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Subject-specific aortic wall shear stress estimations using semi-automatic segmentation
Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Mekanisk värmeteori och strömningslära. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Mekanisk värmeteori och strömningslära. Linköpings universitet, Tekniska högskolan.
Linköpings universitet, Institutionen för medicin och hälsa, Klinisk fysiologi. Linköpings universitet, Hälsouniversitetet.
Linköpings universitet, Institutionen för medicin och hälsa, Fysiologi. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Hjärt- och Medicincentrum, Thorax-kärlkliniken i Östergötland. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.ORCID-id: 0000-0002-9095-403X
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2012 (engelsk)Inngår i: Clinical Physiology and Functional Imaging, ISSN 1475-0961, E-ISSN 1475-097X, Vol. 32, nr 6, s. 481-491Artikkel i tidsskrift (Fagfellevurdert) 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.

sted, utgiver, år, opplag, sider
Wiley-Blackwell, 2012. Vol. 32, nr 6, s. 481-491
Emneord [en]
aortic arch, human, image-based computational fluid dynamics, magnetic resonance imaging, segmentation, wall shear stress
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-85079DOI: 10.1111/j.1475-097X.2012.01146.xISI: 000309393700010OAI: oai:DiVA.org:liu-85079DiVA, id: diva2:564637
Tilgjengelig fra: 2012-11-02 Laget: 2012-11-02 Sist oppdatert: 2017-12-07bibliografisk kontrollert

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Renner, JohanNadali Najafabadi, HosseinModin, DanielLänne, TosteKarlsson, Matts

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