Complex Microvascular Networks Research Articles

Temporal-spatial heterogeneity of hematocrit in microvascular networks

Hematocrit, defined as the volume percentage of red blood cells in blood, is an important indicator of human health status, which demonstrates the capability of blood to deliver oxygen. It has been studied over many decades using in vivo, in vitro, and in silico experiments, and recent studies have shown that its major feature in microvascular networks is the temporal-spatial heterogeneity. The present work is a numerical study of such temporal-spatial heterogeneity, based on direct simulations of cellular-scale blood flow in complex microvascular networks. The simulations take into account the cell deformation and aggregation and thus are able to capture both the three-dimensional dynamics of each individual cell and the temporal-spatial distribution of cell population. The results showed that the temporal-spatial heterogeneity is more pronounced in the network that has the vessels with smaller diameters or with more complex geometry. Such heterogeneity is largely attributed to the existence of bifurcations, where the positively correlated hypotactic (feeding-branch) and paratactic (branch-branch) relations are generally observed in both the time-averaged hematocrit and temporal hematocrit ranges. This suggests that the successive bifurcations have a substantial impact on the temporal-spatial heterogeneity of hematocrit. However, these positive correlations may be broken up if the diameter of the feeding vessel is small enough or the bifurcation is asymmetric extremely, due to the vessel blockage. The present study is of great clinical significance to help doctors make more accurate diagnosis and treatment, by providing more information about the temporal-spatial distribution of the hematocrit in microvascular networks.

A computational study of red blood cell deformability effect on hemodynamic alteration in capillary vessel networks

Capillary blood vessels, the smallest vessels in the body, form an intricate network with constantly bifurcating, merging and winding vessels. Red blood cells (RBCs) must navigate through such complex microvascular networks in order to maintain tissue perfusion and oxygenation. Normal, healthy RBCs are extremely deformable and able to easily flow through narrow vessels. However, RBC deformability is reduced in many pathological conditions and during blood storage. The influence of reduced cell deformability on microvascular hemodynamics is not well established. Here we use a high-fidelity, 3D computational model of blood flow that retains exact geometric details of physiologically realistic microvascular networks, and deformation of every one of nearly a thousand RBCs flowing through the networks. We predict that reduced RBC deformability alters RBC trafficking with significant and heterogeneous changes in hematocrit. We quantify such changes along with RBC partitioning and lingering at vascular bifurcations, perfusion and vascular resistance, and wall shear stress. We elucidate the cellular-scale mechanisms that cause such changes. We show that such changes arise primarily due to the altered RBC dynamics at vascular bifurcations, as well as cross-stream migration. Less deformable cells tend to linger less at majority of bifurcations increasing the fraction of RBCs entering the higher flow branches. Changes in vascular resistance also seen to be heterogeneous and correlate with hematocrit changes. Furthermore, alteration in RBC dynamics is shown to cause localized changes in wall shear stress within vessels and near vascular bifurcations. Such heterogeneous and focal changes in hemodynamics may be the cause of morphological abnormalities in capillary vessel networks as observed in several diseases.

In vivo imaging of hemodynamic redistribution and arteriogenesis across microvascular network.

Arteriogenesis is an important mechanism that contributes to restoration of oxygen supply in chronically ischemic tissues, but remains incompletely understood due to technical limitations. This study presents a novel approach for comprehensive assessment of the remodeling pattern in a complex microvascular network containing multiple collateral microvessels. We have developed a hardware-software integrated platform for quantitative, longitudinal, and label-free imaging of network-wide hemodynamic changes and arteriogenesis at the single-vessel level. By ligating feeding arteries in the mouse ear, we induced network-wide hemodynamic redistribution and localized arteriogenesis. The utility of this technology was demonstrated by studying the influence of obesity on microvascular arteriogenesis. Simultaneously monitoring the remodeling of competing collateral arterioles revealed a new, inverse relationship between initial vascular resistance and extent of arteriogenesis. Obese mice exhibited similar remodeling responses to lean mice through the first week, including diameter increase and flow upregulation in collateral arterioles. However, these gains were subsequently lost in obese mice. Capable of label-free, comprehensive, and dynamic quantification of structural and functional changes in the microvascular network in vivo, this platform opens up new opportunities to study the mechanisms of microvascular arteriogenesis, its implications in diseases, and approaches to pharmacologically rectify microvascular dysfunction.

