto General Hospital, University Health Network, Toronto, Canada
| | - Andrew C T Ha
- Peter Munk Cardiac Center, Division of Cardiology, Toronto General Hospital, University Health Network, Toronto, Canada
| | - Sheldon M Singh
- Sunnybrook Health Sciences Center, Division of Cardiology, University Health Network, Toronto, Canada
| | - Christopher Labos
- Queen Elizabeth Health Complex, Division of Cardiology, University Health Network, Montreal, Canada
| | - Adrian Suszko
- Peter Munk Cardiac Center, Division of Cardiology, Toronto General Hospital, University Health Network, Toronto, Canada
| | - Rupin Dalvi
- Peter Munk Cardiac Center, Division of Cardiology, Toronto General Hospital, University Health Network, Toronto, Canada
| | - Vijay S Chauhan
- Peter Munk Cardiac Center, Division of Cardiology, Toronto General Hospital, University Health Network, Toronto, Canada
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Frisch D, Oesterlein TG, Unger LA, Lenis G, Wakili R, Schmitt C, Luik A, Dossel O, Loewe A. Mapping and Removing the Ventricular Far Field Component in Unipolar Atrial Electrograms. IEEE Trans Biomed Eng 2020; 67:2905-2915. [DOI: 10.1109/tbme.2020.2973471] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Pollnow S, Schwaderlapp G, Loewe A, Dössel O. Monitoring the dynamics of acute radiofrequency ablation lesion formation in thin-walled atria - a simultaneous optical and electrical mapping study. BIOMED ENG-BIOMED TE 2020; 65:327-341. [PMID: 31756159 DOI: 10.1515/bmt-2019-0013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Accepted: 09/27/2019] [Indexed: 11/15/2022]
Abstract
Background Radiofrequency ablation (RFA) is a common approach to treat cardiac arrhythmias. During this intervention, numerous strategies are applied to indirectly estimate lesion formation. However, the assessment of the spatial extent of these acute injuries needs to be improved in order to create well-defined and durable ablation lesions. Methods We investigated the electrophysiological characteristics of rat atrial myocardium during an ex vivo RFA procedure with fluorescence-optical and electrical mapping. By analyzing optical data, the temporal growth of punctiform ablation lesions was reconstructed after stepwise RFA sequences. Unipolar electrograms (EGMs) were simultaneously recorded by a multielectrode array (MEA) before and after each RFA sequence. Based on the optical results, we searched for electrical features to delineate these lesions from healthy myocardium. Results Several unipolar EGM parameters were monotonically decreasing when distances between the electrode and lesion boundary were smaller than 2 mm. The negative component of the unipolar EGM [negative peak amplitude (Aneg)] vanished for distances lesser than 0.4 mm to the lesion boundary. Median peak-to-peak amplitude (Vpp) was decreased by 75% compared to baseline. Conclusion Aneg and Vpp are excellent parameters to discriminate the growing lesion area from healthy myocardium. The experimental setup opens new opportunities to investigate EGM characteristics of more complex ablation lesions.
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Affiliation(s)
- Stefan Pollnow
- Karlsruhe Institute of Technology, Institute of Biomedical Engineering, Fritz-Haber-Weg 1, Karlsruhe 76131, Germany, Tel.: +49-721-608-42650, Fax: +49-721-608-42789
| | - Gerald Schwaderlapp
- Karlsruhe Institute of Technology, Institute of Biomedical Engineering, Fritz-Haber-Weg 1, Karlsruhe 76131, Germany
| | - Axel Loewe
- Karlsruhe Institute of Technology, Institute of Biomedical Engineering, Fritz-Haber-Weg 1, Karlsruhe 76131, Germany
| | - Olaf Dössel
- Karlsruhe Institute of Technology, Institute of Biomedical Engineering, Fritz-Haber-Weg 1, Karlsruhe 76131, Germany
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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: 1.0] [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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Oesterlein TG, Loewe A, Lenis G, Luik A, Schmitt C, Dossel O. Automatic Identification of Reentry Mechanisms and Critical Sites During Atrial Tachycardia by Analyzing Areas of Activity. IEEE Trans Biomed Eng 2018; 65:2334-2344. [DOI: 10.1109/tbme.2018.2794321] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Valinoti M, Masci A, Berto F, Severi S, Corsi C. Towards a repository of synthetic electrograms for atrial activation detection in atrial fibrillation. Comput Biol Med 2018; 101:229-235. [PMID: 30212744 DOI: 10.1016/j.compbiomed.2018.09.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2018] [Revised: 08/31/2018] [Accepted: 09/01/2018] [Indexed: 10/28/2022]
Abstract
