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Comparing Reentrant Drivers Predicted by Image-Based Computational Modeling and Mapped by Electrocardiographic Imaging in Persistent Atrial Fibrillation

Electrocardiographic mapping (ECGI) detects reentrant drivers (RDs) that perpetuate arrhythmia in persistent AF (PsAF). Patient-specific computational models derived from late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) identify all latent sites in the fibrotic substrate that could pote...

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Autores principales: Boyle, Patrick M., Hakim, Joe B., Zahid, Sohail, Franceschi, William H., Murphy, Michael J., Vigmond, Edward J., Dubois, Rémi, Haïssaguerre, Michel, Hocini, Mélèze, Jaïs, Pierre, Trayanova, Natalia A., Cochet, Hubert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5917348/
https://www.ncbi.nlm.nih.gov/pubmed/29725307
http://dx.doi.org/10.3389/fphys.2018.00414
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author Boyle, Patrick M.
Hakim, Joe B.
Zahid, Sohail
Franceschi, William H.
Murphy, Michael J.
Vigmond, Edward J.
Dubois, Rémi
Haïssaguerre, Michel
Hocini, Mélèze
Jaïs, Pierre
Trayanova, Natalia A.
Cochet, Hubert
author_facet Boyle, Patrick M.
Hakim, Joe B.
Zahid, Sohail
Franceschi, William H.
Murphy, Michael J.
Vigmond, Edward J.
Dubois, Rémi
Haïssaguerre, Michel
Hocini, Mélèze
Jaïs, Pierre
Trayanova, Natalia A.
Cochet, Hubert
author_sort Boyle, Patrick M.
collection PubMed
description Electrocardiographic mapping (ECGI) detects reentrant drivers (RDs) that perpetuate arrhythmia in persistent AF (PsAF). Patient-specific computational models derived from late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) identify all latent sites in the fibrotic substrate that could potentially sustain RDs, not just those manifested during mapped AF. The objective of this study was to compare RDs from simulations and ECGI (RD(sim)/RD(ECGI)) and analyze implications for ablation. We considered 12 PsAF patients who underwent RD(ECGI) ablation. For the same cohort, we simulated AF and identified RD(sim) sites in patient-specific models with geometry and fibrosis distribution from pre-ablation LGE-MRI. RD(sim)- and RD(ECGI)-harboring regions were compared, and the extent of agreement between macroscopic locations of RDs identified by simulations and ECGI was assessed. Effects of ablating RD(ECGI)/RD(sim) were analyzed. RD(sim) were predicted in 28 atrial regions (median [inter-quartile range (IQR)] = 3.0 [1.0; 3.0] per model). ECGI detected 42 RD(ECGI)-harboring regions (4.0 [2.0; 5.0] per patient). The number of regions with RD(sim) and RD(ECGI) per individual was not significantly correlated (R = 0.46, P = ns). The overall rate of regional agreement was fair (modified Cohen's κ(0) statistic = 0.11), as expected, based on the different mechanistic underpinning of RD(sim)- and RD(ECGI). nineteen regions were found to harbor both RD(sim) and RD(ECGI), suggesting that a subset of clinically observed RDs was fibrosis-mediated. The most frequent source of differences (23/32 regions) between the two modalities was the presence of RD(ECGI) perpetuated by mechanisms other than the fibrotic substrate. In 6/12 patients, there was at least one region where a latent RD was observed in simulations but was not manifested during clinical mapping. Ablation of fibrosis-mediated RD(ECGI) (i.e., targets in regions that also harbored RD(sim)) trended toward a higher rate of positive response compared to ablation of other RD(ECGI) targets (57 vs. 41%, P = ns). Our analysis suggests that RDs in human PsAF are at least partially fibrosis-mediated. Substrate-based ablation combining simulations with ECGI could improve outcomes.
