Identifying the Principal Modes of Variation in Human Thoracic Aorta Morphology

Autores
Casciaro, Mariano Ezequiel; Craiem, Damian; Chironi, Gilles; Graf Caride, Diego Sebastián; Macron, Laurent; Mousseaux, Elie; Simon, Alain; Armentano, Ricardo Luis
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Purpose: Diagnosis and management of thoracic aorta (TA) disease demand the assessment of accurate quantitative information of the aortic anatomy. We investigated the principal modes of variation in aortic 3-dimensional geometry paying particular attention to the curvilinear portion. Materials and Methods: Images were obtained from extended noncontrast multislice computed tomography scans, originally intended for coronary calcium assessment. The ascending, arch, and descending aortas of 500 asymptomatic patients (57±9 y, 81% male) were segmented using a semiautomated algorithm that sequentially inscribed circles inside the vessel cross-section. Axial planes were used for the descending aorta, whereas oblique reconstructions through a toroid path were required for the arch. Vessel centerline coordinates and the corresponding diameter values were obtained. Twelve size and shape geometric parameters were calculated to perform a principal component analysis. Results: Statistics revealed that the geometric variability of the TA was successfully explained using 3 factors that account for ∼80% of total variability. Averaged aortas were reconstructed varying each factor in 5 intervals. Analyzing the parameter loadings for each principal component, the dominant contributors were interpreted as vessel size (46%), arch unfolding (22%), and arch symmetry (12%). Variables such as age, body size, and risk factors did not substantially modify the correlation coefficients, although some particular differences were observed with sex. Conclusions: We conclude that vessel size, arch unfolding, and symmetry form the basis for characterizing the variability of TA morphology. The numerical data provided in this study as supplementary material can be exploited to accurately reconstruct the curvilinear shape of normal TAs.
Fil: Casciaro, Mariano Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Favaloro. Facultad de Ingeniería y Ciencias Exactas y Naturales; Argentina
Fil: Craiem, Damian. Universidad Favaloro. Facultad de Ingeniería y Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Chironi, Gilles. Universite de Paris V; Francia
Fil: Graf Caride, Diego Sebastián. Universidad Favaloro. Facultad de Ingeniería y Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Macron, Laurent. Universite de Paris V; Francia
Fil: Mousseaux, Elie. Universite de Paris V; Francia
Fil: Simon, Alain. Universite de Paris V; Francia
Fil: Armentano, Ricardo Luis. Universidad Favaloro. Facultad de Ingeniería y Ciencias Exactas y Naturales; Argentina
Materia
Principal Components
Thoracic Aorta
Computed Tomography
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/28448
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/28448
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Identifying the Principal Modes of Variation in Human Thoracic Aorta MorphologyCasciaro, Mariano EzequielCraiem, DamianChironi, GillesGraf Caride, Diego SebastiánMacron, LaurentMousseaux, ElieSimon, AlainArmentano, Ricardo LuisPrincipal ComponentsThoracic AortaComputed TomographyPurpose: Diagnosis and management of thoracic aorta (TA) disease demand the assessment of accurate quantitative information of the aortic anatomy. We investigated the principal modes of variation in aortic 3-dimensional geometry paying particular attention to the curvilinear portion. Materials and Methods: Images were obtained from extended noncontrast multislice computed tomography scans, originally intended for coronary calcium assessment. The ascending, arch, and descending aortas of 500 asymptomatic patients (57±9 y, 81% male) were segmented using a semiautomated algorithm that sequentially inscribed circles inside the vessel cross-section. Axial planes were used for the descending aorta, whereas oblique reconstructions through a toroid path were required for the arch. Vessel centerline coordinates and the corresponding diameter values were obtained. Twelve size and shape geometric parameters were calculated to perform a principal component analysis. Results: Statistics revealed that the geometric variability of the TA was successfully explained using 3 factors that account for ∼80% of total variability. Averaged aortas were reconstructed varying each factor in 5 intervals. Analyzing the parameter loadings for each principal component, the dominant contributors were interpreted as vessel size (46%), arch unfolding (22%), and arch symmetry (12%). Variables such as age, body size, and risk factors did not substantially modify the correlation coefficients, although some particular differences were observed with sex. Conclusions: We conclude that vessel size, arch unfolding, and symmetry form the basis for characterizing the