On the relative importance of rheology for image-based CFD models of the carotid bifurcation

J Biomech Eng. 2007 Apr;129(2):273-8. doi: 10.1115/1.2540836.

Abstract

Background: Patient-specific computational fluid dynamics (CFD) models derived from medical images often require simplifying assumptions to render the simulations conceptually or computationally tractable. In this study, we investigated the sensitivity of image-based CFD models of the carotid bifurcation to assumptions regarding the blood rheology.

Method of approach: CFD simulations of three different patient-specific models were carried out assuming: a reference high-shear Newtonian viscosity, two different non-Newtonian (shear-thinning) rheology models, and Newtonian viscosities based on characteristic shear rates or, equivalently, assumed hematocrits. Sensitivity of wall shear stress (WSS) and oscillatory shear index (OSI) were contextualized with respect to the reproducibility of the reconstructed geometry, and to assumptions regarding the inlet boundary conditions.

Results: Sensitivity of WSS to the various rheological assumptions was roughly 1.0 dyn/cm(2) or 8%, nearly seven times less than that due to geometric uncertainty (6.7 dyn/cm(2) or 47%), and on the order of that due to inlet boundary condition assumptions. Similar trends were observed regarding OSI sensitivity. Rescaling the Newtonian viscosity based on time-averaged inlet shear rate served to approximate reasonably, if overestimate slightly, non-Newtonian behavior.

Conclusions: For image-based CFD simulations of the normal carotid bifurcation, the assumption of constant viscosity at a nominal hematocrit is reasonable in light of currently available levels of geometric precision, thus serving to obviate the need to acquire patient-specific rheological data.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Blood Flow Velocity / physiology*
  • Carotid Arteries / anatomy & histology*
  • Carotid Arteries / physiology*
  • Computer Simulation
  • Hematocrit
  • Humans
  • Image Interpretation, Computer-Assisted / methods*
  • Models, Cardiovascular*
  • Rheology
  • Sensitivity and Specificity
  • Shear Strength
  • Viscosity