Statistical Dynamics of Flowing Red Blood Cells by Morphological Image Processing

Blood is a dense suspension of soft non-Brownian cells of unique importance. Physiological blood flow involves complex interactions of blood cells with each other and with the environment due to the combined effects of varying cell concentration, cell morphology, cell rheology, and confinement. We analyze these interactions using computational morphological image analysis and machine learning algorithms to quantify the non-equilibrium fluctuations of cellular velocities in a minimal, quasi-two-dimensional microfluidic setting that enables high-resolution spatio-temporal measurements of blood cell flow. In particular, we measure the effective hydrodynamic diffusivity of blood cells and analyze its relationship to macroscopic properties such as bulk flow velocity and density. We also use the effective suspension temperature to distinguish the flow of normal red blood cells and pathological sickled red blood cells and suggest that this temperature may help to characterize the propensity for stasis in Virchow's Triad of blood clotting and thrombosis.Author Summary: Viewed from a distance, flowing blood looks like a uniform fluid, but up close the cells in the blood change their position and speed somewhat heterogeneously. These individual cell movements may play a role in the physiology and pathophysiology of nutrient and gas transport, clotting, and diseases where normal processes go wrong. To characterize these random motions, we need to follow individual cells in a very crowded suspension—cells usually occupy more than one-third of the volume in blood. We have developed computer software that can separate individual cells in a crowd and track them as they flow. We use this software to analyze blood flow at the level of the cell and find new and possibly important differences between the blood from healthy patients and the blood from patients with sickle cell disease, a disorder in which blood cells become stiff and often stop flowing. We provide evidence that blood from patients with sickle cell disease shows decreased random cellular motions and suggest that this difference may provide a physical basis for the increased risk of occlusion in sickle cell disease.