A few upstream bifurcations drive the spatial distribution of red blood cells in model microfluidic networks. Issue 7 (28th January 2022)

• Record Type: Journal Article
• Authors: Merlo, Adlan; Berg, Maxime; Duru, Paul; Risso, Frédéric; Davit, Yohan; Lorthois, Sylvie
• Is Part Of: Soft matter. Volume 18:Issue 7(2022)
• Page Start: 1463
• Page End: 1478
• Publication Date: 2022-01-28
• Subjects: Soft condensed matter -- Periodicals; 530.413
• DOI: 10.1039/d1sm01141c
• Languages: English
• ISSNs: 1744-683X

Abstract

Abstract : We show how Red Blood Cell (RBC) transverse migration downstream the first bifurcation of the network has an outsized impact on the RBC distribution at large scale, depending on the network architecture, as illustrated here for a square network. Abstract : The physics of blood flow in small vessel networks is dominated by the interactions between Red Blood Cells (RBCs), plasma and blood vessel walls. The resulting couplings between the microvessel network architecture and the heterogeneous distribution of RBCs at network-scale are still poorly understood. The main goal of this paper is to elucidate how a local effect, such as RBC partitioning at individual bifurcations, interacts with the global structure of the flow field to induce specific preferential locations of RBCs in model microfluidic networks. First, using experimental results, we demonstrate that persistent perturbations to the established hematocrit profile after diverging bifurcations may bias RBC partitioning at the next bifurcations. By performing a sensitivity analysis based upon network models of RBC flow, we show that these perturbations may propagate from bifurcation to bifurcation, leading to an outsized impact of a few crucial upstream bifurcations on the distribution of RBCs at network-scale. Based on measured hematocrit profiles, we further construct a modified RBC partitioning model that accounts for the incomplete relaxation of RBCs at these bifurcations. This model allows us to explain how the flow field results in a single pattern of RBC preferential location in some networks, while it leads to the emergence of two different patterns of RBC preferential location in others. Our findings have important implications in understanding and modeling blood flow in physiological and pathological conditions.