Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Subject-specific aortic wall shear stress estimations using semi-automatic segmentation
Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences.
Linköping University, Department of Medical and Health Sciences, Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Thoracic and Vascular Surgery. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0002-9095-403X
Show others and affiliations
2012 (English)In: Clinical Physiology and Functional Imaging, ISSN 1475-0961, E-ISSN 1475-097X, Vol. 32, no 6, 481-491 p.Article in journal (Refereed) Published
Abstract [en]

Atherosclerosis development is strongly believed to be influenced by hemodynamic forces such as wall shear stress (WSS). To estimate such an entity in-vivo in humans, image-based computational fluid dynamics (CFD) is a useful tool. In this study, we use a combination of magnetic resonance imaging (MRI) and CFD to estimate WSS. In such method, a number of steps are included. One important step is the interpretation of images into 3D models, named segmentation. The choice of segmentation method can influence the resulting WSS distribution in the human aorta. This is studied by comparing WSS results gained from the use of two different segmentation approaches: manual and semi-automatic, where the manual approach is considered to be the reference method. The investigation is performed on a group of eight healthy male volunteers. The different segmentation methods give slightly different geometrical depictions of the human aorta (difference in the mean thoracic Aorta lumen diameter were 0.7% Pandlt;0.86). However, there is a very good agreement between the resulting WSS distribution for the two segmentation approaches. The small differences in WSS between the methods increase in the late systole and early diastolic cardiac cycle time point indicating that the WSS is more sensitive to local geometric differences in these parts of the cardiac cycle (correlation coefficient is 0.96 at peak systole and 0.68 at early diastole). We can conclude that the results show that the semi-automatic segmentation method can be used in future to estimate relevant aortic WSS.

Place, publisher, year, edition, pages
Wiley-Blackwell, 2012. Vol. 32, no 6, 481-491 p.
Keyword [en]
aortic arch, human, image-based computational fluid dynamics, magnetic resonance imaging, segmentation, wall shear stress
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:liu:diva-85079DOI: 10.1111/j.1475-097X.2012.01146.xISI: 000309393700010OAI: oai:DiVA.org:liu-85079DiVA: diva2:564637
Available from: 2012-11-02 Created: 2012-11-02 Last updated: 2017-12-07Bibliographically approved

Open Access in DiVA

fulltext(596 kB)392 downloads
File information
File name FULLTEXT01.pdfFile size 596 kBChecksum SHA-512
928dbe4b06496fcf78a7bea4b920724cbca6b5ed264458189d01d5a53f94801c8ad921093e7bbf9f8cfb3070bf73968698661783a414a44b0e4171dc14aeaf72
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Search in DiVA

By author/editor
Renner, JohanNadali Najafabadi, HosseinModin, DanielLänne, TosteKarlsson, Matts
By organisation
Applied Thermodynamics and Fluid MechanicsThe Institute of TechnologyCenter for Medical Image Science and Visualization (CMIV)Clinical PhysiologyFaculty of Health SciencesPhysiologyDepartment of Thoracic and Vascular Surgery
In the same journal
Clinical Physiology and Functional Imaging
Medical and Health Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 392 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 355 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf