Frontiers in Non-invasive Cardiac Mapping: Rotors in Atrial Fibrillation-Body Surface Frequency-Phase Mapping

[EN] Experimental and clinical data demonstrate that atrial fibrillation (AF) maintenance in animals and groups of patients depends on localized reentrant sources localized primarily to the pulmonary veins (PVs) and the left atrium(LA) posterior wall in paroxysmal AF but elsewhere, including the right atrium (RA), in persistent AF. Moreover, AF can be eliminated by directly ablating AFdriving sources or “rotors,” that exhibit high-frequency, periodic activity. The RADAR-AF randomized trial demonstrated that an ablation procedure based on a more target-specific strategy aimed at eliminating high frequency sites responsible for AF maintenance is as efficacious as and safer than empirically isolating all the PVs. In contrast to the standard ECG, global atrial noninvasive frequency analysis allows non-invasive identification of high-frequency sources before the arrival at the electrophysiology laboratory for ablation. Body surface potential map (BSPM) replicates the endocardial distribution of DFs with localization of the highest DF (HDF) and can identify small areas containing the high-frequency sources. Overall, BSPM had a sensitivity of 75% and specificity of 100% for capturing intracardiac EGMs as having LARA DF gradient. However, raw BSPM data analysis of AF patterns of activity showed incomplete and instable reentrant patterns of activation. Thus, we developed an analysis approach whereby a narrow band-pass filtering allowed selecting the electrical activity projected on the torso at the HDF, which stabilized the projection of rotors that potentially drive AF on the surface. Consequently, driving reentrant patterns (“rotors”) with spatiotemporal stability during >70% of the AF time could be observed noninvasibly after HDFfiltering. Moreover, computer simulations found that the combination of BSPM phase mapping with DF analysis enabled the discrimination of true rotational patterns even during the most complex AF. Altogether, these studies show that the combination of DF analysis with phase maps of HDF-filtered surface ECG recordings allows noninvasive localization of atrial reentries during AF and further a physiologically-based rationale for personalized diagnosis and treatment of patients with AF.Study supported in part by the Spanish Society of Cardiology (Becas Investigacio´ n Clı´nica 2009); the Universitat Polite` cnica de Vale`ncia through its research initiative program; the Generalitat Valenciana Grants (ACIF/2013/021); the Ministerio de Economia y Competividad, Red RIC; the Centro Nacional de Investigaciones Cardiovasculares (proyecto CNIC-13); the Coulter Foundation from the Biomedical Engineering Department (University of Michigan); the Gelman Award from the Cardiovascular Division (University of Michigan); the National Heart, Lung, and Blood Institute grants (P01-HL039707, P01-HL087226 and R01-HL118304), and the Leducq FoundationAtienza, F.; Climent, A.; Guillem Sánchez, MS.; Berenfeld, O. (2015). Frontiers in Non-invasive Cardiac Mapping: Rotors in Atrial Fibrillation-Body Surface Frequency-Phase Mapping. Cardiac Electrophysiology Clinics. 7(1):59-69. https://doi.org/10.1016/j.ccep.2014.11.002S59697

Editorial: Atrial Fibrillation: Technologies for Investigation, Monitoring and Treatment, Volume II

[No abstract

Spatial gradients in action potential duration created by regional magnetofection of hERG are a substrate for wavebreak and turbulent propagation in cardiomyocyte monolayers

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95178/1/jphysiol.2012.238758.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/95178/2/TJP_5439_sm_SuppMat.pd

Far-field contributions in multi-electrodes atrial recordings blur distinction between anatomical and functional reentries and may cause imaginary phase singularities A computational study

[EN] Background Atrial fibrillation (AF) is the most common cardiac arrhythmia and the most important cause of embolic stroke, requiring new technologies for its better understanding and therapies. Recent approaches to map the electrical activity during AF with multi-electrode systems aim at localizing patient-specific ablation targets of reentrant patterns. However, there is a critical need to determine the accuracy of those mapping systems. We performed computer simulations as a numerical approach of systematically evaluating the influence of far-field sources on the electrical recordings and detection of rotors. Methods We constructed 2 computer models of atrial tissue: (i) a 2D sheet model with varying non-active cells area in its center, and (ii) a whole realistic 3D atrial model. Phase maps were built based on the Hilbert transform of the unipolar electrograms recorded by virtual 2D and 3D multi-electrode systems and rotors were tracked through phase singularities detections. Results Analysis of electrograms recorded away from the 2D atrial model shows that the larger the distance between an electrode and the tissue model, the stronger the far-field sources contribution to the electrogram is. Importantly, even if an electrode is positioned in contact with the tissue, the electrogram contains significant contributions from distal sources that blur the distinction between anatomical and functional reentries. Moreover, when mapping the 3D atrial model, remote activity generated false phase singularities at locations without local reentrant excitation patterns. Conclusions Far-field contributions to electrograms during AF reduce the accuracy of detecting and interpreting reentrant activity.This work was supported in part by Programa Prometeu de la Conselleria d'Educacio, Formacio I Ocupacio de la Generalitat Valenciana, award number PROMETEU/2016/088; Plan Estatal de Investigacion Cientifica y Tecnica y de Innovacion 2013-2016 del Ministerio de Economia, Industria y Competitividad of Spain, Agencia Estatal de Investigacion and the European Commission (European Regional Development Funds - ERDF -FEDER), award number DPI2016-75799-R; The National Heart, Lung, and Blood Institute grant ROl-HL118304; the Gelman Award from the Cardiovascular Division at the University of Michigan; and the Coulter Program Award from the Dept. of Biomed Eng. at the University of Michigan.Martínez-Mateu, L.; Romero Pérez, L.; Saiz Rodríguez, FJ.; Berenfeld, O. (2019). Far-field contributions in multi-electrodes atrial recordings blur distinction between anatomical and functional reentries and may cause imaginary phase singularities A computational study. Computers in Biology and Medicine. 108:276-287. https://doi.org/10.1016/j.compbiomed.2019.02.022S27628710

Spatial gradients in action potential duration created by regional magnetofection of hERG are a substrate for wavebreak and turbulent propagation in cardiomyocyte monolayers

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95178/1/jphysiol.2012.238758.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/95178/2/TJP_5439_sm_SuppMat.pd

Presence and stability of rotors in atrial fibrillation: evidence and therapeutic implications

[EN] Rotor-guided ablation has opened new perspectives into the therapy of atrial fibrillation (AF). Analysis of the spatio-temporal cardiac excitation patterns in the frequency and phase domains has demonstrated the importance of rotors in research models of AF, however, the dynamics and role of rotors in human AF are still controversial. In this review, the current knowledge gained through research models and patient data that support the notion that rotors are key players in AF maintenance is summarized. We report and discuss discrepancies regarding rotor prevalence and stability in various studies, which can be attributed in part to methodological differences among mapping systems. Future research for validation and improvement of current clinical electrophysiology mapping technologies will be crucial for developing mechanistic-based selection and application of the best therapeutic strategy for individual AF patient, being it, pharmaceutical, ablative, or other approach.This work was supported in part by grants from the Instituto de Salud Carlos III (Ministry of Economy and Competitiveness, Spain: PI13-01882, PI13-00903, and PI14/00857), Spanish Society of Cardiology (Clinical Research Grant 2015), Generalitat Valenciana (ACIF/2013/021), Innovation (Red RIC, PLE2009-0152), and NHLBI (P01-HL039707, P01-HL087226, and R01-HL118304).Guillem Sánchez, MS.; Climent, AM.; Rodrigo Bort, M.; Fernandez-Aviles, F.; Atienza, F.; Berenfeld, O. (2016). Presence and stability of rotors in atrial fibrillation: evidence and therapeutic implications. Cardiovascular Research. 109(4):480-492. https://doi.org/10.1093/cvr/cvw011S480492109

Technical Considerations on Phase Mapping for Identification of Atrial Reentrant Activity in Direct- and Inverse-Computed Electrograms

