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Assessment of Turbulent Flow Effects on the Vessel Wall Using Four-Dimensional Flow MRI
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences.ORCID iD: 0000-0001-9184-9234
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences.ORCID iD: 0000-0003-1942-7699
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0003-1395-8296
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
2017 (English)In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 77, no 6, p. 2310-2319Article in journal (Refereed) Published
Abstract [en]

Purpose: To explore the use of MR-estimated turbulence quantities for the assessment of turbulent flow effects on the vessel wall. Methods: Numerical velocity data for two patient-derived models was obtained using computational fluid dynamics (CFD) for two physiological flow rates. The four-dimensional (4D) Flow MRI measurements were simulated at three different spatial resolutions and used to investigate the estimation of turbulent wall shear stress (tWSS) using the intravoxel standard deviation (IVSD) of velocity and turbulent kinetic energy (TKE) estimated near the vessel wall. Results: Accurate estimation of tWSS using the IVSD is limited by the spatial resolution achievable with 4D Flow MRI. TKE, estimated near the wall, has a strong linear relationship to the tWSS (mean R(2=)0.84). Near-wall TKE estimates from MR simulations have good agreement to CFD-derived ground truth (mean R-2=0.90). Maps of near-wall TKE have strong visual correspondence to tWSS. Conclusion: Near-wall estimation of TKE permits assessment of relative maps of tWSS, but direct estimation of tWSS is challenging due to limitations in spatial resolution. Assessment of tWSS and near-wall TKE may open new avenues for analysis of different pathologies. (C) 2016 International Society for Magnetic Resonance in Medicine

Place, publisher, year, edition, pages
WILEY , 2017. Vol. 77, no 6, p. 2310-2319
Keywords [en]
phase contrast magnetic resonance imaging; wall shear stress; turbulence; turbulent kinetic energy; aorta
National Category
Medical Image Processing
Identifiers
URN: urn:nbn:se:liu:diva-138232DOI: 10.1002/mrm.26308ISI: 000401270900022PubMedID: 27350049OAI: oai:DiVA.org:liu-138232DiVA, id: diva2:1109393
Note

Funding Agencies|Swedish Research Council; National Supercomputer Centre [SNIC2014-11-22]

Available from: 2017-06-14 Created: 2017-06-14 Last updated: 2019-04-17
In thesis
1. Improving Assessments of Hemodynamics and Vascular Disease
Open this publication in new window or tab >>Improving Assessments of Hemodynamics and Vascular Disease
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Blood vessels are more than simple pipes, passively enabling blood to pass through them. Their form and function are dynamic, changing with both aging and disease. This process involves a feedback loop wherein changes to the shape of a blood vessel affect the hemodynamics, causing yet more structural adaptation. This feedback loop is driven in part by the hemodynamic forces generated by the blood flow, and the distribution and strength of these forces appear to play a role in the initiation, progression, severity, and the outcome of vascular diseases.

Magnetic Resonance Imaging (MRI) offers a unique platform for investigating both the form and function of the vascular system. The form of the vascular system can be examined using MR-based angiography, to generate detailed geometric analyses, or through quantitative techniques for measuring the composition of the vessel wall and atherosclerotic plaques. To complement these analyses, 4D Flow MRI can be used to quantify the functional aspect of the vascular system, by generating a full time-resolved three-dimensional velocity field that represents the blood flow.

This thesis aims to develop and evaluate new methods for assessing vascular disease using novel hemodynamic markers generated from 4D Flow MRI and quantitative MRI data towards the larger goal of a more comprehensive non-invasive examination oriented towards vascular disease. In Paper I, we developed and evaluated techniques to quantify flow stasis in abdominal aortic aneurysms to measure this under-explored aspect of aneurysmal hemodynamics. In Paper II, the distribution and intensity of turbulence in the aorta was quantified in both younger and older men to understand how aging changes this aspect of hemodynamics. A method to quantify the stresses generated by turbulence that act on the vessel wall was developed and evaluated using simulated flow data in Paper III, and in Paper V this method was utilized to examine the wall stresses of the carotid artery. The hemodynamics of vascular disease cannot be uncoupled from the anatomical changes the vessel wall undergoes, and therefore Paper IV developed and evaluated a semi-automatic method for quantifying several aspects of vessel wall composition. These developments, taken together, help generate more valuable information from imaging data, and can be pooled together with other methods to form a more comprehensive non-invasive examination for vascular disease.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2019. p. 64
Series
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1675
National Category
Medical Image Processing Biomedical Laboratory Science/Technology
Identifiers
urn:nbn:se:liu:diva-156311 (URN)10.3384/diss.diva-156311 (DOI)9789176850985 (ISBN)
Public defence
2019-05-31, Hugo Theorell, Norra Entrén, Campus US, Linköping, 13:00 (English)
Opponent
Supervisors
Funder
Swedish Research Council, 2013-06077Swedish Research Council, 2017-03857Region Östergötland, LIO-752951
Available from: 2019-04-17 Created: 2019-04-12 Last updated: 2019-04-24Bibliographically approved

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Ziegler, MagnusLantz, JonasEbbers, TinoDyverfeldt, Petter
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Division of Cardiovascular MedicineFaculty of Medicine and Health SciencesDepartment of Clinical Physiology in LinköpingCenter for Medical Image Science and Visualization (CMIV)
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