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spelling pubmed-59173482018-05-03 Comparing Reentrant Drivers Predicted by Image-Based Computational Modeling and Mapped by Electrocardiographic Imaging in Persistent Atrial Fibrillation Boyle, Patrick M. Hakim, Joe B. Zahid, Sohail Franceschi, William H. Murphy, Michael J. Vigmond, Edward J. Dubois, Rémi Haïssaguerre, Michel Hocini, Mélèze Jaïs, Pierre Trayanova, Natalia A. Cochet, Hubert Front Physiol Physiology Electrocardiographic mapping (ECGI) detects reentrant drivers (RDs) that perpetuate arrhythmia in persistent AF (PsAF). Patient-specific computational models derived from late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) identify all latent sites in the fibrotic substrate that could potentially sustain RDs, not just those manifested during mapped AF. The objective of this study was to compare RDs from simulations and ECGI (RD(sim)/RD(ECGI)) and analyze implications for ablation. We considered 12 PsAF patients who underwent RD(ECGI) ablation. For the same cohort, we simulated AF and identified RD(sim) sites in patient-specific models with geometry and fibrosis distribution from pre-ablation LGE-MRI. RD(sim)- and RD(ECGI)-harboring regions were compared, and the extent of agreement between macroscopic locations of RDs identified by simulations and ECGI was assessed. Effects of ablating RD(ECGI)/RD(sim) were analyzed. RD(sim) were predicted in 28 atrial regions (median [inter-quartile range (IQR)] = 3.0 [1.0; 3.0] per model). ECGI detected 42 RD(ECGI)-harboring regions (4.0 [2.0; 5.0] per patient). The number of regions with RD(sim) and RD(ECGI) per individual was not significantly correlated (R = 0.46, P = ns). The overall rate of regional agreement was fair (modified Cohen's κ(0) statistic = 0.11), as expected, based on the different mechanistic underpinning of RD(sim)- and RD(ECGI). nineteen regions were found to harbor both RD(sim) and RD(ECGI), suggesting that a subset of clinically observed RDs was fibrosis-mediated. The most frequent source of differences (23/32 regions) between the two modalities was the presence of RD(ECGI) perpetuated by mechanisms other than the fibrotic substrate. In 6/12 patients, there was at least one region where a latent RD was observed in simulations but was not manifested during clinical mapping. Ablation of fibrosis-mediated RD(ECGI) (i.e., targets in regions that also harbored RD(sim)) trended toward a higher rate of positive response compared to ablation of other RD(ECGI) targets (57 vs. 41%, P = ns). Our analysis suggests that RDs in human PsAF are at least partially fibrosis-mediated. Substrate-based ablation combining simulations with ECGI could improve outcomes. Frontiers Media S.A. 2018-04-19 /pmc/articles/PMC5917348/ /pubmed/29725307 http://dx.doi.org/10.3389/fphys.2018.00414 Text en Copyright © 2018 Boyle, Hakim, Zahid, Franceschi, Murphy, Vigmond, Dubois, Haïssaguerre, Hocini, Jaïs, Trayanova and Cochet. http://creativecommons.org/licenses/by/4.0/ 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) and the copyright owner 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.
spellingShingle Physiology
Boyle, Patrick M.
Hakim, Joe B.
Zahid, Sohail
Franceschi, William H.
Murphy, Michael J.
Vigmond, Edward J.
Dubois, Rémi
Haïssaguerre, Michel
Hocini, Mélèze
Jaïs, Pierre
Trayanova, Natalia A.
Cochet, Hubert
Comparing Reentrant Drivers Predicted by Image-Based Computational Modeling and Mapped by Electrocardiographic Imaging in Persistent Atrial Fibrillation
title Comparing Reentrant Drivers Predicted by Image-Based Computational Modeling and Mapped by Electrocardiographic Imaging in Persistent Atrial Fibrillation
title_full Comparing Reentrant Drivers Predicted by Image-Based Computational Modeling and Mapped by Electrocardiographic Imaging in Persistent Atrial Fibrillation
title_fullStr Comparing Reentrant Drivers Predicted by Image-Based Computational Modeling and Mapped by Electrocardiographic Imaging in Persistent Atrial Fibrillation
title_full_unstemmed Comparing Reentrant Drivers Predicted by Image-Based Computational Modeling and Mapped by Electrocardiographic Imaging in Persistent Atrial Fibrillation
title_short Comparing Reentrant Drivers Predicted by Image-Based Computational Modeling and Mapped by Electrocardiographic Imaging in Persistent Atrial Fibrillation
title_sort comparing reentrant drivers predicted by image-based computational modeling and mapped by electrocardiographic imaging in persistent atrial fibrillation
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5917348/
https://www.ncbi.nlm.nih.gov/pubmed/29725307
http://dx.doi.org/10.3389/fphys.2018.00414
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