Wall shear stress exposure time: a Lagrangian measure of near-wall stagnation and concentration in cardiovascular flows View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-06

AUTHORS

Amirhossein Arzani, Alberto M. Gambaruto, Guoning Chen, Shawn C. Shadden

ABSTRACT

Near-wall transport is of utmost importance in connecting blood flow mechanics with cardiovascular disease progression. The near-wall region is the interface for biologic and pathophysiologic processes such as thrombosis and atherosclerosis. Most computational and experimental investigations of blood flow implicitly or explicitly seek to quantify hemodynamics at the vessel wall (or lumen surface), with wall shear stress (WSS) quantities being the most common descriptors. Most WSS measures are meant to quantify the frictional force of blood flow on the vessel lumen. However, WSS also provides an approximation to the near-wall blood flow velocity. We herein leverage this fact to compute a wall shear stress exposure time (WSSET) measure that is derived from Lagrangian processing of the WSS vector field. We compare WSSET against the more common relative residence time (RRT) measure, as well as a WSS divergence measure, in several applications where hemodynamics are known to be important to disease progression. Because these measures seek to quantify near-wall transport and because near-wall transport is important in several cardiovascular pathologies, surface concentration computed from a continuum transport model is used as a reference. The results show that compared to RRT, WSSET is able to better approximate the locations of near-wall stagnation and concentration build-up of chemical species, particularly in complex flows. For example, the correlation to surface concentration increased on average from 0.51 (RRT) to 0.79 (WSSET) in abdominal aortic aneurysm flow. Because WSSET considers integrated transport behavior, it can be more suitable in regions of complex hemodynamics that are traditionally difficult to quantify, yet encountered in many disease scenarios. More... »

PAGES

787-803

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10237-016-0853-7

DOI

http://dx.doi.org/10.1007/s10237-016-0853-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1012481884

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/27858174


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