Session ZC14: Biofluids: Small Vessels and Microcirculation II

Comparing diabetic versus healthy red blood cell partitioning at vascular bifurcations

As red blood cells (RBCs) flow through a capillary vessel bifurcation, they usually do not distribute (i.e. partition) in the downstream branches in proportion to the flow rates. Often, the branch with the higher flow fraction receives a disproportionately higher fraction of cells. Partitioning is the key mechanism of RBC distribution in microcirculation. Since RBCs are extremely deformable and their size is comparable to the diameter of a capillary vessel, such partitioning is expected to depend on the degree of deformation that each cell undergoes as it flows through a bifurcation. The deformability, shape and size of RBCs change in diabetes. Nearly no study exists comparing the partitioning behavior of diabetes versus healthy cells. In this work, a high-fidelity computational model is used to accurately resolve cellular scale hemodynamics. This allows for a direct comparison between flows of healthy and diabetic RBCs through vessels of varying diameter, hematocrit, and average plasma flow partitioning. Significant differences include situations where diabetic cells exhibit no partitioning at all while healthy cells do. This finding has physiological significance as it implies that diabetic RBCs are more heterogeneously distributed in the microcirculation than healthy cells. The effect of cell biases from downstream bifurcations, interactions with leukocytes, and influence of diabetic cells on the cell free layer are also observed.   

Experimental study of microparticle transport in blood flow in a microfluidic bifurcation channel

Transport of microparticles in the blood stream is of paramount significance for drug delivery. Blood flow in small vessels such as arterioles is known to display a segregation phenomenon called margination, where highly deformable red blood cells (RBCs) are preferentially found near the axial center of the vessel, segregating leukocytes and platelets in the near-wall region. This phenomenon is particularly important for the efficacy of targeted drug delivery in microcirculation (e.g. to tumor tissues), as the motion of drug-carriers and their distribution are strongly affected by their interactions with RBCs. We present an experimental study of the effects of hematocrit and particle concentration on RBC-particle interactions. We consider a microfluidic bifurcating channel of arteriole size, O(10) microns, in which 8-micron spheres flow along with RBCs, over a wide range of hematocrit and particle concentration. High-speed imaging and particle tracking velocimetry are leveraged to analyze the transport of RBCs and particles, up to whole-blood hematocrit levels. The results provide insights relevant to the underlying mechanisms of margination and the optimization of targeted drug delivery.   

Modeling and Simulation of Circadian Rhythm and Spatiotemporal Dynamics of Ligand-coated Particle Flow in Targeted Drug Delivery Processes

Drug delivery via nanocarriers is a multi-faceted problem that aims at achieving maximum efficacy while minimizing off-target effects and enhancing therapeutic outcomes. Drug carrying nanoparticles are tethered with peptides or antibodies binding the surface of drug encapsulating nanoparticles. Computational Fluid Dynamics (CFD) methods can provide insights into effects of circadian rhythm on the drug-nanoparticle transport, distribution, and interactions with the vascular and interstitial environments. This paper presents an advanced fluid dynamics modeling method that is based on convective transport of viscous incompressible fluid (blood), coupled with a scalar advection diffusion equation for the formation of drug concentration gradients in the transport fluid domain, and buildup of concentration at the targeted site. The method is equipped with a experimentally calibrated particle-endothelial cell adhesion model, a friction model accounting for surface roughness of endothelial cell layer, and a dispersion model for particle transport in the boundary layer. Comparisons with carefully designed microfluidic experiments show predictive capability of the mathematical model for drug transport, adhesion, and retention at the target site.   

A computational study of red blood cell trafficking in tumor/angiogenic capillary vessel networks

Capillary vessels together with arterioles, venules, and vascular junctions, form a highly complex network of narrow pathways for blood flow. Blood in such vessels flows as a dense suspension made of red blood cells (RBC) which are extremely deformable and can easily pass through capillaries less than their size. The distribution of RBCs in the vascular networks is highly heterogeneous and is critical to the healthy functioning of the body. An accurate prediction of RBC trafficking in such networks is a challenging computational problem as it requires resolving 3D deformation of each RBC in the dense suspension flowing through the complex geometry of the vascular networks. We have developed a high-fidelity 3D direct simulation method to predict flow of thousands of deformable RBCs through physiologically realistic microvascular networks comprised of many blood vessels and vascular bifurcations. The complexity of the vascular networks increases significantly in tumor and angiogenesis as characterized by the emergence of abnormal geometry, non-circular and collapsed vessels, multi-furcations, and tessellated architecture. We use in vivo images to create such vascular networks in silico and then predict RBC trafficking and capillary hemodynamics using our direct simulation. We provide quantitative differences between healthy networks and tumor/angiogenic networks in terms of RBC distribution, near-wall cell-free layer and wall shear stress.   

Margination of platelet-sized particles in red blood cell suspensions near the confluence and bifurcation of Y-shaped microchannels

Platelets are known to concentrate near the vessel wall in microvascular blood flow, a phenomenon referred to as margination or near-wall excess. However, platelet margination is expected to be impaired at the confluence of two vessels or bifurcation, and to complete again at a certain distance downstream from the confluence or bifurcation. In this study, we performed in vitro experiments to investigate these margination distances, by using fluorescent polystyrene particles of similar diameter to platelets as a platelet substitute. A confocal laser scanning microscopy was used to measure the distribution of particles suspended in the red blood cell suspension flowing through Y-shaped microchannels. In confluence channels, margination was reconstructed less than 5 mm from the confluence, while in bifurcating channels, it was reconstructed approximately 30 mm from the bifurcation point. These lengths are larger than typical microvessel lengths, suggesting that complete margination is rare in microvessels. Furthermore, it is suggested that platelet margination in venules is less pronounced than in arterioles, and platelets are distributed unevenly at each branching of arterioles.   

