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      Virtual In-Silico Modeling Guided Catheter Ablation Predicts Effective Linear Ablation Lesion Set for Longstanding Persistent Atrial Fibrillation: Multicenter Prospective Randomized Study


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          Objective: Radiofrequency catheter ablation for persistent atrial fibrillation (PeAF) still has a substantial recurrence rate. This study aims to investigate whether an AF ablation lesion set chosen using in-silico ablation (V-ABL) is clinically feasible and more effective than an empirically chosen ablation lesion set (Em-ABL) in patients with PeAF.

          Methods: We prospectively included 108 patients with antiarrhythmic drug-resistant PeAF (77.8% men, age 60.8 ± 9.9 years), and randomly assigned them to the V-ABL ( n = 53) and Em-ABL ( n = 55) groups. Five different in-silico ablation lesion sets [1 pulmonary vein isolation (PVI), 3 linear ablations, and 1 electrogram-guided ablation] were compared using heart-CT integrated AF modeling. We evaluated the feasibility, safety, and efficacy of V-ABL compared with that of Em-ABL.

          Results: The pre-procedural computing time for five different ablation strategies was 166 ± 11 min. In the Em-ABL group, the earliest terminating blinded in-silico lesion set matched with the Em-ABL lesion set in 21.8%. V-ABL was not inferior to Em-ABL in terms of procedure time ( p = 0.403), ablation time ( p = 0.510), and major complication rate ( p = 0.900). During 12.6 ± 3.8 months of follow-up, the clinical recurrence rate was 14.0% in the V-ABL group and 18.9% in the Em-ABL group ( p = 0.538). In Em-ABL group, clinical recurrence rate was significantly lower after PVI+posterior box+anterior linear ablation, which showed the most frequent termination during in-silico ablation (log-rank p = 0.027).

          Conclusions: V-ABL was feasible in clinical practice, not inferior to Em-ABL, and predicts the most effective ablation lesion set in patients who underwent PeAF ablation.

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          Most cited references16

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          Computational medicine: translating models to clinical care.

          Because of the inherent complexity of coupled nonlinear biological systems, the development of computational models is necessary for achieving a quantitative understanding of their structure and function in health and disease. Statistical learning is applied to high-dimensional biomolecular data to create models that describe relationships between molecules and networks. Multiscale modeling links networks to cells, organs, and organ systems. Computational approaches are used to characterize anatomic shape and its variations in health and disease. In each case, the purposes of modeling are to capture all that we know about disease and to develop improved therapies tailored to the needs of individuals. We discuss advances in computational medicine, with specific examples in the fields of cancer, diabetes, cardiology, and neurology. Advances in translating these computational methods to the clinic are described, as well as challenges in applying models for improving patient health.
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            Substrate and Trigger Ablation for Reduction of Atrial Fibrillation (STAR AF): a randomized, multicentre, international trial†

            Aims This multicentre, randomized trial compared three strategies of AF ablation: ablation of complex fractionated electrograms (CFE) alone, pulmonary vein isolation (PVI) alone, and combined PVI + CFE ablation, using standardized automated mapping software. Methods and results Patients with drug-refractory, high-burden paroxysmal (episodes >6 h, >4 in 6 months) or persistent atrial fibrillation (AF) were enrolled at eight centres. Patients (n = 100) were randomized to one of three arms. For CFE alone (n = 34), spontaneous/induced AF was mapped using validated, automated CFE software and all sites 30 s at 1 year. Patients (age 57 ± 10 years, LA size 42 ± 6 mm) were 35% persistent AF. In CFE, ablation terminated AF in 68%. Only 0.4 PVs per patient were isolated as a result of CFE. In PVI, 94% had all four PVs successfully isolated. In PVI + CFE, 94% had all four PVs isolated, 76% had inducible AF with additional CFE ablation, with 73% termination of AF. There were significantly more repeat procedures in the CFE arm (47%) vs. PVI (31%) or PVI + CFE (15%) (P = 0.01). After one procedure, PVI + CFE had a significantly higher freedom from AF (74%) compared with PVI (48%) and CFE (29%) (P = 0.004). After two procedures, PVI + CFE still had the highest success (88%) compared with PVI (68%) and CFE (38%) (P = 0.001). Ninety-six percent of these patients were off anti-arrhythmics. Complications were two tamponades, no PV stenosis, and no mortality. Conclusion In high-burden paroxysmal/persistent AF, PVI + CFE has the highest freedom from AF vs. PVI or CFE alone after one or two procedures. Complex fractionated electrogram alone has the lowest one and two procedure success rates with a higher incidence of repeat procedures. ClinicalTrials.gov identifier number NCT00367757.
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              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.