Microvascularity detection and quantification in glioma: a novel deep-learning-based framework

Microvascularity is highly correlated with the grading and subtyping of gliomas, making this one of its most important histological features. Accurate quantitative analysis of microvessels is helpful for the development of a targeted therapy for antiangiogenesis. The deep-learning algorithm is by far the most effective segmentation and detection model and enables location and recognition of complex microvascular networks in large images obtained from hematoxylin and eosin (H&E) stained specimens. We proposed an automated deep-learning-based method to detect and quantify the microvascularity in glioma and applied it to comprehensive clinical analyses. A total of 350 glioma patients were enrolled in our study, for which digitalized imaging of H&E stained slides were reviewed, molecular diagnosis was performed and follow-up was investigated. The microvascular features were compared according to their histologic types, molecular types, and patients' prognosis. The results show that the proposed method can quantify microvascular characteristics automatically and effectively. Significant increases of microvascular density and microvascular area were observed in glioblastomas (95% p < 0.001 in density, 170% p < 0.001 in area) in comparison with other histologic types; increases were also observed in cases with TERT-mut only (68% p < 0.001 in density, 54% p < 0.001 in area) compared with other molecular types. Survival analysis showed that microvascular features can be used to cluster cases into two groups with different survival periods (hazard ratio [HR] 2.843, log-rank <0.001), which indicates the quantified microvascular features may potentially be alternative signatures for revealing patients' prognosis. This deep-learning-based method may be a useful tool in routine clinical practice for precise diagnosis and antiangiogenic treatment.

Leaf-Inspired Authentically Complex Microvascular Networks for Deciphering Biological Transport Process.

The vascular transport of molecules, cells, and nanoconstructs is a fundamental biophysical process impacting tissue regeneration, delivery of nutrients and therapeutic agents, and the response of the immune system to external pathogens. This process is often studied in single-channel microfluidic devices lacking the complex tridimensional organization of vascular networks. Here, soft lithography is employed to replicate the vein system of a Hedera elix leaf on a polydimethilsiloxane (PDMS) template. The replica is then sealed and connected to an external pumping system to realize an authentically complex microvascular network. This satisfies energy minimization criteria by Murray's law and comprises a network of channels ranging in size from capillaries (∼50 μm) to large arterioles and venules (∼400 μm). Micro-PIV (micro-particle image velocimetry) analysis is employed to characterize flow conditions in terms of streamlines, fluid velocity, and flow rates. To demonstrate the ability to reproduce physiologically relevant transport processes, two different applications are demonstrated: vascular deposition of tumor cells and lysis of blood clots. To this end, conditions are identified to culture cells within the microvasculature and realize a confluent endothelial monolayer. Then, the vascular deposition of circulating breast (MDA-MB 231) cancer cells is documented throughout the network under physiologically relevant flow conditions. Firm cell adhesion mostly occurs in channels with low mean blood velocity. As a second application, blood clots are formed within the chip by mixing whole blood with a thrombin solution. After demonstrating the blood clot stability, tissue plasminogen activator (tPA) and tPA-carrying nanoconstructs (tPA-DPNs) are employed as thrombolytics. In agreement with previous data, clot dissolution is equally induced by tPA and tPA-DPNs. The proposed leaf-inspired chip can be efficiently used to study a variety of vascular transport processes in complex microvascular networks, where geometry and flow conditions can be modulated and monitored throughout the experimental campaign.

High‐fidelity Modeling of Blood Flow in Physiologically Realistic Microvascular Networks

