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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/28448
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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 Técnicas2025-09-29T10:07:07Zoai: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:34982025-09-29 10:07:07.383CONICET 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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1844613927395131392 |
score |
13.070432 |