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Wall Shear Stress Estimations using Semi-Automatic Segmentation
Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology.
Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
Linköping University, Department of Medicine and Health Sciences. Linköping University, Faculty of Health Sciences.
Linköping University, Department of Medicine and Health Sciences, Physiology. Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Centre, Department of Thoracic and Vascular Surgery in Östergötland.ORCID iD: 0000-0002-9095-403X
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

Atherosclerosis development is strongly believed to be influenced by hemodynamic forces such as wall shear stress (WSS). To estimate such entity in-vivo in humans, is image based computational fluid dynamics (CFD) a powerful tool. In this paper we use a combination of magnetic resonance imaging (MRI) and CFD to estimate WSS. In such method a number of steps is included. One important step is the image interpretation into 3D models, named segmentation. The choice of segmentation method can influence the resulting WSS distribution in the human aorta. This is studied by comparingWSS 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 8 healthymale volunteers. The different segmentation methods give slightly different geometrical descriptions of the human aorta. However there is a very good agreement between the resultingWSS 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 position indicating that theWSS is more sensitive to local geometry differences in these parts of the cardiac cycle. We can conclude that the results show that the semi-automatic segmentation method can be used in the future to estimate WSS with relevant accuracy.

National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:liu:diva-65906OAI: oai:DiVA.org:liu-65906DiVA: diva2:400269
Available from: 2011-02-25 Created: 2011-02-25 Last updated: 2017-03-27Bibliographically approved
In thesis
1. Towards Subject Specific Aortic Wall Shear Stress: a combined CFD and MRI approach
Open this publication in new window or tab >>Towards Subject Specific Aortic Wall Shear Stress: a combined CFD and MRI approach
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The cardiovascular system is an important part of the human body since it transports both energy and oxygen to all cells throughout the body. Diseases in this system are often dangerous and cardiovascular diseases are the number one killer in the western world. Common cardiovascular diseases are heart attack and stroke, which origins from obstructed blood flow. It is generally important to understand the causes for these cardiovascular diseases. The main causes for these diseases are atherosclerosis development in the arteries (hardening and abnormal growth). This transform of the arterial wall is believed to be influenced by the mechanical load from the flowing blood on the artery and especially the tangential force the wall shear stress. To retrieve wall shear stress information in arteries invivo is highly interesting due to the coupling to atherosclerosis and indeed a challenge. The goal of this thesis is to develop, describe and evaluate an in-vivo method for subject specific wall shear stress estimations in the human aorta, the largest artery in the human body. The method uses an image based computational fluid dynamics approach in order to estimate the wall shear stress. To retrieve in-vivo geometrical descriptions of the aorta magnetic resonance imaging capabilities is used which creates image material describing the subject specific geometry of the aorta. Magnetic resonance imaging is also used to retrieve subject specific blood velocity information in the aorta. Both aortic geometry and velocity is gained at the same time. Thereafter the image material is interpreted using level-set segmentation in order to get a three-dimensional description of the aorta. Computational fluid dynamics simulations is applied on the subject specific aorta in order to calculate time resolved wall shear stress distribution at the entire aortic wall included in the actual model.

This work shows that it is possible to estimate subject specific wall shear stress in the human aorta. The results from a group of healthy volunteers revealed that the arterial geometry is very subject specific and the different wall shear stress distributions have general similarities but the level and local distribution are clearly different. Sensitivity (on wall shear stress) to image modality, the different segmentation methods and different inlet velocity profiles have been tested, which resulted in these general conclusions:

  • The aortic diameter from magnetic resonance imaging became similar to the reference diameter measurement method.
  • The fast semi-automatic level-set segmentation method gave similar geometry and wall shear stress results when compared to a reference segmentation method.
  • Wall shear stress distribution became different when comparing a simplified uniform velocity profile inlet boundary condition with a measured velocity profile.

The method proposed in this thesis has the possibility to produce subject specific wall shear stress distribution in the human aorta. The method can be used for further medical research regarding atherosclerosis development and has the possibility for usage in clinical work.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2011. 40 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1360
National Category
Fluid Mechanics and Acoustics
Identifiers
urn:nbn:se:liu:diva-65910 (URN)978-91-7393-244-8 (ISBN)
Public defence
2011-04-12, ACAS, hus A, Campus Valla, Linköpings universitet, Linköping, 10:15 (English)
Opponent
Supervisors
Available from: 2011-02-25 Created: 2011-02-25 Last updated: 2017-03-27Bibliographically approved

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

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Applied Thermodynamics and Fluid MechanicsCenter for Medical Image Science and Visualization, CMIVThe Institute of TechnologyDepartment of Medicine and Health SciencesFaculty of Health SciencesPhysiologyDepartment of Thoracic and Vascular Surgery in Östergötland
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