[EN] Purpose Recent investigations failed to reproduce the positive rotor-guided ablation outcomes shown by initial studies for treating persistent atrial fibrillation (persAF). Phase singularity (PS) is an important feature for AF driver detection, but algorithms for automated PS identification differ. We aim to investigate the performance of four different techniques for automated PS detection. Methods 2048-channel virtual electrogram (VEGM) and electrocardiogram signals were collected for 30 s from 10 patients undergoing persAF ablation. QRST-subtraction was performed and VEGMs were processed using sinusoidal wavelet reconstruction. The phase was obtained using Hilbert transform. PSs were detected using four algorithms: (1) 2D image processing based and neighbor-indexing algorithm; (2) 3D neighbor-indexing algorithm; (3) 2D kernel convolutional algorithm estimating topological charge; (4) topological charge estimation on 3D mesh. PS annotations were compared using the structural similarity index (SSIM) and Pearson's correlation coefficient (CORR). Optimized parameters to improve detection accuracy were found for all four algorithms usingF(beta)score and 10-fold cross-validation compared with manual annotation. Local clustering with density-based spatial clustering of applications with noise (DBSCAN) was proposed to improve algorithms 3 and 4. Results The PS density maps created by each algorithm with default parameters were poorly correlated. Phase gradient threshold and search radius (or kernels) were shown to affect PS detections. The processing times for the algorithms were significantly different (p< 0.0001). TheF(beta)scores for algorithms 1, 2, 3, 3 + DBSCAN, 4 and 4 + DBSCAN were 0.547, 0.645, 0.742, 0.828, 0.656, and 0.831. Algorithm 4 + DBSCAN achieved the best classification performance with acceptable processing time (2.0 +/- 0.3 s). Conclusion AF driver identification is dependent on the PS detection algorithms and their parameters, which could explain some of the inconsistencies in rotor-guided ablation outcomes in different studies. For 3D triangulated meshes, algorithm 4 + DBSCAN with optimal parameters was the best solution for real-time, automated PS detection due to accuracy and speed. Similarly, algorithm 3 + DBSCAN with optimal parameters is preferred for uniform 2D meshes. Such algorithms - and parameters - should be preferred in future clinical studies for identifying AF drivers and minimizing methodological heterogeneities. This would facilitate comparisons in rotor-guided ablation outcomes in future works. This work was supported by the NIHR Leicester Biomedical Research Centre, UK. XL received research grants from Medical Research Council UK (MRC DPFS Ref: MR/S037306/1). TA received research grants from the British Heart Foundation (BHF Project Grant No. PG/18/33/33780), BHF Research Accelerator Award funding and Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP, Brazil, Grant No. 2017/00319-8). MG research was funded by a research grant from the Instituto de Salud Carlos III (Ministry of Economy and Competitiveness, Spain: PI13-00903). GN received funding from the British Heart Foundation (BHF Programme Grant, RG/17/3/32774). Li, X.; Almeida, TP.; Dastagir, N.; Guillem Sánchez, MS.; Salinet, J.; Chu, GS.; Stafford, PJ.... (2020). Standardizing Single-Frame Phase Singularity Identification Algorithms and Parameters in Phase Mapping During Human Atrial Fibrillation. Frontiers in Physiology. 11:1-16. https://doi.org/10.3389/fphys.2020.00869 ALHUSSEINI, 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.13177 Allessie, M. A., de Groot, N. M. S., Houben, R. P. M., Schotten, U., Boersma, E., Smeets, J. L., & Crijns, H. J. (2010). Electropathological Substrate of Long-Standing Persistent Atrial Fibrillation in Patients With Structural Heart Disease. Circulation: Arrhythmia and Electrophysiology, 3(6), 606-615. doi:10.1161/circep.109.910125 Benharash, P., Buch, E., Frank, P., Share, M., Tung, R., Shivkumar, K., & Mandapati, R. (2015). Quantitative Analysis of Localized Sources Identified by Focal Impulse and Rotor Modulation Mapping in Atrial Fibrillation. Circulation: Arrhythmia and Electrophysiology, 8(3), 554-561. doi:10.1161/circep.115.002721 BRAY, M.