Structure and hemodynamics of microvascular networks: heterogeneity and correlations

Pries, Axel R.; Secomb, Timothy W.; Gaehtgens, P.

doi:10.1152/ajpheart.1995.269.5.h1713

Cited by 118 publications

(167 citation statements)

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“…Second, we also found that topological organization strongly determined the blood pressure distribution as found previously in the rat mesentery (Pries et al, 1995). The pressure drops by 40% between its pial value and the capillary one.…”

Section: Discussionsupporting

confidence: 84%

“…We investigated both the spatial and the topological distribution of the blood pressure inside the cortex, as these considerations have been previously found to be of importance in mesentery networks (Pries et al, 1995(Pries et al, , 1996. First, we found that the blood perfusion very rapidly became uniform inside the gray matter depth, where various cellular layers are present.…”

Section: Discussionmentioning

confidence: 93%

“…Our method is applied to primate cortical brain microvascular networks whose structure has been exhaustively analyzed (Risser et al, 2007(Risser et al, , 2009. Moreover, the present work aims at determining how the network topology and geometry influence the pressure, hematocrit, and flow distributions in the cerebral microvascular circulation, as what has been shown in mesentery (Pries et al, 1995(Pries et al, , 1996.…”

Section: Introductionmentioning

confidence: 99%

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Cerebral Blood Flow Modeling in Primate Cortex

Guibert

Fonta

Plouraboué

2010

J Cereb Blood Flow Metab

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We report new results on blood flow modeling over large volumes of cortical gray matter of primate brain. We propose a network method for computing the blood flow, which handles realistic boundary conditions, complex vessel shapes, and complex nonlinear blood rheology. From a detailed comparison of the available models for the blood flow rheology and the phase separation effect, we are able to derive important new results on the impact of network structure on blood pressure, hematocrit, and flow distributions. Our findings show that the network geometry (vessel shapes and diameters), the boundary conditions associated with the arterial inputs and venous outputs, and the effective viscosity of the blood are essential components in the flow distribution. In contrast, we show that the phase separation effect has a minor function in the global microvascular hemodynamic behavior. The behavior of the pressure, hematocrit, and blood flow distributions within the network are described through the depth of the primate cerebral cortex and are discussed.

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Section: Discussionsupporting

confidence: 84%

Section: Discussionmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

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Cerebral Blood Flow Modeling in Primate Cortex

Guibert

Fonta

Plouraboué

2010

J Cereb Blood Flow Metab

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“…A pressure-driven pump system with a flow controller (Fluigent, Villejuif, France) was used to pump each solution through the microfluidic device at a physiologically relevant average velocity of 1 mm/s (44)(45)(46)(47). This velocity corresponds to a volumetric flow rate of 0.24 mL/min and an apparent wall shear rate of 61 s À1 for our channel dimensions.…”

Section: Methodsmentioning

confidence: 99%

Direct Tracking of Particles and Quantification of Margination in Blood Flow

Carboni

Bognet

Bouchillon

et al. 2016

Biophysical Journal

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Margination refers to the migration of particles toward blood vessel walls during blood flow. Understanding the mechanisms that lead to margination will aid in tailoring the attributes of drug-carrying particles for effective drug delivery. Most previous studies evaluated the margination propensity of these particles via an adhesion mechanism, i.e., by measuring the number of particles that adhered to the channel wall. Although particle adhesion and margination are related, adhesion also depends on other factors. In this study, we quantified the margination propensity of particles of varying diameters (0.53, 0.84, and 2.11 mm) and apparent wall shear rates (30, 61, and 121 s À1 ) by directly tracking fluorescent particles flowing through a microfluidic channel. The margination parameter, M, is defined as the total number of particles found within the cell-free layers normalized by the total number of particles that passed through the channel. In this study, an M-value of 0.2 indicated no margination, which was observed for all particle sizes in water. In the case of blood, larger particles were found to have higher M-values and thus marginated more effectively than smaller particles. The corresponding M-values at the device outlet were 0.203, 0.223, and 0.285 for 0.53-, 0.84-, and 2.11-mm particles, respectively. At the inlet, the M-values for all particle sizes in blood were <0.2, suggesting that non-fully-developed flow and constriction may lead to demargination. For particle velocities transverse to the flow direction (v y ), all particle sizes showed a larger standard deviation of v y as well as a higher effective diffusivity when the particles were suspended in blood relative to water. These higher values are attributed to collisions between the blood cells and particles, further supporting recent simulation results. In terms of flow rates, for a given particle size, the higher the flow rate, the higher the M-value.

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“…The viscosity is dependent on the diameter of the vessel as determined in the rat mesentery vasculature by Pries et al [9], assuming constant systemic hematocrit of 45%:…”

Section: Model Simulationsmentioning

confidence: 99%

Relation between branching patterns and perfusion in stochastic generated coronary arterial trees

et al. 2007

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Biological variation in branching patterns is likely to affect perfusion of tissue. To assess the fundamental consequences of branching characteristics, 50 stochastic asymmetrical coronary trees and one nonstochastic symmetrical branching tree were generated. In the stochastic trees, area growth, A, at branching points was varied: A = random; 1.00; 1.10; 1.13 and 1.15 and symmetry, S, was varied: S = random; 1.00; 0.70; 0.58; 0.50 and 0.48. With random S and A values, a large variation in flow and volume was found, linearly related to the number of vessels in the trees. Large A values resulted in high number of vessels and high flow and volume values, indicating vessels connected in parallel. Lowering symmetry values increased the number of vessels, however, without changing flow, indicating a dominant connection of vessels in series. Both large A and small S values gave more realistic gradual pressure drops compared to the symmetrical non-stochastic branching tree. This study showed large variations in tree realizations, which may reflect real biological variations in tree anatomies. Furthermore, perfusion of tissue clearly depends on the branching rules applied.

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Structure and hemodynamics of microvascular networks: heterogeneity and correlations

Cited by 118 publications

References 0 publications

Cerebral Blood Flow Modeling in Primate Cortex

Cerebral Blood Flow Modeling in Primate Cortex

Direct Tracking of Particles and Quantification of Margination in Blood Flow

Relation between branching patterns and perfusion in stochastic generated coronary arterial trees

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