Influence of feeding hematocrit and perfusion pressure on hematocrit reduction (Fåhræus effect) in an artificial microvascular network

Abstract

Objective Hematocrit in narrow vessels is reduced due to concentration of fast flowing red blood cells (RBC) in the center, and of slower flowing plasma along the wall of the vessel, which in combination with plasma skimming at bifurcations leads to the striking heterogeneity of local hematocrit in branching capillary networks known as the network Fåhræus effect. We analyzed the influence of feeding hematocrit and perfusion pressure on the Fåhræus effect in an artificial microvascular network (AMVN). Methods RBC suspensions in plasma with hematocrits between 20–70% were perfused at pressures of 5–60 cmH2O through the AMVN. A microscope and high-speed camera were used to measure RBC velocity and hematocrit in microchannels of height of 5 μm and widths of 5–19 μm. Results Channel hematocrits were reduced compared with feeding hematocrits in 5 μm and 7 μm, but not in larger microchannels. The magnitude of hematocrit reduction increased with decreasing feeding hematocrit and decreasing perfusion pressure (flow velocity), showing an about 7-fold higher effect for 40% feeding hematocrit and low pressure/flow velocity than for 60% feeding hematocrit and high pressure/flow velocity. Conclusions The magnitude of the network Fåhræus effect in an AMVN is inversely related to feeding hematocrit and perfusion pressure.

Development of a flow standard to enable highly reproducible measurements of deformability of stored red blood cells in a microfluidic device

“…Our results suggest that changes unfold in two phases bridged by a 2‐week plateau (between Days 7 and 21) when changes in RBC deformability are not statistically significant. Previous reports of deformability impairment occurring before Day 7 or after Day 21 are partly in line with our observations . Bennett‐Guerrero et al concluded that RBC deformability measured using ektacytometry was gradually altered over the 42‐day storage period.…”

“…Preliminary assays (Fig. S1, available as supporting information in the online version of this paper) has shown that the flow rate of RCC sample was inversely influenced by its Hct level, which is in line with observations in similar microfluidic systems . The RBCs settling behavior of slow initial sedimentation phase followed by fast sedimentation phase was depicted by an initial steady flow rate followed by a flow rate decreases.…”

Race‐specific differences in the phase coherence between blood flow and oxygenation: A simultaneous NIRS, white light spectroscopy and LDF study

“…The low oxygen saturation exhibited by BA group (Table ) could perhaps be related to plasma skimming—considering that, at higher altitude, atmospheric oxygen levels are lower, leading to increased erythrocyte density and hematocrit to enable more oxygen to be delivered to the tissues. An investigation of microvascular hematocrit and its possible relation to oxygen supply indicated that processes such as muscle contraction and vasodilation (which are known to manifest in microvascular dynamics) could potentially influence the in vivo capillary hematocrit . The dynamic coordination between plasma skimming and the effect of blood viscosity on hematocrit can produce spontaneous oscillations in capillary blood flow (skin microcirculation) .…”

“…An investigation of microvascular hematocrit and its possible relation to oxygen supply indicated that processes such as muscle contraction and vasodilation (which are known to manifest in microvascular dynamics) could potentially influence the in vivo capillary hematocrit . The dynamic coordination between plasma skimming and the effect of blood viscosity on hematocrit can produce spontaneous oscillations in capillary blood flow (skin microcirculation) . Further investigation of such coordination and its effect on oscillations in blood flow and oxygenation would be very interesting.…”

Local vs. Global Blood Flow Modulation in Artificial Microvascular Networks: Effects on Red Blood Cell Distribution and Partitioning

“…Next to experimental studies in vivo (Kleinfeld et al, 1998 ; Schulte et al, 2003 ; Stefanovic et al, 2008 ; Gutiérrez-Jiménez et al, 2016 ) and numerical models (Lorthois et al, 2011a , b ; Lorthois and Lauwers, 2012 ; Schmid et al, 2017 , 2019 ; Balogh and Bagchi, 2018 ), there are several in vitro studies investigating blood flow in artificial microvascular networks in vitro (e.g., Forouzan et al, 2012 ; Reinhart et al, 2017 ; Fenech et al, 2019 ). However, to the best of our knowledge, in vitro experiments modeling different mechanisms of blood flow modulation during hyperemia are limited.…”