High-fidelity in silico modeling of blood flow in microvascular networks continues to be a challenge. Blood in small vessels behaves as a concentrated suspension of red blood cells (RBC), which are extremely deformable. Computational modeling must resolve the dynamics and deformation of individual RBC while simultaneously extending to a dense suspension. Most cellular-scale in silico models to date have considered blood flow in simple geometries, such as straight tubes or channels, which do not represent physiological conditions, since the architecture of vascular networks in vivo is characterized by bifurcating, merging, and winding vessels. Such geometrical differences result in significant deviations in hemodynamics between that achieved in a straight conduit versus a vascular network. We have recently developed a high-fidelity, multiscale, 3D computational model of flow of deformable RBCs in complex microvascular networks resembling in vivo-like architectures. The vascular networks are designed following in vivo images and data, and are comprised of bifurcating, merging, and tortuous vessels. Our model accurately resolves the large deformation and dynamics of each individual RBC, while simultaneously retaining complex geometric details of the vascular architecture. The model is versatile, and can consider networks irrespective of topological/geometrical complexities. Flow can be driven by either pressure or flow boundary conditions of physiological values. Cell distributions naturally develop in the networks from an initial random distribution, eventually resulting in a heterogeneous cell distribution as observed in vivo. Extreme deformation and a wide range of RBC shapes are observed that are in agreement with in vivo observations. Quantitative comparisons were made with in vivo data using hemodynamic quantities such as flow resistance, wall shear stress, cell-free layer, etc., and good agreement was observed. The model can also consider white blood cells and platelets, and receptor-mediated adhesion between vascular wall and cells. The model provides a full 3D quantification of hemodynamic quantities with unprecedented details that are not available in experimental measurements. For example, the model allows full 3D characterizations of the near-wall cell-free layer (CFL) and wall shear stress (WSS) and gradients (WSSG). It predicts that CFL becomes more asymmetric along vessel lengths with increasing vessel tortuosity. While WSS itself decreases from arterial to venous sides, the model predicts that WSS in presence of RBCs increases more than that without RBCs on the venous sides and at capillary bifurcations. This implies that the effect of RBCs on WSS is more enhanced at specific locations in a microvascular network. WSSG is also predicted to be much higher in presence of the RBCs, and increase at capillary bifurcations. The model is used further to study transport and deposition of nanoparticle drug carriers in the microvasculature. Results show that nanoparticle accumulation is highly nonuniform across the vasculature with the highest accumulation occurring in bifurcations and the lowest in venules. Support or Funding Information Supported by the National Science Foundation In silico model of flow of blood cells in a microvascular network. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Modeling of pulsatile flow-dependent nitric oxide regulation in a realistic microvascular network

Hemodynamic pulsatility has been reported to regulate microcirculatory function. To quantitatively assess the impact of flow pulsatility on the microvasculature, a mathematical model was first developed to simulate the regulation of NO production by pulsatile flow in the microcirculation. Shear stress and pressure pulsatility were selected as regulators of endothelial NO production and NO-dependent vessel dilation as feedback to control microvascular hemodynamics. The model was then applied to a real microvascular network of the rat mesentery consisting of 546 microvessels. As compared to steady flow conditions, pulsatile flow increased the average NO concentration in arterioles from 256.8±93.1nM to 274.8±101.1nM (P<0.001), with a corresponding increase in vessel dilation by approximately 7% from 27.5±10.6% to 29.4±11.4% (P<0.001). In contrast, NO concentration and vessel size showed a far lesser increase (about 1.7%) in venules under pulsatile flow as compared to steady flow conditions. Network perfusion and flow heterogeneity were improved under pulsatile flow conditions, and vasodilation within the network was more sensitive to heart rate changes than pulse pressure amplitude. The proposed model simulates the role of flow pulsatility in the regulation of a complex microvascular network in terms of NO concentration and hemodynamics under varied physiological conditions.

Three-dimensional reconstruction of a vascular network by dynamic tracking of magnetite nanoparticles.

Visualization of small blood vessels feeding tumor sites provides important information on the tumors and their microenvironment. This information plays an important role in targeted drug therapies using magnetic gradients. However, capabilities of current clinical imaging modalities may be insufficient to resolve complex microvascular networks. The purpose of this study is to map the vascular network, 3D, based on the magnetic susceptibility contrast. Magnetic particles induce an inhomogeneity in the MRI's magnetic field in an order much larger than their real size. This is an approach to compensate the spatial resolution insufficiency of a clinical MR scanner. Micron-sized agglomerations of magnetite nanoparticles were injected in a 3D phantom vascular network, and a fast multislice, multiacquisition MR sequence was applied to track the agglomerations along their trajectories. The experiment was performed twice for two different imaging planes: coronal and transversal. The susceptibility artifact in the images indicated the presence and the position of the agglomerations. The calculated positions through multiple images were assembled to build up the 3D distribution of the vascular network. The calculated points were compared with the centerline of the channels, extracted from the 3D reference image, to determine the absolute measurement error. The mean error was measured to be approximately half of the pixel's size. It was found that the positioning error on the axis perpendicular to the imaging slice was nearly twice as high as on the imaging plane axes due to the slice thickness. In order to compensate for the lack of resolution on the perpendicular axis, the reconstruction was performed using a combination of coronal and transversal data. The combination of the coordinates led to a significant decrease in the mean measurement error at each segment in the vascular network (p < 0.001). A method for 3D reconstruction of a microvascular network based on the susceptibility contrast in MRI and using a clinical scanner and a commercial receiver coil was proposed. The method presents a novel approach for reconstruction of vascular networks using the susceptibility effect. The proposed method may be applied to resolve vascular networks at a micrometric scale.