              The clinical significance of left atrial pressure (LAP) has not yet been clearly elucidated in patients with atrial fibrillation (AF). To explore the effects of elevated LAP on pathophysiology and clinical outcome after radiofrequency catheter ablation in patients with AF. We measured LAP during both sinus rhythm (SR) and AF in 454 patients 348 (76.7%) men; mean age 58 ± 11 years; 326(71.8%) paroxysmal AF) who underwent radiofrequency catheter ablation and compared LAP at v wave (LAPpeak) and LAP at y descent (LAPnadir) by using imaging (echocardiography and computed tomography), electrophysiologic mapping (NavX), and clinical data. In 280 (61.7%) patients, pulmonary vein (PV) diastolic flow velocity was measured during SR by transesophageal echocardiography. Patients with LAPpeak(SR) ≥19 mm Hg had greater left atrial (LA) dimension (P < .001), LA volume index (P = .003), and E/Em (mitral annular septal area [peak diastolic velocity]; P = .001) but reduced LA voltage (P < .001) and mitral annular septal area (peak systolic velocity; P = .006) compared with patients with LAPpeak(SR) <19 mm Hg. High LAPpeak(SR) was independently associated with anterior LA volume (linear regression coefficient [B] = 0.381; 95% confidence interval [CI] 0.169-0.593; P < .001) and low LA voltage (B = -0.022; 95% CI -0.030 to -0.013; P < .001). PV diastolic flow velocity (B = 0.161; 95% CI 0.083-0.239; P < .001) and E/Em (B = 0.430; 95% CI 0.096-0.763; P = .012) were independent, noninvasive parameters associated with high LApeak(SR). During 13.1 ± 6.0 months of follow-up, high LAPpeak(SR) was an independent predictor for clinical recurrence of AF (hazard ratio 1.887; 95% CI 1.063-3.350; P = .028). Elevated LAP was closely associated with electroanatomical remodeling of the LA and was an independent predictor for recurrence after AF ablation. PV diastolic flow velocity and E/Em can be used as a noninvasive parameter predicting high LAPpeak(SR) in patients with AF. Copyright © 2014 Heart Rhythm Society. All rights reserved.

                Author and article information

                Front Physiol
                Front Physiol
                Front. Physiol.
                Frontiers in Physiology
                Frontiers Media S.A.
                11 October 2017
                : 8
                : 792
                [1] 1Cardiovascular Center, Korea University , Seoul, South Korea
                [2] 2Division of Cardiology, Yonsei University Health System , Seoul, South Korea
                [3] 3Division of Cardiology, Catholic University of Korea , Seoul, South Korea
                [4] 4Asan Medical Center, University of Ulsan , Seoul, South Korea
                [5] 5Samsung Medical Center, Sungkyunkwan University , Seoul, South Korea
                [6] 6Division of Cardiology, Seoul National University , Seoul, South Korea
                Author notes

                Edited by: Eun Bo Shim, Kangwon National University, South Korea

                Reviewed by: Jae Boum Youm, Inje University, South Korea; Seiryo Sugiura, The University of Tokyo, Japan

                *Correspondence: Hui-Nam Pak hnpak@ 123456yuhs.ac

                This article was submitted to Computational Physiology and Medicine, a section of the journal Frontiers in Physiology

                †These authors have contributed equally to this work.

                Copyright © 2017 Shim, Hwang, Song, Lim, Kim, Joung, Kim, Oh, Nam, On, Oh, Kim and Pak.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                : 25 May 2017
                : 27 September 2017
                Page count
                Figures: 4, Tables: 3, Equations: 1, References: 30, Pages: 8, Words: 6154
                Funded by: Ministry of Health and Welfare 10.13039/100008903
                Award ID: A085136
                Funded by: Ministry of Education 10.13039/100010449
                Award ID: 2017R1D1A1B03030495
                Original Research

                Anatomy & Physiology
                atrial fibrillation,catheter ablation,virtual ablation,in-silico modeling,recurrence


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