Clinical Usefulness of Computational Modeling-Guided Persistent Atrial Fibrillation Ablation: Updated Outcome of Multicenter Randomized Study

In-Soo Kim, Byounghyun Lim, Jaemin Shim, Minki Hwang, Hee Tae Yu, Tae-Hoon Kim, Jae-Sun Uhm, Sung-Hwan Kim, Boyoung Joung, Young Keun On, Seil Oh, Yong-Seog Oh, Gi-Byung Nam, Moon-Hyoung Lee, Eun Bo Shim, Young-Hoon Kim, Hui-Nam Pak, CUVIA-AF1 Investigators, In-Soo Kim, Byounghyun Lim, Jaemin Shim, Minki Hwang, Hee Tae Yu, Tae-Hoon Kim, Jae-Sun Uhm, Sung-Hwan Kim, Boyoung Joung, Young Keun On, Seil Oh, Yong-Seog Oh, Gi-Byung Nam, Moon-Hyoung Lee, Eun Bo Shim, Young-Hoon Kim, Hui-Nam Pak, CUVIA-AF1 Investigators

Abstract

Objective: Catheter ablation of persistent atrial fibrillation (AF) is still challenging, no optimal extra-pulmonary vein lesion set is known. We previously reported the clinical feasibility of computational modeling-guided AF catheter ablation.

Methods: We randomly assigned 118 patients with persistent AF (77.8% men, age 60.8 ± 9.9 years) to the computational modeling-guided ablation group (53 patients) and the empirical ablation group (55 patients) based on the operators' experience. For virtual ablation, four virtual linear and one electrogram-guided lesion sets were tested on patient heart computed tomogram-based models, and the lesion set with the fastest termination time was reported to the operator in the modeling-guided ablation group. The primary outcome was freedom from atrial tachyarrhythmias lasting longer than 30 s after a single procedure.

Results: During 31.5 ± 9.4 months, virtual ablation procedures were available in 95.2% of the patients (108/118). Clinical recurrence rate was significantly lower after a modeling-guided ablation than after an empirical ablation (20.8 vs. 40.0%, log-rank p = 0.042). Modeling-guided ablation was independently associated with a better long-term rhythm outcome of persistent AF ablation (HR = 0.29 [0.12-0.69], p = 0.005). The rhythm outcome of the modeling-guided ablation showed better trends in males, non-obese patients with a less remodeled atrium (left atrial dimension < 50 mm), ejection fraction ≥ 50%, and those without hypertension or diabetes (p < 0.01). There were no significant differences between the groups for the total procedure time (p = 0.403), ablation time (p = 0.510), and major complication rate (p = 0.900).

Conclusion: Among patients with persistent AF, the computational modeling-guided ablation was superior to the empirical catheter ablation regarding the rhythm outcome.

Clinical trial registration: This study was registered with the ClinicalTrials.gov, number NCT02171364.

Keywords: atrial fibrillation; catheter ablation; computational modeling; recurrence; virtual ablation.

Copyright © 2019 Kim, Lim, Shim, Hwang, Yu, Kim, Uhm, Kim, Joung, On, Oh, Oh, Nam, Lee, Shim, Kim and Pak.

Figures

FIGURE 1
FIGURE 1
Study flow diagram. The enrolled patients were randomly assigned to either the computational modeling-guided ablation group or the empirical ablation group. PeAF, persistent atrial fibrillation; RFCA, radiofrequency catheter ablation.
FIGURE 2
FIGURE 2
Five different protocols of virtual ablation. AL, left atrial anterior linear line; CFAE, complex fragmented atrial electrogram; CPVI, circumferential pulmonary vein isolation; LLI, left atrial left lateral isthmus line; POBI, posterior box isolation; Roof, left atrial roof line.
FIGURE 3
FIGURE 3
Kaplan–Meier curves according to patients with AAD usage. (A) Overall patients. (B) Patients with maintaining AAD use after catheter ablation. (C) Patients without maintaining AAD use after catheter ablation. AAD, antiarrhythmic drug.
FIGURE 4
FIGURE 4
Age- and sex-adjusted HR for post-RFCA clinical recurrence of AF according to subgroups (Cox proportional-hazard model regression analysis). AF, atrial fibrillation; AP diameter, antero-posterior diameter; BMI, body mass index; DM, diabetes mellitus; EF, ejection fraction; E/Em, the ratio of early transmitral flow velocity (E) to early mitral annular velocity (Em); HR, hazard ratio; HTN, hypertension.