-A., LIN, S.-F., ALIEV, R. R., ROTH, B. J., & WIKSWO, J. P. (2001). Experimental and Theoretical Analysis of Phase Singularity Dynamics in Cardiac Tissue. Journal of Cardiovascular Electrophysiology, 12(6), 716-722. doi:10.1046/j.1540-8167.2001.00716.x Bray, M.-A., & Wikswo, J. P. (2002). Use of topological charge to determine filament location and dynamics in a numerical model of scroll wave activity. IEEE Transactions on Biomedical Engineering, 49(10), 1086-1093. doi:10.1109/tbme.2002.803516 Buch, E., Share, M., Tung, R., Benharash, P., Sharma, P., Koneru, J., … Shivkumar, K. (2016). Long-term clinical outcomes of focal impulse and rotor modulation for treatment of atrial fibrillation: A multicenter experience. Heart Rhythm, 13(3), 636-641. doi:10.1016/j.hrthm.2015.10.031 Canny, J. (1986). A Computational Approach to Edge Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-8(6), 679-698. doi:10.1109/tpami.1986.4767851 Clayton, R. H., & Nash, M. P. (2015). Analysis of Cardiac Fibrillation Using Phase Mapping. Cardiac Electrophysiology Clinics, 7(1), 49-58. doi:10.1016/j.ccep.2014.11.011 Davis, J., & Goadrich, M. (2006). The relationship between Precision-Recall and ROC curves. Proceedings of the 23rd international conference on Machine learning - ICML ’06. doi:10.1145/1143844.1143874 De Groot, N. M. S., Houben, R. P. M., Smeets, J. L., Boersma, E., Schotten, U., Schalij, M. J., … Allessie, M. A. (2010). Electropathological Substrate of Longstanding Persistent Atrial Fibrillation in Patients With Structural Heart Disease. Circulation, 122(17), 1674-1682. doi:10.1161/circulationaha.109.910901 Earley, M. J., Abrams, D. J. R., Sporton, S. C., & Schilling, R. J. (2006). Validation of the Noncontact Mapping System in the Left Atrium During Permanent Atrial Fibrillation and Sinus Rhythm. Journal of the American College of Cardiology, 48(3), 485-491. doi:10.1016/j.jacc.2006.04.069 Gianni, C., Mohanty, S., Di Biase, L., Metz, T., Trivedi, C., Gökoğlan, Y., … Natale, A. (2016). Acute and early outcomes of focal impulse and rotor modulation (FIRM)-guided rotors-only ablation in patients with nonparoxysmal atrial fibrillation. Heart Rhythm, 13(4), 830-835. doi:10.1016/j.hrthm.2015.12.028 GOJRATY, S., LAVI, N., VALLES, E., KIM, S. J., MICHELE, J., & GERSTENFELD, E. P. (2009). Dominant Frequency Mapping of Atrial Fibrillation: Comparison of Contact and Noncontact Approaches. Journal of Cardiovascular Electrophysiology, 20(9), 997-1004. doi:10.1111/j.1540-8167.2009.01488.x Grandi, E., Pandit, S. V., Voigt, N., Workman, A. J., Dobrev, D., Jalife, J., & Bers, D. M. (2011). Human Atrial Action Potential and Ca 2+ Model. Circulation Research, 109(9), 1055-1066. doi:10.1161/circresaha.111.253955 Gray, R. A., Pertsov, A. M., & Jalife, J. (1998). Spatial and temporal organization during cardiac fibrillation. Nature, 392(6671), 75-78. doi:10.1038/32164 Guillem, 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.112.000167 Guillem, 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/cvw011 Gurevich, D. R., & Grigoriev, R. O. (2019). Robust approach for rotor mapping in cardiac tissue. Chaos: An Interdisciplinary Journal of Nonlinear Science, 29(5), 053101. doi:10.1063/1.5086936 HAISSAGUERRE, M., HOCINI, M., SHAH, A. J., DERVAL, N., SACHER, F., JAIS, P., & DUBOIS, R. (2013). Noninvasive Panoramic Mapping of Human Atrial Fibrillation Mechanisms: A Feasibility Report. Journal of Cardiovascular Electrophysiology, 24(6), 711-717. doi:10.1111/jce.12075 Iyer, A. N., & Gray, R. A. (2001). An Experimentalist’s Approach to Accurate Localization of Phase Singularities during Reentry. Annals of Biomedical Engineering, 29(1), 47-59. doi:10.1114/1.1335538 Jalife, J. (2002). Mother rotors and fibrillatory conduction: a mechanism of atrial fibrillation. Cardiovascular Research, 54(2), 204-216. doi:10.1016/s0008-6363(02)00223-7 Jalife, J., Filgueiras Rama, D., & Berenfeld, O. (2015). Letter by Jalife et al Regarding Article, «Quantitative Analysis of Localized