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Associations between fully-automated, 3D-based functional analysis of the left atrium and classification schemes in atrial fibrillation
BACKGROUND: Atrial fibrillation (AF) has been linked to left atrial (LA) enlargement. Whereas most studies focused on 2D-based estimation of static LA volume (LAV), we used a fully-automatic convolutional neural network (CNN) for time-resolved (CINE) volumetry of the whole LA on cardiac MRI (cMRI)....
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9377598/ https://www.ncbi.nlm.nih.gov/pubmed/35969532 http://dx.doi.org/10.1371/journal.pone.0272011 |
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author | Pradella, Maurice Anastasopoulos, Constantin Yang, Shan Moor, Manuela Badertscher, Patrick Gehweiler, Julian E. Spies, Florian Haaf, Philip Zellweger, Michael Sommer, Gregor Stieltjes, Bram Bremerich, Jens Osswald, Stefan Kühne, Michael Sticherling, Christian Knecht, Sven |
author_facet | Pradella, Maurice Anastasopoulos, Constantin Yang, Shan Moor, Manuela Badertscher, Patrick Gehweiler, Julian E. Spies, Florian Haaf, Philip Zellweger, Michael Sommer, Gregor Stieltjes, Bram Bremerich, Jens Osswald, Stefan Kühne, Michael Sticherling, Christian Knecht, Sven |
author_sort | Pradella, Maurice |
collection | PubMed |
description | BACKGROUND: Atrial fibrillation (AF) has been linked to left atrial (LA) enlargement. Whereas most studies focused on 2D-based estimation of static LA volume (LAV), we used a fully-automatic convolutional neural network (CNN) for time-resolved (CINE) volumetry of the whole LA on cardiac MRI (cMRI). Aim was to investigate associations between functional parameters from fully-automated, 3D-based analysis of the LA and current classification schemes in AF. METHODS: We retrospectively analyzed consecutive AF patients who underwent cMRI on 1.5T systems including a stack of oblique-axial CINE series covering the whole LA. The LA was automatically segmented by a validated CNN. In the resulting volume-time curves, maximum, minimum and LAV before atrial contraction were automatically identified. Active, passive and total LA emptying fractions (LAEF) were calculated and compared to clinical classifications (AF Burden score (AFBS), increased stroke risk (CHA(2)DS(2)VASc≥2), AF type (paroxysmal/persistent), EHRA score, and AF risk factors). Moreover, multivariable linear regression models (mLRM) were used to identify associations with AF risk factors. RESULTS: Overall, 102 patients (age 61±9 years, 17% female) were analyzed. Active LAEF (LAEF_active) decreased significantly with an increase of AFBS (minimal: 44.0%, mild: 36.2%, moderate: 31.7%, severe: 20.8%, p<0.003) which was primarily caused by an increase of minimum LAV. Likewise, LAEF_active was lower in patients with increased stroke risk (30.7% vs. 38.9%, p = 0.002). AF type and EHRA score did not show significant differences between groups. In mLRM, a decrease of LAEF_active was associated with higher age (per year: -0.3%, p = 0.02), higher AFBS (per category: -4.2%, p<0.03) and heart failure (-12.1%, p<0.04). CONCLUSIONS: Fully-automatic morphometry of the whole LA derived from cMRI showed significant relationships between LAEF_active with increased stroke risk and severity of AFBS. Furthermore, higher age, higher AFBS and presence of heart failure were independent predictors of reduced LAEF_active, indicating its potential usefulness as an imaging biomarker. |
format | Online Article Text |
id | pubmed-9377598 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-93775982022-08-16 Associations between fully-automated, 3D-based functional analysis of the left atrium and classification schemes in atrial fibrillation Pradella, Maurice Anastasopoulos, Constantin Yang, Shan Moor, Manuela Badertscher, Patrick Gehweiler, Julian E. Spies, Florian Haaf, Philip Zellweger, Michael Sommer, Gregor Stieltjes, Bram Bremerich, Jens Osswald, Stefan Kühne, Michael Sticherling, Christian Knecht, Sven PLoS One Research Article BACKGROUND: Atrial fibrillation (AF) has been linked to left atrial (LA) enlargement. Whereas most studies focused on 2D-based estimation of static LA volume (LAV), we used a fully-automatic convolutional neural network (CNN) for time-resolved (CINE) volumetry of the whole LA on cardiac MRI (cMRI). Aim was to investigate associations between functional parameters from fully-automated, 3D-based analysis of the LA and current classification schemes in AF. METHODS: We retrospectively analyzed consecutive AF patients who underwent cMRI on 1.5T systems including a stack of oblique-axial CINE series covering the whole LA. The LA was automatically segmented by a validated CNN. In the resulting volume-time curves, maximum, minimum and LAV before atrial contraction were automatically identified. Active, passive and total LA emptying fractions (LAEF) were calculated and compared to clinical classifications (AF Burden score (AFBS), increased stroke risk (CHA(2)DS(2)VASc≥2), AF type (paroxysmal/persistent), EHRA score, and AF risk factors). Moreover, multivariable linear regression models (mLRM) were used to identify associations with AF risk factors. RESULTS: Overall, 102 patients (age 61±9 years, 17% female) were analyzed. Active LAEF (LAEF_active) decreased significantly with an increase of AFBS (minimal: 44.0%, mild: 36.2%, moderate: 31.7%, severe: 20.8%, p<0.003) which was primarily caused by an increase of minimum LAV. Likewise, LAEF_active was lower in patients with increased stroke risk (30.7% vs. 38.9%, p = 0.002). AF type and EHRA score did not show significant differences between groups. In mLRM, a decrease of LAEF_active was associated with higher age (per year: -0.3%, p = 0.02), higher AFBS (per category: -4.2%, p<0.03) and heart failure (-12.1%, p<0.04). CONCLUSIONS: Fully-automatic morphometry of the whole LA derived from cMRI showed significant relationships between LAEF_active with increased stroke risk and severity of AFBS. Furthermore, higher age, higher AFBS and presence of heart failure were independent predictors of reduced LAEF_active, indicating its potential usefulness as an imaging biomarker. Public Library of Science 2022-08-15 /pmc/articles/PMC9377598/ /pubmed/35969532 http://dx.doi.org/10.1371/journal.pone.0272011 Text en © 2022 Pradella et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Pradella, Maurice Anastasopoulos, Constantin Yang, Shan Moor, Manuela Badertscher, Patrick Gehweiler, Julian E. Spies, Florian Haaf, Philip Zellweger, Michael Sommer, Gregor Stieltjes, Bram Bremerich, Jens Osswald, Stefan Kühne, Michael Sticherling, Christian Knecht, Sven Associations between fully-automated, 3D-based functional analysis of the left atrium and classification schemes in atrial fibrillation |
title | Associations between fully-automated, 3D-based functional analysis of the left atrium and classification schemes in atrial fibrillation |
title_full | Associations between fully-automated, 3D-based functional analysis of the left atrium and classification schemes in atrial fibrillation |
title_fullStr | Associations between fully-automated, 3D-based functional analysis of the left atrium and classification schemes in atrial fibrillation |
title_full_unstemmed | Associations between fully-automated, 3D-based functional analysis of the left atrium and classification schemes in atrial fibrillation |
title_short | Associations between fully-automated, 3D-based functional analysis of the left atrium and classification schemes in atrial fibrillation |
title_sort | associations between fully-automated, 3d-based functional analysis of the left atrium and classification schemes in atrial fibrillation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9377598/ https://www.ncbi.nlm.nih.gov/pubmed/35969532 http://dx.doi.org/10.1371/journal.pone.0272011 |
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