References

    1. Beinart R., Abbara S., Blum A., Ferencik M., Heist K., Ruskin J., et al. (2011). Left atrial wall thickness variability measured by CT scans in patients undergoing pulmonary vein isolation. J. Cardiovasc. Electrophysiol. 22 1232–1236. 10.1111/j.1540-8167.2011.02100.x
    1. Calkins H., Kuck K. H., Cappato R., Brugada J., Camm A. J., Chen S. A., et al. (2012). 2012 HRS/EHRA/ECAS expert consensus statement on catheter and surgical ablation of atrial fibrillation: recommendations for patient selection, procedural techniques, patient management and follow-up, definitions, endpoints, and research trial design: a report of the heart rhythm society (HRS) task force on catheter and surgical ablation of atrial fibrillation. Developed in partnership with the European heart rhythm association (EHRA), a registered branch of the European society of cardiology (ESC) and the European cardiac arrhythmia society (ECAS); and in collaboration with the American college of cardiology (ACC), American heart association (AHA), the Asia Pacific Heart Rhythm Society (APHRS), and the society of thoracic surgeons (STS). Endorsed by the governing bodies of the American college of cardiology foundation, the American heart association, the European cardiac arrhythmia society, the European heart rhythm association, the society of thoracic surgeons, the Asia pacific heart rhythm society, and the heart rhythm society. Heart Rhythm 9 632–696e.21. 10.1016/j.hrthm.2011.12.016
    1. Courtemanche M., Ramirez R. J., Nattel S. (1998). Ionic mechanisms underlying human atrial action potential properties: insights from a mathematical model. Am. J. Physiol. 275 H301–H321. 10.1152/ajpheart.1998.275.1.H301
    1. Dimitri H., Ng M., Brooks A. G., Kuklik P., Stiles M. K., Lau D. H., et al. (2012). Atrial remodeling in obstructive sleep apnea: implications for atrial fibrillation. Heart Rhythm 9 321–327. 10.1016/j.hrthm.2011.10.017
    1. Dossel O., Krueger M. W., Weber F. M., Wilhelms M., Seemann G. (2012). Computational modeling of the human atrial anatomy and electrophysiology. Med. Biol. Eng. Comput. 50 773–799. 10.1007/s11517-012-0924-6
    1. Haissaguerre M., Hocini M., Denis A., Shah A. J., Komatsu Y., Yamashita S., et al. (2014). Driver domains in persistent atrial fibrillation. Circulation 130 530–538. 10.1161/CIRCULATIONAHA.113.005421
    1. Haissaguerre M., Hocini M., Sanders P., Sacher F., Rotter M., Takahashi Y., et al. (2005). Catheter ablation of long-lasting persistent atrial fibrillation: clinical outcome and mechanisms of subsequent arrhythmias. J. Cardiovasc. Electrophysiol. 16 1138–1147. 10.1111/j.1540-8167.2005.00308.x
    1. Hansen B. J., Csepe T. A., Zhao J., Ignozzi A. J., Hummel J. D., Fedorov V. V. (2016). Maintenance of atrial fibrillation: are reentrant drivers with spatial stability the key? Circ. Arrhythm. Electrophysiol. 9:e004398. 10.1161/CIRCEP.116.004398
    1. Hansen B. J., Zhao J., Csepe T. A., Moore B. T., Li N., Jayne L. A., et al. (2015). Atrial fibrillation driven by micro-anatomic intramural re-entry revealed by simultaneous sub-epicardial and sub-endocardial optical mapping in explanted human hearts. Eur. Heart J. 36 2390–2401. 10.1093/eurheartj/ehv233
    1. Hwang M., Kwon S. S., Wi J., Park M., Lee H. S., Park J. S., et al. (2014). Virtual ablation for atrial fibrillation in personalized in-silico three-dimensional left atrial modeling: comparison with clinical catheter ablation. Prog. Biophys. Mol. Biol. 116 40–47. 10.1016/j.pbiomolbio.2014.09.006