Sources Identified by Focal Impulse and Rotor Modulation Mapping in Atrial Fibrillation». Circulation: Arrhythmia and Electrophysiology, 8(5), 1296-1298. doi:10.1161/circep.115.003324 Jarman, J. W. E., Wong, T., Kojodjojo, P., Spohr, H., Davies, J. E., Roughton, M., … Peters, N. S. (2012). Spatiotemporal Behavior of High Dominant Frequency During Paroxysmal and Persistent Atrial Fibrillation in the Human Left Atrium. Circulation: Arrhythmia and Electrophysiology, 5(4), 650-658. doi:10.1161/circep.111.967992 Kuklik, P., Zeemering, S., Maesen, B., Maessen, J., Crijns, H. J., Verheule, S., … Schotten, U. (2015). Reconstruction of Instantaneous Phase of Unipolar Atrial Contact Electrogram Using a Concept of Sinusoidal Recomposition and Hilbert Transform. IEEE Transactions on Biomedical Engineering, 62(1), 296-302. doi:10.1109/tbme.2014.2350029 Identification of Rotors during Human Atrial Fibrillation Using Contact Mapping and Phase Singularity Detection: Technical Considerations. (2017). IEEE Transactions on Biomedical Engineering, 64(2), 310-318. doi:10.1109/tbme.2016.2554660 Lee, Y.-S., Song, J.-S., Hwang, M., Lim, B., Joung, B., & Pak, H.-N. (2016). A New Efficient Method for Detecting Phase Singularity in Cardiac Fibrillation. PLOS ONE, 11(12), e0167567. doi:10.1371/journal.pone.0167567 Li, X., Chu, G. S., Almeida, T. P., Salinet, J. L., Dastagir, N., Mistry, A. R., … André Ng, G. (2017). 5Characteristics of ablated rotors in terminating persistent atrial fibrillation using non-contact mapping. EP Europace, 19(suppl_1), i3-i3. doi:10.1093/europace/eux283.145 Li, X., Salinet, J. L., Almeida, T. P., Vanheusden, F. J., Chu, G. S., Ng, G. A., & Schlindwein, F. S. (2017). An interactive platform to guide catheter ablation in human persistent atrial fibrillation using dominant frequency, organization and phase mapping. Computer Methods and Programs in Biomedicine, 141, 83-92. doi:10.1016/j.cmpb.2017.01.011 Mandapati, R., Skanes, A., Chen, J., Berenfeld, O., & Jalife, J. (2000). Stable Microreentrant Sources as a Mechanism of Atrial Fibrillation in the Isolated Sheep Heart. Circulation, 101(2), 194-199. doi:10.1161/01.cir.101.2.194 Narayan, S. M., Baykaner, T., Clopton, P., Schricker, A., Lalani, G. G., Krummen, D. E., … Miller, J. M. (2014). Ablation of Rotor and Focal Sources Reduces Late Recurrence of Atrial Fibrillation Compared With Trigger Ablation Alone. Journal of the American College of Cardiology, 63(17), 1761-1768. doi:10.1016/j.jacc.2014.02.543 NARAYAN, S. M., KRUMMEN, D. E., & RAPPEL, W.-J. (2012). Clinical Mapping Approach To Diagnose Electrical Rotors and Focal Impulse Sources for Human Atrial Fibrillation. Journal of Cardiovascular Electrophysiology, 23(5), 447-454. doi:10.1111/j.1540-8167.2012.02332.x Narayan, S. M., Krummen, D. E., Shivkumar, K., Clopton, P., Rappel, W.-J., & Miller, J. M. (2012). Treatment of Atrial Fibrillation by the Ablation of Localized Sources. Journal of the American College of Cardiology, 60(7), 628-636. doi:10.1016/j.jacc.2012.05.022 Nattel, S. (2002). New ideas about atrial fibrillation 50 years on. Nature, 415(6868), 219-226. doi:10.1038/415219a Nattel, S. (2003). Atrial Electrophysiology and Mechanisms of Atrial Fibrillation. Journal of Cardiovascular Pharmacology and Therapeutics, 8(1_suppl), S5-S11. doi:10.1177/107424840300800102 Ortigosa, N., Fernández, C., Galbis, A., & Cano, Ó. (2015). Phase information of time-frequency transforms as a key feature for classification of atrial fibrillation episodes. Physiological Measurement, 36(3), 409-424. doi:10.1088/0967-3334/36/3/409 Pandit, S. V., & Jalife, J. (2013). Rotors and the Dynamics of Cardiac Fibrillation. Circulation Research, 112(5), 849-862. doi:10.1161/circresaha.111.300158 VII. Mathematical contributions to the theory of evolution.