[EN] [Background] Phase mapping has become a broadly used technique to identify atrial reentrant circuits for ablative therapy guidance. This work studies the phase mapping process and how the signal nature and its filtering affect the reentrant pattern characterization in electrogram (EGM), body surface potential mapping, and electrocardiographic imaging signals. [Methods and Results] EGM, body surface potential mapping, and electrocardiographic imaging phase maps were obtained from 17 simulations of atrial fibrillation, atrial flutter, and focal atrial tachycardia. Reentrant activity was identified by singularity point recognition in raw signals and in signals after narrow band-pass filtering at the highest dominant frequency (HDF). Reentrant activity was dominantly present in the EGM recordings only for atrial fibrillation and some atrial flutter propagations patterns, and HDF filtering allowed increasing the reentrant activity detection from 60% to 70% of time in atrial fibrillation in unipolar recordings and from 0% to 62% in bipolar. In body surface potential mapping maps, HDF filtering increased from 10% to 90% the sensitivity, although provoked a residual false reentrant activity ¿30% of time. In electrocardiographic imaging, HDF filtering allowed to increase ¿100% the time with detected rotors, although provoked the apparition of false rotors during 100% of time. Nevertheless, raw electrocardiographic imaging phase maps presented reentrant activity just in atrial fibrillation recordings accounting for ¿80% of time. [Conclusions] Rotor identification is accurate and sensitive and does not require additional signal processing in measured or noninvasively computed unipolar EGMs. Bipolar EGMs and body surface potential mapping do require HDF filtering to detect rotors at the expense of a decreased specificity.This study was supported, in part, by Universitat Politecnica de Valencia through its research initiative program; Generalitat Valenciana Grants (ACIF/2013/021); the Instituto de Salud Carlos III (Ministry of Economy and Competitiveness, Spain: PI13-01882, PI13-00903, PI14/00857, PI16/01123, TEC2013-46067-R, DTS16/0160, and IJCI-2014-22178); Spanish Society of Cardiology (Grant for Clinical Research in Cardiology 2015); Spanish Ministry of Science and Innovation (Red RIC RD12.0042.0001); and the National Heart, Lung, and Blood Institute (P01-HL039707, P01-HL087226, and Q1 R01-HL118304) and cofounded by FEDER.Rodrigo Bort, M.; Martínez Climent, A.; Liberos Mascarell, A.; Fernández-Avilés, F.; Berenfeld, O.; Atienza, F.; Guillem Sánchez, MS. (2017). Technical Considerations on Phase Mapping for Identification of Atrial Reentrant Activity in Direct- and Inverse-Computed Electrograms. Circulation Arrhythmia and Electrophysiology. 10(9):1-13. https://doi.org/10.1161/CIRCEP.117.005008S113109Allessie, M., & de Groot, N. (2014). CrossTalk opposing view: Rotors have not been demonstrated to be the drivers of atrial fibrillation. The Journal of Physiology, 592(15), 3167-3170. doi:10.1113/jphysiol.2014.271809Narayan, S. M., & Zaman, J. A. B. (2016). Mechanistically based mapping of human cardiac fibrillation. The Journal of Physiology, 594(9), 2399-2415. doi:10.1113/jp270513Guillem, M. S., Climent, A. M., Rodrigo, M., Fernández-Avilés, F., Atienza, F., & Berenfeld, O. (2016). Presence and stability of rotors in atrial fibrillation: evidence and therapeutic implications. Cardiovascular Research, 109(4), 480-492. doi:10.1093/cvr/cvw011Narayan, S. M., Krummen, D. E., Clopton, P., Shivkumar, K., & Miller, J. M. (2013). Direct or Coincidental Elimination of Stable