    1. Hwang M., Song J. S., Lee Y. S., Li C., Shim E. B., Pak H. N. (2016). Electrophysiological rotor ablation in in-Silico modeling of atrial fibrillation: comparisons with dominant frequency, shannon entropy, and phase singularity. PLoS One 11:e0149695. 10.1371/journal.pone.0149695
    1. Jacquemet V. (2015). Modeling left and right atrial contributions to the ECG: a dipole-current source approach. Comput. Biol. Med. 65 192–199. 10.1016/j.compbiomed.2015.06.007
    1. Kim T. H., Park J., Park J. K., Uhm J. S., Joung B., Lee M. H., et al. (2014). Pericardial fat volume is associated with clinical recurrence after catheter ablation for persistent atrial fibrillation, but not paroxysmal atrial fibrillation: an analysis of over 600-patients. Int. J. Cardiol. 176 841–846. 10.1016/j.ijcard.2014.08.008
    1. Kim T. H., Park J., Uhm J. S., Kim J. Y., Joung B., Lee M. H., et al. (2016). Challenging achievement of bidirectional block after linear ablation affects the rhythm outcome in patients with persistent atrial fibrillation. J. Am. Heart Assoc. 5:e003894. 10.1161/JAHA.116.003894
    1. Knecht S., Hocini M., Wright M., Lellouche N., O’Neill M. D., Matsuo S., et al. (2008). Left atrial linear lesions are required for successful treatment of persistent atrial fibrillation. Eur. Heart J. 29 2359–2366. 10.1093/eurheartj/ehn302
    1. Labarthe S., Bayer J., Coudiere Y., Henry J., Cochet H., Jais P., et al. (2014). A bilayer model of human atria: mathematical background, construction, and assessment. Europace 16(Suppl. 4), iv21–iv29. 10.1093/europace/euu256
    1. Lim B., Hwang M., Song J. S., Ryu A. J., Joung B., Shim E. B., et al. (2017). Effectiveness of atrial fibrillation rotor ablation is dependent on conduction velocity: an in-silico 3-dimensional modeling study. PLoS One 12:e0190398. 10.1371/journal.pone.0190398
    1. Mahajan R., Nelson A., Pathak R. K., Middeldorp M. E., Wong C. X., Twomey D. J., et al. (2018). Electroanatomical remodeling of the atria in obesity: impact of adjacent epicardial fat. JACC Clin. Electrophysiol. 4 1529–1540. 10.1016/j.jacep.2018.08.014
    1. Marrouche N. F., Brachmann J., Andresen D., Siebels J., Boersma L., Jordaens L., et al. (2018). Catheter ablation for atrial fibrillation with heart failure. N. Engl. J. Med. 378 417–427. 10.1056/NEJMoa1707855
    1. Nademanee K., McKenzie J., Kosar E., Schwab M., Sunsaneewitayakul B., Vasavakul T., et al. (2004). A new approach for catheter ablation of atrial fibrillation: mapping of the electrophysiologic substrate. J. Am. Coll. Cardiol. 43 2044–2053. 10.1016/j.jacc.2003.12.054
    1. Narayan S. M., Baykaner T., Clopton P., Schricker A., Lalani G. G., Krummen D. E., et al. (2014). Ablation of rotor and focal sources reduces late recurrence of atrial fibrillation compared with trigger ablation alone: extended follow-up of the CONFIRM trial (conventional ablation for atrial fibrillation with or without focal impulse and rotor modulation). J. Am. Coll. Cardiol. 63 1761–1768. 10.1016/j.jacc.2014.02.543
    1. Pak H. N., Hwang C., Lim H. E., Kim J. W., Lee H. S., Kim Y. H. (2006). Electroanatomic characteristics of atrial premature beats triggering atrial fibrillation in patients with persistent versus paroxysmal atrial fibrillation. J. Cardiovasc. Electrophysiol. 17 818–824. 10.1111/j.1540-8167.2006.00503.x
