A methodology to quantify the geometrical complexity of the abdominal aortic aneurysm

Research output: Contribution to journalArticle

Abstract

The abdominal aortic aneurysm (AAA) anatomy influences the technical success of the endovascular aneurysm repair (EVAR), yet very few data regarding the aortic tree angles exist in the literature. This poses great limitations in the numerical analyses of endografts, constraining their design improvement as well as the identification of their operational limitations. In this study, a matrix Φ of 10 angles was constructed for the description of the pathological region and was implemented on a large dataset of anatomies. More specifically, computed tomography angiographies from 258 patients were analysed and 10 aortic angles were calculated per case, able to adequately describe the overall AAA shape. 9 dimensional variables (i.e. diameters and lengths) were also recorded. The median and extreme values of these variables were computed providing a detailed quantification of the geometrical landscape of the AAA. Moreover, statistical analysis showed that the identified angles presented no strong correlation with each other while no lateral or anterior/posterior symmetry of the AAA was identified. These findings suggest that endograft designers are free to construct any extreme case-studies with the values provided in a mix-and-match manner. This strategy can have a powerful effect in EVAR stent graft designing, as well as EVAR planning.
LanguageEnglish
Article number17379
Number of pages12
JournalScientific Reports
Volume9
DOIs
Publication statusPublished - 22 Nov 2019

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Abdominal Aortic Aneurysm
Aneurysm
Anatomy
Stents
Transplants

Keywords

  • abdominal aortic aneurysm
  • geometry
  • angles
  • EVAR
  • modelling
  • statistical analysis
  • CTA

Cite this

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title = "A methodology to quantify the geometrical complexity of the abdominal aortic aneurysm",
abstract = "The abdominal aortic aneurysm (AAA) anatomy influences the technical success of the endovascular aneurysm repair (EVAR), yet very few data regarding the aortic tree angles exist in the literature. This poses great limitations in the numerical analyses of endografts, constraining their design improvement as well as the identification of their operational limitations. In this study, a matrix Φ of 10 angles was constructed for the description of the pathological region and was implemented on a large dataset of anatomies. More specifically, computed tomography angiographies from 258 patients were analysed and 10 aortic angles were calculated per case, able to adequately describe the overall AAA shape. 9 dimensional variables (i.e. diameters and lengths) were also recorded. The median and extreme values of these variables were computed providing a detailed quantification of the geometrical landscape of the AAA. Moreover, statistical analysis showed that the identified angles presented no strong correlation with each other while no lateral or anterior/posterior symmetry of the AAA was identified. These findings suggest that endograft designers are free to construct any extreme case-studies with the values provided in a mix-and-match manner. This strategy can have a powerful effect in EVAR stent graft designing, as well as EVAR planning.",
keywords = "abdominal aortic aneurysm, geometry, angles, EVAR, modelling, statistical analysis, CTA",
author = "Faidon Kyriakou and William Dempster and David Nash",
year = "2019",
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doi = "10.1038/s41598-019-53820-z",
language = "English",
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journal = "Scientific Reports",
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AU - Dempster, William

AU - Nash, David

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N2 - The abdominal aortic aneurysm (AAA) anatomy influences the technical success of the endovascular aneurysm repair (EVAR), yet very few data regarding the aortic tree angles exist in the literature. This poses great limitations in the numerical analyses of endografts, constraining their design improvement as well as the identification of their operational limitations. In this study, a matrix Φ of 10 angles was constructed for the description of the pathological region and was implemented on a large dataset of anatomies. More specifically, computed tomography angiographies from 258 patients were analysed and 10 aortic angles were calculated per case, able to adequately describe the overall AAA shape. 9 dimensional variables (i.e. diameters and lengths) were also recorded. The median and extreme values of these variables were computed providing a detailed quantification of the geometrical landscape of the AAA. Moreover, statistical analysis showed that the identified angles presented no strong correlation with each other while no lateral or anterior/posterior symmetry of the AAA was identified. These findings suggest that endograft designers are free to construct any extreme case-studies with the values provided in a mix-and-match manner. This strategy can have a powerful effect in EVAR stent graft designing, as well as EVAR planning.

AB - The abdominal aortic aneurysm (AAA) anatomy influences the technical success of the endovascular aneurysm repair (EVAR), yet very few data regarding the aortic tree angles exist in the literature. This poses great limitations in the numerical analyses of endografts, constraining their design improvement as well as the identification of their operational limitations. In this study, a matrix Φ of 10 angles was constructed for the description of the pathological region and was implemented on a large dataset of anatomies. More specifically, computed tomography angiographies from 258 patients were analysed and 10 aortic angles were calculated per case, able to adequately describe the overall AAA shape. 9 dimensional variables (i.e. diameters and lengths) were also recorded. The median and extreme values of these variables were computed providing a detailed quantification of the geometrical landscape of the AAA. Moreover, statistical analysis showed that the identified angles presented no strong correlation with each other while no lateral or anterior/posterior symmetry of the AAA was identified. These findings suggest that endograft designers are free to construct any extreme case-studies with the values provided in a mix-and-match manner. This strategy can have a powerful effect in EVAR stent graft designing, as well as EVAR planning.

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KW - EVAR

KW - modelling

KW - statistical analysis

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