Rotors or Focal Sources May Explain Successful Atrial Fibrillation Ablation. Journal of the American College of Cardiology, 62(2), 138-147. doi:10.1016/j.jacc.2013.03.021Berenfeld, O., Ennis, S., Hwang, E., Hooven, B., Grzeda, K., Mironov, S., … Jalife, J. (2011). Time- and frequency-domain analyses of atrial fibrillation activation rate: The optical mapping reference. Heart Rhythm, 8(11), 1758-1765. doi:10.1016/j.hrthm.2011.05.007Gray, R. A., Pertsov, A. M., & Jalife, J. (1998). Spatial and temporal organization during cardiac fibrillation. Nature, 392(6671), 75-78. doi:10.1038/32164Rodrigo, M., Guillem, M. S., Climent, A. M., Pedrón-Torrecilla, J., Liberos, A., Millet, J., … Berenfeld, O. (2014). Body surface localization of left and right atrial high-frequency rotors in atrial fibrillation patients: A clinical-computational study. Heart Rhythm, 11(9), 1584-1591. doi:10.1016/j.hrthm.2014.05.013Vijayakumar, R., Vasireddi, S. K., Cuculich, P. S., Faddis, M. N., & Rudy, Y. (2016). Methodology Considerations in Phase Mapping of Human Cardiac Arrhythmias. Circulation: Arrhythmia and Electrophysiology, 9(11). doi:10.1161/circep.116.004409Guillem, M. S., Climent, A. M., Millet, J., Arenal, Á., Fernández-Avilés, F., Jalife, J., … Berenfeld, O. (2013). Noninvasive Localization of Maximal Frequency Sites of Atrial Fibrillation by Body Surface Potential Mapping. Circulation: Arrhythmia and Electrophysiology, 6(2), 294-301. doi:10.1161/circep.112.000167Haissaguerre, M., Hocini, M., Denis, A., Shah, A. J., Komatsu, Y., Yamashita, S., … Dubois, R. (2014). Driver Domains in Persistent Atrial Fibrillation. Circulation, 130(7), 530-538. doi:10.1161/circulationaha.113.005421Dössel, O., Krueger, M. W., Weber, F. M., Wilhelms, M., & Seemann, G. (2012). Computational modeling of the human atrial anatomy and electrophysiology. Medical & Biological Engineering & Computing, 50(8), 773-799. doi:10.1007/s11517-012-0924-6Koivumäki, J. T., Seemann, G., Maleckar, M. M., & Tavi, P. (2014). In Silico Screening of the Key Cellular Remodeling Targets in Chronic Atrial Fibrillation. PLoS Computational Biology, 10(5), e1003620. doi:10.1371/journal.pcbi.1003620Garcia-Molla, V. M., Liberos, A., Vidal, A., Guillem, M. S., Millet, J., Gonzalez, A., … Climent, A. M. (2014). Adaptive step ODE algorithms for the 3D simulation of electric heart activity with graphics processing units. Computers in Biology and Medicine, 44, 15-26. doi:10.1016/j.compbiomed.2013.10.023Rodrigo, M., Climent, A. M., Liberos, A., Calvo, D., Fernández-Avilés, F., Berenfeld, O., … Guillem, M. S. (2016). Identification of Dominant Excitation Patterns and Sources of Atrial Fibrillation by Causality Analysis. Annals of Biomedical Engineering, 44(8), 2364-2376. doi:10.1007/s10439-015-1534-xPEDRÓN-TORRECILLA, J., RODRIGO, M., CLIMENT, A. M., LIBEROS, A., PÉREZ-DAVID, E., BERMEJO, J., … GUILLEM, M. S. (2016). Noninvasive Estimation of Epicardial Dominant High-Frequency Regions During Atrial Fibrillation. Journal of Cardiovascular Electrophysiology, 27(4), 435-442. doi:10.1111/jce.12931Zlochiver, S., Yamazaki, M., Kalifa, J., & Berenfeld, O. (2008). Rotor meandering contributes to irregularity in electrograms during atrial fibrillation. Heart Rhythm, 5(6), 846-854. doi:10.1016/j.hrthm.2008.03.010ALHUSSEINI, M., VIDMAR, D., MECKLER, G. L., KOWALEWSKI, C. A., SHENASA, F., WANG, P. J., … RAPPEL, W.-J. (2017). Two Independent Mapping Techniques Identify Rotational Activity Patterns at Sites of Local Termination During Persistent Atrial Fibrillation. Journal of Cardiovascular Electrophysiology, 28(6), 615-622. doi:10.1111/jce.1317

