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Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
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Sensitivity analysis on a network model of glymphatic flow.

Kimberly A S Boster1, Jeffrey Tithof2, Douglas D Cook3

  • 1Department of Mechanical Engineering, University of Rochester, Rochester, NY 14627, USA.

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|June 1, 2022
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Summary
This summary is machine-generated.

Cerebrospinal and interstitial fluid (ISF) flow models are limited by unknown brain parameters. The model is most sensitive to perivascular space permeability, a key area for future research.

Keywords:
cerebrospinal fluidcomputational modellingglymphatic systemperivascular spacesreduced-order modellingsensitivity analysis

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Area of Science:

  • Neuroscience
  • Fluid Dynamics
  • Computational Biology

Background:

  • Intracranial cerebrospinal fluid (CSF) and interstitial fluid (ISF) dynamics are crucial for brain health, but direct in vivo human studies are limited.
  • Accurate computational models are essential for understanding these phenomena, but require precise input parameters.

Purpose of the Study:

  • To conduct a sensitivity analysis on a lumped-parameter network model of murine brain CSF and ISF flow.
  • To identify key parameters influencing model predictions and assess the impact of input uncertainty.

Main Methods:

  • Utilized a Monte Carlo approach for sensitivity analysis on a network model of CSF and ISF.
  • Investigated flow and solute transport in perivascular spaces (PVSs) and the brain parenchyma.
  • Bounded model predictions based on parameter uncertainty.

Main Results:

  • Transport Péclet numbers in penetrating PVSs and parenchyma differ by at least two orders of magnitude.
  • Low permeability in penetrating PVSs suggests unrealistic pressure requirements or poor perfusion.
  • Model sensitivity is highest for the permeability of penetrating PVSs, a poorly constrained parameter.

Conclusions:

  • The permeability of penetrating perivascular spaces is a critical, yet largely unknown, parameter for brain fluid dynamics models.
  • Current uncertainty in penetrating PVS permeability significantly limits the practical application and interpretation of existing models.
  • Future experimental measurement of penetrating PVS permeability is essential for advancing our understanding of intracranial fluid transport.