Novel Computational Analysis of Left Atrial Anatomy Improves Prediction of Atrial Fibrillation Recurrence after Ablation

The left atrium (LA) can change in size and shape due to atrial fibrillation (AF)-induced remodeling. These alterations can be linked to poorer outcomes of AF ablation. In this study, we propose a novel comprehensive computational analysis of LA anatomy to identify what features of LA shape can opti...

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Authors: Varela, Marta, Bisbal, Felipe, Zacur, Ernesto, Berruezo Sánchez, Antonio, Aslanidi, Oleg V., Mont Girbau, Lluís, Lamata, Pablo
Format: article
Status:Published version
Publication Date:2017
Country:España
Institution:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repository:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/121964
Online Access:https://hdl.handle.net/2445/121964
Access Level:Open access
Keyword:Anatomia humana
Fibril·lació auricular
Marcadors bioquímics
Human anatomy
Atrial fibrillation
Biochemical markers
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spelling Novel Computational Analysis of Left Atrial Anatomy Improves Prediction of Atrial Fibrillation Recurrence after AblationVarela, MartaBisbal, FelipeZacur, ErnestoBerruezo Sánchez, AntonioAslanidi, Oleg V.Mont Girbau, LluísLamata, PabloAnatomia humanaFibril·lació auricularMarcadors bioquímicsHuman anatomyAtrial fibrillationBiochemical markersThe left atrium (LA) can change in size and shape due to atrial fibrillation (AF)-induced remodeling. These alterations can be linked to poorer outcomes of AF ablation. In this study, we propose a novel comprehensive computational analysis of LA anatomy to identify what features of LA shape can optimally predict post-ablation AF recurrence. To this end, we construct smooth 3D geometrical models from the segmentation of the LA blood pool captured in pre-procedural MR images. We first apply this methodology to characterize the LA anatomy of 144 AF patients and build a statistical shape model that includes the most salient variations in shape across this cohort. We then perform a discriminant analysis to optimally distinguish between recurrent and non-recurrent patients. From this analysis, we propose a new shape metric called vertical asymmetry, which measures the imbalance of size along the anterior to posterior direction between the superior and inferior left atrial hemispheres. Vertical asymmetry was found, in combination with LA sphericity, to be the best predictor of post-ablation recurrence at both 12 and 24 months (area under the ROC curve: 0.71 and 0.68, respectively) outperforming other shape markers and any of their combinations. We also found that model-derived shape metrics, such as the anterior-posterior radius, were better predictors than equivalent metrics taken directly from MRI or echocardiography, suggesting that the proposed approach leads to a reduction of the impact of data artifacts and noise. This novel methodology contributes to an improved characterization of LA organ remodeling and the reported findings have the potential to improve patient selection and risk stratification for catheter ablations in AF.Frontiers Media2018201820172018info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion12 p.application/pdfhttps://hdl.handle.net/2445/121964Articles publicats en revistes (Medicina)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésReproducció del document publicat a: https://doi.org/10.3389/fphys.2017.00068Frontiers in Physiology, 2017, vol. 8, num. 68https://doi.org/10.3389/fphys.2017.00068info:eu-repo/grantAgreement/EC/H2020/655020cc-by (c) Varela, Marta et al., 2017http://creativecommons.org/licenses/by/3.0/esinfo:eu-repo/semantics/openAccessoai:recercat.cat:2445/1219642026-05-29T05:05:01Z
dc.title.none.fl_str_mv Novel Computational Analysis of Left Atrial Anatomy Improves Prediction of Atrial Fibrillation Recurrence after Ablation
title Novel Computational Analysis of Left Atrial Anatomy Improves Prediction of Atrial Fibrillation Recurrence after Ablation
spellingShingle Novel Computational Analysis of Left Atrial Anatomy Improves Prediction of Atrial Fibrillation Recurrence after Ablation
Varela, Marta
Anatomia humana
