Identifying the principal modes of variation in human thoracic aorta morphology
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 M...
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todo:paper_08835993_v29_n4_p224_Casciaro2023-10-03T15:40:33Z Identifying the principal modes of variation in human thoracic aorta morphology Casciaro, M.E. Craiem, D. Chironi, G. Graf, S. Macron, L. Mousseaux, E. Simon, A. Armentano, R.L. 3-dimensional arterial modeling Aortic arch Noncontrast multislice computed tomography Principal component analysis calcium adult aged aorta arch aorta disease article ascending aorta descending aorta female geometry human major clinical study male morphology multidetector computed tomography principal component analysis risk factor thoracic aorta algorithm aorta disease body surface image processing middle aged pathology radiography retrospective study thoracic aorta very elderly Adult Aged Aged, 80 and over Algorithms Aorta, Thoracic Aortic Diseases Body Surface Area Female Humans Image Processing, Computer-Assisted Male Middle Aged Multidetector Computed Tomography Principal Component Analysis Retrospective Studies 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. Copyright © 2014 by Lippincott Williams & Wilkins. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_08835993_v29_n4_p224_Casciaro |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
3-dimensional arterial modeling Aortic arch Noncontrast multislice computed tomography Principal component analysis calcium adult aged aorta arch aorta disease article ascending aorta descending aorta female geometry human major clinical study male morphology multidetector computed tomography principal component analysis risk factor thoracic aorta algorithm aorta disease body surface image processing middle aged pathology radiography retrospective study thoracic aorta very elderly Adult Aged Aged, 80 and over Algorithms Aorta, Thoracic Aortic Diseases Body Surface Area Female Humans Image Processing, Computer-Assisted Male Middle Aged Multidetector Computed Tomography Principal Component Analysis Retrospective Studies |
| spellingShingle |
3-dimensional arterial modeling Aortic arch Noncontrast multislice computed tomography Principal component analysis calcium adult aged aorta arch aorta disease article ascending aorta descending aorta female geometry human major clinical study male morphology multidetector computed tomography principal component analysis risk factor thoracic aorta algorithm aorta disease body surface image processing middle aged pathology radiography retrospective study thoracic aorta very elderly Adult Aged Aged, 80 and over Algorithms Aorta, Thoracic Aortic Diseases Body Surface Area Female Humans Image Processing, Computer-Assisted Male Middle Aged Multidetector Computed Tomography Principal Component Analysis Retrospective Studies Casciaro, M.E. Craiem, D. Chironi, G. Graf, S. Macron, L. Mousseaux, E. Simon, A. Armentano, R.L. Identifying the principal modes of variation in human thoracic aorta morphology |
| topic_facet |
3-dimensional arterial modeling Aortic arch Noncontrast multislice computed tomography Principal component analysis calcium adult aged aorta arch aorta disease article ascending aorta descending aorta female geometry human major clinical study male morphology multidetector computed tomography principal component analysis risk factor thoracic aorta algorithm aorta disease body surface image processing middle aged pathology radiography retrospective study thoracic aorta very elderly Adult Aged Aged, 80 and over Algorithms Aorta, Thoracic Aortic Diseases Body Surface Area Female Humans Image Processing, Computer-Assisted Male Middle Aged Multidetector Computed Tomography Principal Component Analysis Retrospective Studies |
| 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. Copyright © 2014 by Lippincott Williams & Wilkins. |
| format |
JOUR |
| author |
Casciaro, M.E. Craiem, D. Chironi, G. Graf, S. Macron, L. Mousseaux, E. Simon, A. Armentano, R.L. |
| author_facet |
Casciaro, M.E. Craiem, D. Chironi, G. Graf, S. Macron, L. Mousseaux, E. Simon, A. Armentano, R.L. |
| author_sort |
Casciaro, M.E. |
| title |
Identifying the principal modes of variation in human thoracic aorta morphology |
| 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 |
| url |
http://hdl.handle.net/20.500.12110/paper_08835993_v29_n4_p224_Casciaro |
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