Minimal configuration of body surface potential mapping for discrimination of left versus right dominant frequencies during atrial fibrillation

[EN] Background: Ablation of drivers maintaining atrial fibrillation (AF) has been demonstrated as an effective therapy. Drivers in the form of rapidly activated atrial regions can be noninvasively localized to either left or right atria (LA, RA) with body surface potential mapping (BSPM) systems. This study quantifies the accuracy of dominant frequency (DF) measurements from reduced-leads BSPM systems and assesses the minimal configuration required for ablation guidance. Methods: Nine uniformly distributed lead sets of eight to 66 electrodes were evaluated. BSPM signals were registered simultaneously with intracardiac electrocardiograms (EGMs) in 16 AF patients. DF activity was analyzed on the surface potentials for the nine leads configurations, and the noninvasive measures were compared with the EGM recordings. Results: Surface DF measurements presented similar values than panoramic invasive EGM recordings, showing the highest DF regions in corresponding locations. The noninvasive DFs measures had a high correlation with the invasive discrete recordings; they presented a deviation of 0.8 for leads configurations with 12 or more electrodes. Conclusions: Reduced-leads BSPM systems enable noninvasive discrimination between LA versus RA DFs with similar results as higher-resolution 66-leads system. Our findings demonstrate the possible incorporation of simplified BSPM systems into clinical planning procedures for AF ablation.This work was supported in part by Generalitat-Valenciana Grants [ACIF/2013/021]; Instituto de SaludCarlos III, Ministerio de Ciencia e Innovacion [PI13/00903, PI13-01882, PI14/00857, PI16/01123, TEC2013-46067-R, DTS16/0160 and IJCI-2014-22178] cofound by FEDER.; Spanish Society of Cardiology [Clinical research Grants 2015]; Ministerio de Ciencia e Innovacion [Red RICRD12.0042.0001]; and the National Heart, Lung, and Blood Institute [P01-HL039707, P01-HL087226 and R01-HL118304].Rodrigo Bort, M.; Climent Martínez, BA.; Liberos Mascarell, A.; Fernández-Avilés, F.; Atienza, F.; Guillem Sánchez, MS.; Berenfeld, O. (2017). Minimal configuration of body surface potential mapping for discrimination of left versus right dominant frequencies during atrial fibrillation. Pacing and Clinical Electrophysiology. 40(8):940-946. https://doi.org/10.1111/pace.13133S940946408Atienza, F., Almendral, J., Ormaetxe, J. M., Moya, Á., Martínez-Alday, J. D., Hernández-Madrid, A., … Jalife, J. (2014). Comparison of Radiofrequency Catheter Ablation of Drivers and Circumferential Pulmonary Vein Isolation in Atrial Fibrillation. Journal of the American College of Cardiology, 64(23), 2455-2467. doi:10.1016/j.jacc.2014.09.053Narayan, S. M., Krummen, D. E., Clopton, P., Shivkumar, K., & Miller, J. M. (2013). Direct or Coincidental Elimination of Stable Rotors or Focal Sources May Explain Successful Atrial Fibrillation Ablation. Journal of the American College of Cardiology, 62(2), 138-147. doi:10.1016/j.jacc.2013.03.021Haissaguerre, M., Hocini, M., Denis, A., Shah, A. J., Komatsu, Y., Yamashita, S., … Dubois, R. (2014). Driver Domains in Persistent Atrial Fibrillation. Circulation, 130(7), 530-538. doi:10.1161/circulationaha.113.005421Atienza, F., Almendral, J., Jalife, J., Zlochiver, S., Ploutz-Snyder, R., Torrecilla, E. G., … Berenfeld, O. (2009). Real-time dominant frequency mapping and ablation of dominant frequency sites in atrial fibrillation with left-to-right frequency gradients predicts long-term maintenance of sinus rhythm. Heart Rhythm, 6(1), 33-40. doi:10.1016/j.hrthm.2008.10.024Lim, H. S., Zellerhoff, S., Derval, N., Denis, A., Yamashita, S., Berte, B., … Haissaguerre, M. (2015). Noninvasive Mapping to Guide Atrial Fibrillation Ablation. Cardiac Electrophysiology Clinics, 7(1), 89-98. doi:10.1016/j.ccep.2014.11.004Rodrigo, M., Guillem, M. S., Climent, A. M., Pedrón-Torrecilla, J., Liberos, A., Millet, J., … Berenfeld, O. (2014). Body surface localization of left and right atrial high-frequency rotors in atrial fibrillation patients: A clinical-computational study. Heart Rhythm, 11(9), 1584-1591. doi:10.1016/j.hrthm.2014.05.013Guillem, M. S., Climent, A. M., Millet, J., Arenal, Á., Fernández-Avilés, F., Jalife, J., … Berenfeld, O. (2013). Noninvasive Localization of Maximal Frequency