Literature DB >> 25261813

Virtual ablation for atrial fibrillation in personalized in-silico three-dimensional left atrial modeling: comparison with clinical catheter ablation.

Minki Hwang1, Soon-Sung Kwon2, Jin Wi1, Mijin Park1, Hyun-Seung Lee2, Jin-Seo Park2, Young-Seon Lee1, Eun Bo Shim3, Hui-Nam Pak4.   

Abstract

BACKGROUND: Although catheter ablation is an effective rhythm control strategy for atrial fibrillation (AF), empirically-based ablation has a substantial recurrence rate. The purposes of this study were to develop a computational platform for patient-specific virtual AF ablation and to compare the anti-fibrillatory effects of 5 different virtual ablation protocols with empirically chosen clinical ablations.
METHODS: We included 20 patients with AF (65% male, 60.1 ± 10.5 years old, 80% persistent AF [PeAF]) who had undergone empirically-based catheter ablation: circumferential pulmonary vein isolation (CPVI) for paroxysmal AF (PAF) and additional posterior box lesion (L1) and anterior line (L2) for PeAF. Using patient-specific three-dimensional left atrial (LA) geometry, we generated a finite element model and tested the AF termination rate after 5 different virtual ablations: CPVI alone, CPVI + L1, CPVI + L1,2, CPVI with complex fractionated atrial electrogram (CFAE) ablation, and CFAE ablation alone.
RESULTS: 1. Virtual CPVI + L1,2 ablation showed the highest AF termination rate in overall patients (55%) and PeAF patients (n = 16, 62.5%). 2. The virtual AF maintenance duration was shortest in the case of virtual CPVI + L1,2 ablation in overall patients (2.19 ± 1.28 vs. 2.91 ± 1.04 s, p = 0.009) and in patients with PeAF (2.05 ± 1.23 vs. 2.93 ± 10.2 s, p = 0.004) compared with other protocols.
CONCLUSION: Virtual AF ablation using personalized in-silico model of LA is feasible. Virtual ablation with CPVI + L1,2 shows the highest antifibrillatory effect, concordant with the empirical ablation protocol in patients with PeAF.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Atrial fibrillation; Catheter ablation; Simulation; Virtual ablation

Mesh:

Year:  2014        PMID: 25261813     DOI: 10.1016/j.pbiomolbio.2014.09.006

Source DB:  PubMed          Journal:  Prog Biophys Mol Biol        ISSN: 0079-6107            Impact factor:   3.667


  25 in total

Review 1.  Lessons from computer simulations of ablation of atrial fibrillation.

Authors:  Vincent Jacquemet
Journal:  J Physiol       Date:  2016-03-04       Impact factor: 5.182

Review 2.  Computational modeling: What does it tell us about atrial fibrillation therapy?

Authors:  Eleonora Grandi; Dobromir Dobrev; Jordi Heijman
Journal:  Int J Cardiol       Date:  2019-01-25       Impact factor: 4.164

Review 3.  The role of personalized atrial modeling in understanding atrial fibrillation mechanisms and improving treatment.

Authors:  Konstantinos N Aronis; Rheeda Ali; Natalia A Trayanova
Journal:  Int J Cardiol       Date:  2019-01-31       Impact factor: 4.164

Review 4.  Current progress of computational modeling for guiding clinical atrial fibrillation ablation.

Authors:  Zhenghong Wu; Yunlong Liu; Lv Tong; Diandian Dong; Dongdong Deng; Ling Xia
Journal:  J Zhejiang Univ Sci B       Date:  2021-10-15       Impact factor: 3.066

Review 5.  Anti-arrhythmic strategies for atrial fibrillation: The role of computational modeling in discovery, development, and optimization.

Authors:  Eleonora Grandi; Mary M Maleckar
Journal:  Pharmacol Ther       Date:  2016-09-06       Impact factor: 12.310

Review 6.  Elimination Of Triggers Without An Additional Substrate Modification Is Not Sufficient In Patients With Persistent Atrial Fibrillation.

Authors:  Junbeom Park; Hui-Nam Pak
Journal:  J Atr Fibrillation       Date:  2015-02-28

Review 7.  Predicting the risk of sudden cardiac death.

Authors:  Claudia Lerma; Leon Glass
Journal:  J Physiol       Date:  2016-02-02       Impact factor: 5.182

Review 8.  Optimization of catheter ablation of atrial fibrillation: insights gained from clinically-derived computer models.

Authors:  Jichao Zhao; Sanjay R Kharche; Brian J Hansen; Thomas A Csepe; Yufeng Wang; Martin K Stiles; Vadim V Fedorov
Journal:  Int J Mol Sci       Date:  2015-05-13       Impact factor: 5.923

9.  Electrophysiological Rotor Ablation in In-Silico Modeling of Atrial Fibrillation: Comparisons with Dominant Frequency, Shannon Entropy, and Phase Singularity.

Authors:  Minki Hwang; Jun-Seop Song; Young-Seon Lee; Changyong Li; Eun Bo Shim; Hui-Nam Pak
Journal:  PLoS One       Date:  2016-02-24       Impact factor: 3.240

10.  The Spatiotemporal Stability of Dominant Frequency Sites in In-Silico Modeling of 3-Dimensional Left Atrial Mapping of Atrial Fibrillation.

Authors:  Changyong Li; Byounghyun Lim; Minki Hwang; Jun-Seop Song; Young-Seon Lee; Boyoung Joung; Hui-Nam Pak
Journal:  PLoS One       Date:  2016-07-26       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.