Fibril·lació auricular
Marcadors bioquímics
Human anatomy
Atrial fibrillation
Biochemical markers
title_short Novel Computational Analysis of Left Atrial Anatomy Improves Prediction of Atrial Fibrillation Recurrence after Ablation
title_full Novel Computational Analysis of Left Atrial Anatomy Improves Prediction of Atrial Fibrillation Recurrence after Ablation
title_fullStr Novel Computational Analysis of Left Atrial Anatomy Improves Prediction of Atrial Fibrillation Recurrence after Ablation
title_full_unstemmed Novel Computational Analysis of Left Atrial Anatomy Improves Prediction of Atrial Fibrillation Recurrence after Ablation
title_sort Novel Computational Analysis of Left Atrial Anatomy Improves Prediction of Atrial Fibrillation Recurrence after Ablation
dc.creator.none.fl_str_mv Varela, Marta
Bisbal, Felipe
Zacur, Ernesto
Berruezo Sánchez, Antonio
Aslanidi, Oleg V.
Mont Girbau, Lluís
Lamata, Pablo
author Varela, Marta
author_facet Varela, Marta
Bisbal, Felipe
Zacur, Ernesto
Berruezo Sánchez, Antonio
Aslanidi, Oleg V.
Mont Girbau, Lluís
Lamata, Pablo
author_role author
author2 Bisbal, Felipe
Zacur, Ernesto
Berruezo Sánchez, Antonio
Aslanidi, Oleg V.
Mont Girbau, Lluís
Lamata, Pablo
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Anatomia humana
Fibril·lació auricular
Marcadors bioquímics
Human anatomy
Atrial fibrillation
Biochemical markers
topic Anatomia humana
Fibril·lació auricular
Marcadors bioquímics
Human anatomy
Atrial fibrillation
Biochemical markers
description The left atrium (LA) can change in size and shape due to atrial fibrillation (AF)-induced remodeling. These alterations can be linked to poorer outcomes of AF ablation. In this study, we propose a novel comprehensive computational analysis of LA anatomy to identify what features of LA shape can optimally predict post-ablation AF recurrence. To this end, we construct smooth 3D geometrical models from the segmentation of the LA blood pool captured in pre-procedural MR images. We first apply this methodology to characterize the LA anatomy of 144 AF patients and build a statistical shape model that includes the most salient variations in shape across this cohort. We then perform a discriminant analysis to optimally distinguish between recurrent and non-recurrent patients. From this analysis, we propose a new shape metric called vertical asymmetry, which measures the imbalance of size along the anterior to posterior direction between the superior and inferior left atrial hemispheres. Vertical asymmetry was found, in combination with LA sphericity, to be the best predictor of post-ablation recurrence at both 12 and 24 months (area under the ROC curve: 0.71 and 0.68, respectively) outperforming other shape markers and any of their combinations. We also found that model-derived shape metrics, such as the anterior-posterior radius, were better predictors than equivalent metrics taken directly from MRI or echocardiography, suggesting that the proposed approach leads to a reduction of the impact of data artifacts and noise. This novel methodology contributes to an improved characterization of LA organ remodeling and the reported findings have the potential to improve patient selection and risk stratification for catheter ablations in AF.
publishDate 2017
dc.date.none.fl_str_mv 2017
2018
2018
2018
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/121964
url https://hdl.handle.net/2445/121964
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.3389/fphys.2017.00068
Frontiers in Physiology, 2017, vol. 8, num. 68
https://doi.org/10.3389/fphys.2017.00068
info:eu-repo/grantAgreement/EC/H2020/655020
dc.rights.none.fl_str_mv cc-by (c) Varela, Marta et al., 2017
http://creativecommons.org/licenses/by/3.0/es
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc-by (c) Varela, Marta et al., 2017
http://creativecommons.org/licenses/by/3.0/es
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 12 p.
application/pdf
dc.publisher.none.fl_str_mv Frontiers Media
publisher.none.fl_str_mv Frontiers Media
dc.source.none.fl_str_mv Articles publicats en revistes (Medicina)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869409453382565888
score 15,812429

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