Predicting 3D and skewed velocity and hematocrit distributions in networks of capillary blood vessels using machine learning models

Capillary blood vessels, together with their upstream and downstream vessels known as arterioles and venules, and vascular junctions, form an intricate network. Blood in such small vessels flows as a dense suspension made of red blood cells (RBC) which are extremely deformable. The distribution of blood velocity and hematocrit (RBC concentration) over vessel cross-section is generally complex. The velocity is non-parabolic and often highly skewed. The hematocrit distribution is also radially non-uniform and skewed. A detailed and accurate knowledge of the cross-sectional velocity and hematocrit distribution is of immense physiological importance as these can provide accurate calculation of the wall shear stress and the near-wall cell-free layer. Both in vivo measurements and 1D models of network-scale blood flow have limitations in terms of such detailed information. High-fidelity simulations that treat blood as suspension of deformable RBCs can provide such information. However, such models are computationally very expensive when flow of blood cells in large vascular networks comprised of many vessels and junctions are considered. To overcome this issue, we present machine learning (ML) models that can predict cross-sectional distribution of velocity and hematocrit in large vascular networks. Predictions from our ML models show excellent agreement against the results from high-fidelity RBC-resolved simulations.   

Title: Predictions of microvascular leak from an anatomically correct mouse GI tract

Abstract:

Prior research resulted in the discovery of a novel RX protein proven to cause cell death in injected mice via hyper vasoconstriction. This project seeks to lay further groundwork for trauma research and ultimately a solution to the failure of the major organs in humans after experiencing major trauma on the battlefield or otherwise. This was achieved by creating a CAD-modeled section of the microvasculature in the GI tract of a mouse. The necessary data and images were previously attained through Electron Scanning Microscopy (ESM) analysis of the intestinal mucosa. Based on acquired blood flow and pressure data as well as measured lumen diameter response data to the RX protein, an average base pressure, flow rate and scale were chosen. This idealized model was compared to simulations in which the base values were construed by the vasoconstriction response of both venules and arterioles and an induced jejunal microvascular leak​. Then, graphical techniques related to pressure and blood flow changes provide further data for continued research in this field.

Defining the contribution of red blood cell mechanical properties to altered rheology in sickle cell disease

In sickle cell disease (SCD), polymerization of hemoglobin under deoxygenated conditions causes red blood cells (RBCs) to stiffen, resulting in aberrant blood flow. At the continuum level, deoxygenated blood in SCD exhibits increased shear-thinning and wall friction but it is not understood how the distribution of RBC properties contributes to whole-blood rheology. To this end, we developed an experimental-computational platform to probe the effect of oxygen-dependent RBC stiffness and volume fraction on blood properties. Simulations of mixed suspensions of healthy and stiff RBCs suggested that margination of stiff RBCs contributes to decreased RBC speeds near the wall and thus an increase in whole-blood wall friction. These predictions were tested experimentally using a method in which sickle RBCs were stained fluorescently and tracked in a mixture of healthy blood under deoxygenated conditions. At high stiff cell fractions, theory and experiments showed a decrease in mean RBC speed and therefore an increase in total flow resistance. Furthermore, we tested theoretically and experimentally how frictional forces between stiffened cells affect the observed blood rheology. Results from this work will advance our general understanding of particle suspension flows and help identify mechanisms that contribute to pathological blood flow in SCD.   

Red blood cell lingering modulates hematocrit distribution in the microcirculation

Understanding the distribution of red blood cells (RBCs) in the microcirculation is crucial for assessing oxygen delivery and solute transport to tissues. In this study, we investigate the influence of RBC partitioning at successive bifurcations on hematocrit heterogeneity, which refers to the volume fraction of RBCs in blood within microvessels. Traditionally, RBCs were believed to partition disproportionately based on fractional blood flow rates, resulting in predictable hematocrit distributions. However, recent investigations have revealed deviations from this expected behavior on both temporal and time-average scales.

To explore these deviations, we employed a combination of in vivo experiments and in silico simulations, focusing on the microscopic behavior of RBC lingering. We introduce a novel method to quantify the extent of cell lingering at highly confined capillary-level bifurcations, demonstrating its correlation with deviations from established empirical predictions by Pries et al. Moreover, we examine how bifurcation geometry and cell membrane rigidity influence RBC lingering. Notably, we find that rigid cells exhibit reduced lingering compared to softer ones.

Our findings emphasize the importance of considering RBC lingering as a significant mechanism in the study of microcirculatory abnormalities associated with diseases like malaria and sickle-cell disease. Additionally, this research sheds light on how pathological conditions, such as thrombosis, tumors, and aneurysms, can alter the microvascular networks. By comprehensively understanding the role of RBC lingering, we can enhance our understanding of how abnormal RBC rigidity affects microcirculatory blood flow and contribute to the development of targeted interventions for various vascular disorders.