BACKGROUND Recently, the analysis of the spatio-temporal behavior of atrial fibrillation activation patterns has been widely investigated with the aim to better understand the arrhythmia implications on the heart electrical activity. Most of the proposed techniques are based on atrial activation timing detections. Unfortunately atrial activation timings are not easily recognizable on the electrograms (EGMs) and an approach to support the validation of such techniques is highly desirable. The aim of this study is to provide an effective workflow for the generation of synthetic unipolar atrial electrograms (SEGMs) in atrial fibrillation (AF) condition and with different levels of noise. METHOD Real EGMs signals were obtained from a dataset of 6 subjects that underwent ablation. Each SEGM was obtained by modeling the three principal components of an EGM starting from real signals: atrial far-field (Afar), atrial near-field (Anear) and the ventricular far-field (Vfar). Afar was generated using an autoregressive model applied on segments from real EGMs not characterized by ventricular or atrial activations; Anear and Vfar were extracted directly from the real signals. A Gamma distribution and an atrio-ventricular node model were used to locate both Anear and Vfar on Afar, respectively. Three electrophysiologists with different levels of expertise evaluated the realism of the SEGMs on a set of 100 randomly selected signals including 50 EGMs and 50 SEGMs. Analysis was repeated by the three experts on a subset of 21 signals. RESULTS The time required to generate the synthetic EGMs was less than 1 min once annotated EGMs are available. The cardiologists succeeded in distinguishing real from synthetic EGMs in 45%, 43% and 35% of the signals, respectively. By repeating the evaluation, 28%, 0% and 48% of signals were classified differently, including 67%, 52% and 36% of correct classifications. CONCLUSION The proposed approach proved to be effective in producing SEGMs which are difficult to distinguish from real EGMs. This study provides a tool for realistic SEGM generation from real EGMs in AF condition with different levels of noise and at different AF rates. The tool may be easily adopted to obtain SEGMs in different arrhythmic conditions. SEGMs generated in this study are shared with the scientific community as a first step towards a repository of synthetic and real atrial signals supporting the benchmarking of new approaches to investigate AF.
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Affiliation(s)
- Maddalena Valinoti
- Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi", University of Bologna, Via Venezia 52, 47521, Bologna, Cesena, Italy
| | - Alessandro Masci
- Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi", University of Bologna, Via Venezia 52, 47521, Bologna, Cesena, Italy.
| | - Francesca Berto
- Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi", University of Bologna, Via Venezia 52, 47521, Bologna, Cesena, Italy
| | - Stefano Severi
- Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi", University of Bologna, Via Venezia 52, 47521, Bologna, Cesena, Italy
| | - Cristiana Corsi
- Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi", University of Bologna, Via Venezia 52, 47521, Bologna, Cesena, Italy.
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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: 0.6] [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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Oesterlein TG, Schmid J, Bauer S, Jadidi A, Schmitt C, Dössel O, Luik A. Analysis and visualization of intracardiac electrograms in diagnosis and research: Concept and application of KaPAVIE. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2016; 127:165-173. [PMID: 26774236 DOI: 10.1016/j.cmpb.2015.12.007] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2015] [Revised: 12/11/2015] [Accepted: 12/17/2015] [Indexed: 06/05/2023]
Abstract
BACKGROUND AND OBJECTIVE Progress in biomedical engineering has improved the hardware available for diagnosis and treatment of cardiac arrhythmias. But although huge amounts of intracardiac electrograms (EGMs) can be acquired during electrophysiological examinations, there is still a lack of software aiding diagnosis. The development of novel algorithms for the automated analysis of EGMs has proven difficult, due to the highly interdisciplinary nature of this task and hampered data access in clinical systems. Thus we developed a software platform, which allows rapid implementation of new algorithms, verification of their functionality and suitable visualization for discussion in the clinical environment. METHODS A software for visualization was developed in Qt5 and C++ utilizing the class library of VTK. The algorithms for signal analysis were implemented in MATLAB. Clinical data for analysis was exported from electroanatomical mapping systems. RESULTS The visualization software KaPAVIE (Karlsruhe Platform for Analysis and Visualization of Intracardiac Electrograms) was implemented and tested on several clinical datasets. Both common and novel algorithms were implemented which address important clinical questions in diagnosis of different arrhythmias. It proved useful in discussions with clinicians due to its interactive and user-friendly design. Time after export from the clinical mapping system to visualization is below 5min. CONCLUSION KaPAVIE(2) is a powerful platform for the development of novel algorithms in the clinical environment. Simultaneous and interactive visualization of measured EGM data and the results of analysis will aid diagnosis and help understanding the underlying mechanisms of complex arrhythmias like atrial fibrillation.
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Affiliation(s)
- Tobias Georg Oesterlein
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
| | - Jochen Schmid
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
| | - Silvio Bauer
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
| | - Amir Jadidi
- Universitäts-Herzzentrum Freiburg-Bad Krozingen, Germany.
| | | | - Olaf Dössel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
| | - Armin Luik
- Städtisches Klinikum Karlsruhe, Karlsruhe, Germany.
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