A network model of glymphatic flow under different experimentally-motivated parametric scenarios
Jeffrey Tithof,
Kimberly A.S. Boster,
Peter A.R. Bork,
Maiken Nedergaard,
John H. Thomas,
Douglas H. Kelley
Affiliations
Jeffrey Tithof
Department of Mechanical Engineering, University of Rochester, 235 Hopeman Building, Rochester 14627, NY, USA; Department of Mechanical Engineering, University of Minnesota, 111 Church St SE, Minneapolis 55455, MN, USA; Corresponding author
Kimberly A.S. Boster
Department of Mechanical Engineering, University of Rochester, 235 Hopeman Building, Rochester 14627, NY, USA
Peter A.R. Bork
Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen N, Copenhagen, Denmark
Maiken Nedergaard
Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen N, Copenhagen, Denmark; Center for Translational Neuromedicine, Department of Neurosurgery, University of Rochester Medical Center, 601 Elmwood Avenue, Rochester 14642, NY, USA
John H. Thomas
Department of Mechanical Engineering, University of Rochester, 235 Hopeman Building, Rochester 14627, NY, USA
Douglas H. Kelley
Department of Mechanical Engineering, University of Rochester, 235 Hopeman Building, Rochester 14627, NY, USA
Summary: Flow of cerebrospinal fluid (CSF) through perivascular spaces (PVSs) in the brain delivers nutrients, clears metabolic waste, and causes edema formation. Brain-wide imaging cannot resolve PVSs, and high-resolution methods cannot access deep tissue. However, theoretical models provide valuable insight. We model the CSF pathway as a network of hydraulic resistances, using published parameter values. A few parameters (permeability of PVSs and the parenchyma, and dimensions of PVSs and astrocyte endfoot gaps) have wide uncertainties, so we focus on the limits of their ranges by analyzing different parametric scenarios. We identify low-resistance PVSs and high-resistance parenchyma as the only scenario that satisfies three essential criteria: that the flow be driven by a small pressure drop, exhibit good CSF perfusion throughout the cortex, and exhibit a substantial increase in flow during sleep. Our results point to the most important parameters, such as astrocyte endfoot gap dimensions, to be measured in future experiments.