variability of TA morphology. The numerical data provided in this study as supplementary material can be exploited to accurately reconstruct the curvilinear shape of normal TAs.Fil: Casciaro, Mariano Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Favaloro. Facultad de Ingeniería y Ciencias Exactas y Naturales; ArgentinaFil: Craiem, Damian. Universidad Favaloro. Facultad de Ingeniería y Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Chironi, Gilles. Universite de Paris V; FranciaFil: Graf Caride, Diego Sebastián. Universidad Favaloro. Facultad de Ingeniería y Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Macron, Laurent. Universite de Paris V; FranciaFil: Mousseaux, Elie. Universite de Paris V; FranciaFil: Simon, Alain. Universite de Paris V; FranciaFil: Armentano, Ricardo Luis. Universidad Favaloro. Facultad de Ingeniería y Ciencias Exactas y Naturales; ArgentinaLippincott Williams2014-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/28448Casciaro, Mariano Ezequiel; Craiem, Damian; Chironi, Gilles; Graf Caride, Diego Sebastián; Macron, Laurent; et al.; Identifying the Principal Modes of Variation in Human Thoracic Aorta Morphology; Lippincott Williams; Journal of Thoracic Imaging; 29; 4; 7-2014; 224-2320883-5993CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://insights.ovid.com/pubmed?pmid=24296697info:eu-repo/semantics/altIdentifier/doi/10.1097/RTI.0000000000000060info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:04:04Zoai:ri.conicet.gov.ar:11336/28448instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 15:04:05.071CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Identifying the Principal Modes of Variation in Human Thoracic Aorta Morphology
title Identifying the Principal Modes of Variation in Human Thoracic Aorta Morphology
spellingShingle Identifying the Principal Modes of Variation in Human Thoracic Aorta Morphology
Casciaro, Mariano Ezequiel
Principal Components
Thoracic Aorta
Computed Tomography
title_short Identifying the Principal Modes of Variation in Human Thoracic Aorta Morphology
title_full Identifying the Principal Modes of Variation in Human Thoracic Aorta Morphology
title_fullStr Identifying the Principal Modes of Variation in Human Thoracic Aorta Morphology
title_full_unstemmed Identifying the Principal Modes of Variation in Human Thoracic Aorta Morphology
title_sort Identifying the Principal Modes of Variation in Human Thoracic Aorta Morphology
dc.creator.none.fl_str_mv Casciaro, Mariano Ezequiel
Craiem, Damian
Chironi, Gilles
Graf Caride, Diego Sebastián
Macron, Laurent
Mousseaux, Elie
Simon, Alain
Armentano, Ricardo Luis
author Casciaro, Mariano Ezequiel
author_facet Casciaro, Mariano Ezequiel
Craiem, Damian
Chironi, Gilles
Graf Caride, Diego Sebastián
Macron, Laurent
Mousseaux, Elie
Simon, Alain
Armentano, Ricardo Luis
author_role author
author2 Craiem, Damian
Chironi, Gilles
Graf Caride, Diego Sebastián
Macron, Laurent
Mousseaux, Elie
Simon, Alain
Armentano, Ricardo Luis
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Principal Components
Thoracic Aorta
Computed Tomography
topic Principal Components
Thoracic Aorta
Computed Tomography
dc.description.none.fl_txt_mv Purpose: Diagnosis and management of thoracic aorta (TA) disease demand the assessment of accurate quantitative information of the aortic anatomy. We investigated the principal modes of variation in aortic 3-dimensional geometry paying particular attention to the curvilinear portion. Materials and Methods: Images were obtained from extended noncontrast multislice computed tomography scans, originally intended for coronary calcium assessment. The ascending, arch, and descending aortas of 500 asymptomatic patients (57±9 y, 81% male) were segmented using a semiautomated algorithm that sequentially inscribed circles inside the vessel cross-section. Axial planes were used for the descending aorta, whereas oblique reconstructions through a toroid path were required for the arch. Vessel centerline coordinates and the corresponding diameter values were obtained. Twelve size and shape geometric parameters were calculated to perform a principal component analysis. Results: Statistics revealed that the geometric variability of the TA was successfully explained using 3 factors that account for ∼80% of total variability. Averaged aortas were reconstructed varying each factor in 5 intervals. Analyzing the parameter loadings for each principal component, the dominant contributors were interpreted as vessel size (46%), arch unfolding (22%), and arch symmetry (12%). Variables such as age, body size, and risk factors did not substantially modify the correlation coefficients, although some particular differences were observed with sex. Conclusions: We conclude that vessel size, arch unfolding, and symmetry form the basis for characterizing the variability of TA morphology. The numerical data provided in this study as supplementary material can be exploited to accurately reconstruct the curvilinear shape of normal TAs.