Sites of Atrial Fibrillation by Body Surface Potential Mapping. Circulation: Arrhythmia and Electrophysiology, 6(2), 294-301. doi:10.1161/circep.112.000167Lux, R. L., Smith, C. R., Wyatt, R. F., & Abildskov, J. A. (1978). Limited Lead Selection for Estimation of Body Surface Potential Maps in Electrocardiography. IEEE Transactions on Biomedical Engineering, BME-25(3), 270-276. doi:10.1109/tbme.1978.326332Finlay, D. D., Nugent, C. D., Donnelly, M. P., & Black, N. D. (2008). Selection of optimal recording sites for limited lead body surface potential mapping in myocardial infarction and left ventricular hypertrophy. Journal of Electrocardiology, 41(3), 264-271. doi:10.1016/j.jelectrocard.2008.02.009Guillem, M. S., Castells, F., Climent, A. M., Bodí, V., Chorro, F. J., & Millet, J. (2008). Evaluation of lead selection methods for optimal reconstruction of body surface potentials. Journal of Electrocardiology, 41(1), 26-34. doi:10.1016/j.jelectrocard.2007.07.001De la Salud Guillem, M., Bollmann, A., Climent, A. M., Husser, D., Millet-Roig, J., & Castells, F. (2009). How Many Leads Are Necessary for a Reliable Reconstruction of Surface Potentials During Atrial Fibrillation? IEEE Transactions on Information Technology in Biomedicine, 13(3), 330-340. doi:10.1109/titb.2008.2011894Castells, F., Mora, C., Rieta, J. J., Moratal-Pérez, D., & Millet, J. (2005). Estimation of atrial fibrillatory wave from single-lead atrial fibrillation electrocardiograms using principal component analysis concepts. Medical & Biological Engineering & Computing, 43(5), 557-560. doi:10.1007/bf02351028Narayan, S. M., & Jalife, J. (2014). CrossTalk proposal: Rotors have been demonstrated to drive human atrial fibrillation. The Journal of Physiology, 592(15), 3163-3166. doi:10.1113/jphysiol.2014.271031Allessie, M., & de Groot, N. (2014). CrossTalk opposing view: Rotors have not been demonstrated to be the drivers of atrial fibrillation. The Journal of Physiology, 592(15), 3167-3170. doi:10.1113/jphysiol.2014.271809Berenfeld, O., & Oral, H. (2012). The quest for rotors in atrial fibrillation: Different nets catch different fishes. Heart Rhythm, 9(9), 1440-1441. doi:10.1016/j.hrthm.2012.04.029PEDRÓN-TORRECILLA, J., RODRIGO, M., CLIMENT, A. M., LIBEROS, A., PÉREZ-DAVID, E., BERMEJO, J., … GUILLEM, M. S. (2016). Noninvasive Estimation of Epicardial Dominant High-Frequency Regions During Atrial Fibrillation. Journal of Cardiovascular Electrophysiology, 27(4), 435-442. doi:10.1111/jce.12931Uijen, G., van Oosterom, A., & Hoekema, R. (1999). The Number of Independent Signals in Body Surface Maps. Methods of Information in Medicine, 38(02), 119-124. doi:10.1055/s-0038-1634176Ihara, Z., van Oosterom, A., Jacquemet, V., & Hoekema, R. (2007). Adaptation of the standard 12-lead electrocardiogram system dedicated to the analysis of atrial fibrillation. Journal of Electrocardiology, 40(1), 68.e1-68.e8. doi:10.1016/j.jelectrocard.2006.04.006Gerstenfeld, E. P., SippensGroenewegen, A., Lux, R. L., & Lesh, M. D. (2000). Derivation of an optimal lead set for measuring ectopic atrial activation from the pulmonary veins by using body surface mapping. Journal of Electrocardiology, 33, 179-185. doi:10.1054/jelc.2000.20307SippensGroenewegen, A., Peeters, H. A. P., Jessurun, E. R., Linnenbank, A. C., Robles de Medina, E. O., Lesh, M. D., & van Hemel, N. M. (1998). Body Surface Mapping During Pacing at Multiple Sites in the Human Atrium. Circulation, 97(4), 369-380. doi:10.1161/01.cir.97.4.369SALINET, J. L., TUAN, J. H., SANDILANDS, A. J., STAFFORD, P. J., SCHLINDWEIN, F. S., & NG, G. A. (2013). Distinctive Patterns of Dominant Frequency Trajectory Behavior in Drug-Refractory Persistent Atrial Fibrillation: Preliminary Characterization of Spatiotemporal Instability. Journal of Cardiovascular Electrophysiology, 25(4), 371-379. doi:10.1111/jce.12331Sanders, P., Berenfeld, O., Hocini, M., Jaïs, P., Vaidyanathan, R., Hsu, L.-F., … Haïssaguerre, M. (2005). Spectral Analysis Identifies Sites of High-Frequency Activity Maintaining Atrial Fibrillation in Humans. Circulation, 112(6), 789-797. doi:10.1161/circulationaha.104.517011Atienza, F., Almendral, J., Moreno, J., Vaidyanathan, R., Talkachou, A., Kalifa, J., … Berenfeld, O. (2006). Activation of Inward Rectifier Potassium Channels Accelerates Atrial Fibrillation in Humans. Circulation, 114(23), 2434-2442. doi:10.1161/circulationaha.106.63373