—III. Regression, heredity, and panmixia. (1896). Philosophical Transactions of the Royal Society of London. Series A, Containing Papers of a Mathematical or Physical Character, 187, 253-318. doi:10.1098/rsta.1896.0007 Pertsov, A. M., Davidenko, J. M., Salomonsz, R., Baxter, W. T., & Jalife, J. (1993). Spiral waves of excitation underlie reentrant activity in isolated cardiac muscle. Circulation Research, 72(3), 631-650. doi:10.1161/01.res.72.3.631 Podziemski, P., Zeemering, S., Kuklik, P., van Hunnik, A., Maesen, B., Maessen, J., … Schotten, U. (2018). Rotors Detected by Phase Analysis of Filtered, Epicardial Atrial Fibrillation Electrograms Colocalize With Regions of Conduction Block. Circulation: Arrhythmia and Electrophysiology, 11(10). doi:10.1161/circep.117.005858 Wieser, L., Stühlinger, M. C., Hintringer, F., Tilg, B., Fischer, G., & Rantner, L. J. (2007). Detection of Phase Singularities in Triangular Meshes. Methods of Information in Medicine, 46(06), 646-654. doi:10.3414/me0427 Ríos-Muñoz, G. R., Arenal, Á., & Artés-Rodríguez, A. (2018). Real-Time Rotational Activity Detection in Atrial Fibrillation. Frontiers in Physiology, 9. doi:10.3389/fphys.2018.00208 Rodrigo, M., Climent, A. M., Liberos, A., Fernández-Avilés, F., Berenfeld, O., Atienza, F., & Guillem, M. S. (2017). Technical Considerations on Phase Mapping for Identification of Atrial Reentrant Activity in Direct- and Inverse-Computed Electrograms. Circulation: Arrhythmia and Electrophysiology, 10(9). doi:10.1161/circep.117.005008 Rodrigo, 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.2014.05.013 Roney, C. H., Cantwell, C. D., Bayer, J. D., Qureshi, N. A., Lim, P. B., Tweedy, J. H., … Ng, F. S. (2017). Spatial Resolution Requirements for Accurate Identification of Drivers of Atrial Fibrillation. Circulation: Arrhythmia and Electrophysiology, 10(5). doi:10.1161/circep.116.004899 Salinet, J., Schlindwein, F. S., Stafford, P., Almeida, T. P., Li, X., Vanheusden, F. J., … Ng, G. A. (2017). Propagation of meandering rotors surrounded by areas of high dominant frequency in persistent atrial fibrillation. Heart Rhythm, 14(9), 1269-1278. doi:10.1016/j.hrthm.2017.04.031 Salinet, J. L., Madeiro, J. P. V., Cortez, P. C., Stafford, P. J., André Ng, G., & Schlindwein, F. S. (2013). Analysis of QRS-T subtraction in unipolar atrial fibrillation electrograms. Medical & Biological Engineering & Computing, 51(12), 1381-1391. doi:10.1007/s11517-013-1071-4 Salinet, J. L., Oliveira, G. N., Vanheusden, F. J., Comba, J. L. D., Ng, G. A., & Schlindwein, F. S. (2013). Visualizing intracardiac atrial fibrillation electrograms using spectral analysis. Computing in Science & Engineering, 15(2), 79-87. doi:10.1109/mcse.2013.37 Schilling, R. J., Peters, N. S., & Davies, D. W. (1998). Simultaneous Endocardial Mapping in the Human Left Ventricle Using a Noncontact Catheter. Circulation, 98(9), 887-898. doi:10.1161/01.cir.98.9.887 Schricker, A. A., Lalani, G. G., Krummen, D. E., & Narayan, S. M. (2014). Rotors as Drivers of Atrial Fibrillation and Targets for Ablation. Current Cardiology Reports, 16(8). doi:10.1007/s11886-014-0509-0 Steinberg, J. S., Shah, Y., Bhatt, A., Sichrovsky, T., Arshad, A., Hansinger, E., & Musat, D. (2017). Focal impulse and rotor modulation: Acute procedural observations and extended clinical follow-up. Heart Rhythm, 14(2), 192-197. doi:10.1016/j.hrthm.2016.11.008 THIAGALINGAM, A., WALLACE, E. M., BOYD, A. C., EIPPER, V. E., CAMPBELL, C. R., BYTH, K., … KOVOOR, P. (2004). Noncontact Mapping of the Left Ventricle:. Insights from Validation with Transmural Contact Mapping. Pacing and Clinical Electrophysiology, 27(5), 570-578. doi:10.1111/j.1540-8159.2004.00489.x Umapathy, K., Nair, K., Masse, S., Krishnan, S., Rogers, J., Nash, M. P., & Nanthakumar, K. (2010). Phase Mapping of Cardiac Fibrillation. Circulation: Arrhythmia and Electrophysiology, 3(1), 105-114. doi:10.1161/circep.110.853804 WITTKAMPF, F. H. M., & NAKAGAWA, H. (2006). RF Catheter Ablation: Lessons on Lesions. Pacing and Clinical Electrophysiology, 29(11), 1285-1297. doi:10.1111/j.1540-8159.2006.00533.x Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004). Image Quality Assessment: From Error Visibility to Structural Similarity. IEEE Transactions on Image Processing, 13(4), 600-612. doi:10.1109/tip.2003.819861

Standardizing Single-Frame Phase Singularity Identification Algorithms and Parameters in Phase Mapping During Human Atrial Fibrillation

Abstract