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Fluids and Barriers of the CNS
Published in: Fluids and Barriers of the CNS 1/2018

Open Access 01-12-2018 | Research

Pulsatile flow drivers in brain parenchyma and perivascular spaces: a resistance network model study

Authors: Julian Rey, Malisa Sarntinoranont

Published in: Fluids and Barriers of the CNS | Issue 1/2018

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Abstract

Background

In animal models, dissolved compounds in the subarachnoid space and parenchyma have been found to preferentially transport through the cortex perivascular spaces (PVS) but the transport phenomena involved are unclear.

Methods

In this study two hydraulic network models were used to predict fluid motion produced by blood vessel pulsations and estimate the contribution made to solute transport in PVS and parenchyma. The effect of varying pulse amplitude and timing, PVS dimensions, and tissue hydraulic conductivity on fluid motion was investigated.

Results

Periodic vessel pulses resulted in oscillatory fluid motion in PVS and parenchyma but no net flow over time. For baseline parameters, PVS and parenchyma peak fluid velocity was on the order of 10 μm/s and 1 nm/s, with corresponding Peclet numbers below 103 and 10−1 respectively. Peak fluid velocity in the PVS and parenchyma tended to increase with increasing pulse amplitude and vessel size, and exhibited asymptotic relationships with hydraulic conductivity.

Conclusions

Solute transport in parenchyma was predicted to be diffusion dominated, with a negligible contribution from convection. In the PVS, dispersion due to oscillating flow likely plays a significant role in PVS rapid transport observed in previous in vivo experiments. This dispersive effect could be more significant than convective solute transport from net flow that may exist in PVS and should be studied further.
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Metadata
Title
Pulsatile flow drivers in brain parenchyma and perivascular spaces: a resistance network model study
Authors
Julian Rey
Malisa Sarntinoranont
Publication date
01-12-2018
Publisher
BioMed Central
Published in
Fluids and Barriers of the CNS / Issue 1/2018
Electronic ISSN: 2045-8118
DOI
https://doi.org/10.1186/s12987-018-0105-6

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