A One-Dimensional Mathematical Model for Studying the Pulsatile Flow in Microvascular Networks

Techniques that model microvascular hemodynamics have been developed for decades. While the physiological significance of pressure pulsatility is acknowledged, most of the microcirculatory models use steady flow approaches. To theoretically study the extent and transmission of pulsatility in microcirculation, dynamic models need to be developed. In this paper, we present a one-dimensional model to describe the dynamic behavior of microvascular blood flow. The model is applied to a microvascular network from a rat mesentery. Intravital microscopy was used to record the morphology and flow velocities in individual vessel segments, and boundaries are defined according to the experimental data. The system of governing equations constituting the model is solved numerically using the discontinuous Galerkin method. An implicit integration scheme is adopted to increase computing efficiency. The model allows the simulation of the dynamic properties of blood flow in microcirculatory networks, including the pressure pulsatility (quantified by a pulsatility index) and pulse wave velocity (PWV). From the main input arteriole to the main output venule, the pulsatility index decreases by 66.7%. PWV obtained along arterioles declines with decreasing diameters, with mean values of 77.16, 25.31, and 8.30 cm/s for diameters of 26.84, 17.46, and 13.33 μm, respectively. These results suggest that the 1D model developed is able to simulate the characteristics of pressure pulsatility and wave propagation in complex microvascular networks.

QUANTIFICATION OF ANGIOGENESIS ON THE RAT AORTIC RING ASSAY

Image analysis is used to quantify angiogenesis on the rat aortic ring model. This technique allows to determine: (1) the aortic ring area and factor shape; (2) the number of microvessels, the total number of branching, the maximal microvessel length and the number of microvessels in function of the distance to the aortic ring; (3) the total number of isolated fibroblast-like cells and the number of fibroblast-like cells in function of the distance to the aortic ring. We show that this method is suitable to quantify spontaneous angiogenesis as well as to analyse a complex microvascular network induced by vascular endothelial growth factor (VEGF).

Comprehensive in vivo micro-vascular imaging of the human eye by dual-beam-scan Doppler optical coherence angiography

Comprehensive angiography provides insight into the diagnosis of vascular-related diseases. However, complex microvascular networks of unstable in vivo organs such as the eye require micron-scale resolution in three dimensions and a high sampling rate to access a wide area as maintaining the high resolution. Here, we introduce dual-beam-scan Doppler optical coherence angiography (OCA) as a label-free comprehensive ophthalmic angiography that satisfies theses requirements. In addition to high resolution and high imaging speed, high sensitivity to motion for detecting tiny blood flow of microvessels is achieved by detecting two time-delayed signals with scanning of two probing beams separated on a sample. We present in vivo three-dimensional imaging of the microvasculature of the posterior part of the human eye. The demonstrated results show that this technique may be used for comprehensive ophthalmic angiography to evaluate the vasculature of the posterior human eye and to diagnose variety of vascular diseases.

Improved quantification of angiogenesis in the rat aortic ring assay.

In vitro angiogenesis assays are essential for the identification of potential angiogenic agents and screening for pharmacological inhibitors. Among these assays, the rat aortic ring model developed by Nicosia bridges the gap between in vivo and in vitro models. The quantification of angiogenesis on this system must be applicable to characterise vascular networks of various states of complexity. We present here an improved computer-assisted image analysis which allows: (1) the determination of the aortic ring area and its factor shape; (2) the number of microvessels, the total number of branchings, the maximal microvessel length and the microvessel distribution; (3) the total number of isolated fibroblast-like cells and their distribution. We show that this method is suitable to quantify spontaneous angiogenesis as well as to analyse a complex microvascular network induced by various concentrations of vascular endothelial growth factor (VEGF). In addition, by evaluating a new parameter, the fibroblast-like cell distribution, our results show that: (1) during spontaneous angiogenic response, maximal fibroblast-like cell migration delimits microvascular outgrowth; and (2) the known angiogenic inhibitor Batimastat prevents endothelial cell sprouting without completely blocking fibroblast-like cell migration. Finally, this new method of quantification is of great interest to better understand angiogenesis and to test pro- or anti-angiogenic agents.

The quantitative estimation of microvessels in microvascular networks

A novel method is presented that greatly facilitates the determination of vessel segment number and density in both simple and complex microvascular networks. This approach was applied to microvascular networks represented by the Bra-Ket operator technique and accurately predicted the number of vessel segments in both tree-branched and loop-branched (arcade) networks. The method was then applied to the complex hexagonal array network described by Engelson et al. for gastrointestinal mucosa and accurately yielded an average vessel segment number of three around each hexagonal loop. This new method may be used for conveniently estimating tissue microvascular densities, such as vessel rarefaction or proliferation, and for the modelling of microvascular networks.