Fil: Casciaro, Mariano Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Favaloro. Facultad de Ingeniería y Ciencias Exactas y Naturales; Argentina
Fil: Craiem, Damian. Universidad Favaloro. Facultad de Ingeniería y Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Chironi, Gilles. Universite de Paris V; Francia
Fil: Graf Caride, Diego Sebastián. Universidad Favaloro. Facultad de Ingeniería y Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Macron, Laurent. Universite de Paris V; Francia
Fil: Mousseaux, Elie. Universite de Paris V; Francia
Fil: Simon, Alain. Universite de Paris V; Francia
Fil: Armentano, Ricardo Luis. Universidad Favaloro. Facultad de Ingeniería y Ciencias Exactas y Naturales; Argentina
description Purpose: Diagnosis and management of thoracic aorta (TA) disease demand the assessment of accurate quantitative information of the aortic anatomy. We investigated the principal modes of variation in aortic 3-dimensional geometry paying particular attention to the curvilinear portion. Materials and Methods: Images were obtained from extended noncontrast multislice computed tomography scans, originally intended for coronary calcium assessment. The ascending, arch, and descending aortas of 500 asymptomatic patients (57±9 y, 81% male) were segmented using a semiautomated algorithm that sequentially inscribed circles inside the vessel cross-section. Axial planes were used for the descending aorta, whereas oblique reconstructions through a toroid path were required for the arch. Vessel centerline coordinates and the corresponding diameter values were obtained. Twelve size and shape geometric parameters were calculated to perform a principal component analysis. Results: Statistics revealed that the geometric variability of the TA was successfully explained using 3 factors that account for ∼80% of total variability. Averaged aortas were reconstructed varying each factor in 5 intervals. Analyzing the parameter loadings for each principal component, the dominant contributors were interpreted as vessel size (46%), arch unfolding (22%), and arch symmetry (12%). Variables such as age, body size, and risk factors did not substantially modify the correlation coefficients, although some particular differences were observed with sex. Conclusions: We conclude that vessel size, arch unfolding, and symmetry form the basis for characterizing the variability of TA morphology. The numerical data provided in this study as supplementary material can be exploited to accurately reconstruct the curvilinear shape of normal TAs.
publishDate 2014
dc.date.none.fl_str_mv 2014-07
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/28448
Casciaro, Mariano Ezequiel; Craiem, Damian; Chironi, Gilles; Graf Caride, Diego Sebastián; Macron, Laurent; et al.; Identifying the Principal Modes of Variation in Human Thoracic Aorta Morphology; Lippincott Williams; Journal of Thoracic Imaging; 29; 4; 7-2014; 224-232
0883-5993
CONICET Digital
CONICET
url http://hdl.handle.net/11336/28448
identifier_str_mv Casciaro, Mariano Ezequiel; Craiem, Damian; Chironi, Gilles; Graf Caride, Diego Sebastián; Macron, Laurent; et al.; Identifying the Principal Modes of Variation in Human Thoracic Aorta Morphology; Lippincott Williams; Journal of Thoracic Imaging; 29; 4; 7-2014; 224-232
0883-5993
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://insights.ovid.com/pubmed?pmid=24296697
info:eu-repo/semantics/altIdentifier/doi/10.1097/RTI.0000000000000060
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Lippincott Williams
publisher.none.fl_str_mv Lippincott Williams
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.22299

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