    1. Park J., Joung B., Uhm J. S., Young Shim C., Hwang C., Hyoung Lee M., et al. (2014). High left atrial pressures are associated with advanced electroanatomical remodeling of left atrium and independent predictors for clinical recurrence of atrial fibrillation after catheter ablation. Heart Rhythm 11 953–960. 10.1016/j.hrthm.2014.03.009
    1. Pashakhanloo F., Herzka D. A., Ashikaga H., Mori S., Gai N., Bluemke D. A., et al. (2016). Myofiber architecture of the human atria as revealed by submillimeter diffusion tensor imaging. Circ. Arrhythm. Electrophysiol. 9:e004133. 10.1161/CIRCEP.116.004133
    1. Shim J., Hwang M., Song J. S., Lim B., Kim T. H., Joung B., et al. (2017). Virtual in-Silico modeling guided catheter ablation predicts effective linear ablation lesion set for longstanding persistent atrial fibrillation: multicenter prospective randomized study. Front. Physiol. 8:792. 10.3389/fphys.2017.00792
    1. Song J. S., Kim J., Lim B., Lee Y. S., Hwang M., Joung B., et al. (2018). Pro-arrhythmogenic effects of heterogeneous tissue curvature- a suggestion for role of left atrial appendage in atrial fibrillation. Circ. J. 83 32–40. 10.1253/circj.CJ-18-0615
    1. Takahashi Y., Takahashi A., Kuwahara T., Okubo K., Fujino T., Takagi K., et al. (2011). Renal function after catheter ablation of atrial fibrillation. Circulation 124 2380–2387. 10.1161/CIRCULATIONAHA.111.047266
    1. Trayanova N. A., Boyle P. M., Nikolov P. P. (2018). personalized imaging and modeling strategies for arrhythmia prevention and therapy. Curr. Opin. Biomed. Eng. 5 21–28. 10.1016/j.cobme.2017.11.007
    1. Verma A., Champagne J., Sapp J., Essebag V., Novak P., Skanes A., et al. (2013). Discerning the incidence of symptomatic and asymptomatic episodes of atrial fibrillation before and after catheter ablation (DISCERN AF): a prospective, multicenter study. JAMA Intern. Med. 173 149–156. 10.1001/jamainternmed.2013.1561
    1. Verma A., Jiang C. Y., Betts T. R., Chen J., Deisenhofer I., Mantovan R., et al. (2015). Approaches to catheter ablation for persistent atrial fibrillation. N. Engl. J. Med. 372 1812–1822. 10.1056/NEJMoa1408288
    1. Wilhelms M., Hettmann H., Maleckar M. M., Koivumaki J. T., Dossel O., Seemann G. (2012). Benchmarking electrophysiological models of human atrial myocytes. Front. Physiol. 3:487. 10.3389/fphys.2012.00487
    1. Willems S., Klemm H., Rostock T., Brandstrup B., Ventura R., Steven D., et al. (2006). Substrate modification combined with pulmonary vein isolation improves outcome of catheter ablation in patients with persistent atrial fibrillation: a prospective randomized comparison. Eur. Heart J. 27 2871–2878. 10.1093/eurheartj/ehl093
    1. Wynn G. J., Das M., Bonnett L. J., Panikker S., Wong T., Gupta D. (2014). Efficacy of catheter ablation for persistent atrial fibrillation: a systematic review and meta-analysis of evidence from randomized and nonrandomized controlled trials. Circ. Arrhythm. Electrophysiol. 7 841–852. 10.1161/CIRCEP.114.001759
    1. Zozor S., Blanc O., Jacquemet V., Virag N., Vesin J. M., Pruvot E., et al. (2003). A numerical scheme for modeling wavefront propagation on a monolayer of arbitrary geometry. IEEE Trans. Biomed. Eng. 50 412–420. 10.1109/TBME.2003.809505

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