Affiliation:
1. Department of Mechanical and Industrial Engineering New Jersey Institute of Technology Newark New Jersey USA
2. J. Crayton Pruitt Family Department of Biomedical Engineering University of Florida Gainesville Florida USA
Abstract
ABSTRACTObjectiveTortuous microvessels are characteristic of microvascular remodeling associated with numerous physiological and pathological scenarios. Three‐dimensional (3D) hemodynamics in tortuous microvessels influenced by red blood cells (RBCs), however, are largely unknown, and important questions remain. Is blood viscosity influenced by vessel tortuosity? How do RBC dynamics affect wall shear stress (WSS) patterns and the near‐wall cell‐free layer (CFL) over a range of conditions? The objective of this work was to parameterize hemodynamic characteristics unique to a tortuous microvessel.MethodsRBC‐resolved simulations were performed using an immersed boundary method‐based 3D fluid dynamics solver. A representative tortuous microvessel was selected from a stimulated angiogenic network obtained from imaging of the rat mesentery and digitally reconstructed for the simulations. The representative microvessel was a venule with a diameter of approximately 20 μm. The model assumes a constant diameter along the vessel length and does not consider variations due to endothelial cell shapes or the endothelial surface layer.ResultsMicrovessel tortuosity was observed to increase blood apparent viscosity compared to a straight tube by up to 26%. WSS spatial variations in high curvature regions reached 23.6 dyne/cm2 over the vessel cross‐section. The magnitudes of WSS and CFL thickness variations due to tortuosity were strongly influenced by shear rate and negligibly influenced by tube hematocrit levels.ConclusionsNew findings from this work reveal unique tortuosity‐dependent hemodynamic characteristics over a range of conditions. The results provide new thought‐provoking information to better understand the contribution of tortuous vessels in physiological and pathological processes and help improve reduced‐order models.
Funder
National Science Foundation
National Institutes of Health
Cited by
1 articles.
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