Characterization of Nanoparticle Dispersion in Red Blood Cell Suspension by the Lattice Boltzmann-Immersed Boundary Method

Abstract

Nanodrug-carrier delivery in the blood stream is strongly influenced by nanoparticle (NP) dispersion. This paper presents a numerical study on NP transport and dispersion in red blood cell (RBC) suspensions under shear and channel flow conditions, utilizing an immersed boundary fluid-structure interaction model with a lattice Boltzmann fluid solver, an elastic cell membrane model and a particle motion model driven by both hydrodynamic loading and Brownian dynamics. The model can capture the multiphase features of the blood flow. Simulations were performed to obtain an empirical formula to predict NP dispersion rate for a range of shear rates and cell concentrations. NP dispersion rate predictions from the formula were then compared to observations from previous experimental and numerical studies. The proposed formula is shown to accurately predict the NP dispersion rate. The simulation results also confirm previous findings that the NP dispersion rate is strongly influenced by local disturbances in the flow due to RBC motion and deformation. The proposed formula provides an efficient method for estimating the NP dispersion rate in modeling NP transport in large-scale vascular networks without explicit RBC and NP models.

Predicting different adhesive regimens of circulating particles at blood capillary walls

“…This computational tool was efficiently applied to follow the dynamics of rigid particles and deformable capsules, such us red blood cells (RBCs) and leukocytes, in whole blood capillary flow. Specifically, it was applied to finely tune the geometry and viscoelastic properties of RBCs in order to accurately replicate the rheological response of whole blood as well as to reduce computing burden (Fedosov et al 2010;Sun and Munn 2005;Kruger et al 2011), predict the clustering of RBCs and microcapsules in narrow capillaries (McWhirter et al 2009), explain the role of RBCs on the vascular rolling of leukocytes (Sun et al 2003), determine numerically the size of the cell-free layer developing next to the vessel walls (Fedosov et al 2010) and model the vascular transport of micro-/nanoparticles (Coclite et al 2016;Gekle 2016;Tan et al 2016;Basagaoglu et al 2013).…”

Modeling thermal inkjet and cell printing process using modified pseudopotential and thermal lattice Boltzmann methods

“…Similarly, the solid velocity, u ( X , t ), will be interpolated from the local fluid nodes and will be used to update solid nodes [25, 39]. …”

“…Our cell model is benchmarked with optical tweezer experimental data in our previous work [31, 39] where we studied red blood cell damage. In the same study, the deformation of RBC under pure shear flow is also investigated where the results for oscillation period agreed with experiments of Abkarian et al [40].…”

Nanoparticle transport and delivery in a heterogeneous pulmonary vasculature

“…However, to better understand how RBCs influence drug delivery in vascular tree, dispersion rate can be corrected to compensate the presence of RBCs. In our prior work (Tan et al, 2016), we have previously characterized nanoparticle dispersion in red blood cell suspension by the Lattice Boltzmann-Immersed Boundary Method. Simulations were performed to obtain an empirical formula to predict NP dispersion rate for a range of shear rates and cell concentrations.…”