Evidence map›Paper›PMID 39407250›Full record

ArticleFluids and barriers of the CNS2024

Modeling CSF circulation and the glymphatic system during infusion using subject specific intracranial pressures and brain geometries.

Lars Willas Dreyer, Anders Eklund, Marie E Rognes, Jan Malm, Sara Qvarlander, Karen-Helene Støverud, Kent-Andre Mardal, Vegard Vinje

Abstract read
In one paragraph

Article in Fluids and barriers of the CNS, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. A brain-wide solute transport model of the glymphatic system.Journal of the Royal Society, Interface · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Lars Willas DreyerDepartment of Scientific Computing and Numerical Analysis, Simula Research Laboratory, Oslo, Norway.
Anders EklundDepartment of Diagnostics and Intervention, Biomedical engineering and radiation physics, Umeå University, Umeå, Sweden.
Marie E RognesDepartment of Scientific Computing and Numerical Analysis, Simula Research Laboratory, Oslo, Norway.
Jan MalmDepartment of Clinical Sciences, Umeå University, Umeå, Sweden.
Sara QvarlanderDepartment of Diagnostics and Intervention, Biomedical engineering and radiation physics, Umeå University, Umeå, Sweden.
Karen-Helene StøverudDepartment of Diagnostics and Intervention, Biomedical engineering and radiation physics, Umeå University, Umeå, Sweden.
Kent-Andre MardalDepartment of Scientific Computing and Numerical Analysis, Simula Research Laboratory, Oslo, Norway. kent-and@simula.no.
Vegard VinjeDepartment of Scientific Computing and Numerical Analysis, Simula Research Laboratory, Oslo, Norway.

Funding

European Research Council 714892Norges Forskningsråd 301013Swedish National Space Board 193/17
6 · The paper itself

Abstract

backgroundInfusion testing is an established method for assessing CSF resistance in patients with idiopathic normal pressure hydrocephalus (iNPH). To what extent the increased resistance is related to the glymphatic system is an open question. Here we introduce a computational model that includes the glymphatic system and enables us to determine the importance of (1) brain geometry, (2) intracranial pressure, and (3) physiological parameters on the outcome of and response to an infusion test.

methodsWe implemented a seven-compartment multiple network porous medium model with subject specific geometries from MR images using the finite element library FEniCS. The model consists of the arterial, capillary and venous blood vessels, their corresponding perivascular spaces, and the extracellular space (ECS). Both subject specific brain geometries and subject specific infusion tests were used in the modeling of both healthy adults and iNPH patients. Furthermore, we performed a systematic study of the effect of variations in model parameters.

resultsBoth the iNPH group and the control group reached a similar steady state solution when subject specific geometries under identical boundary conditions was used in simulation. The difference in terms of average fluid pressure and velocity between the iNPH and control groups, was found to be less than 6% during all stages of infusion in all compartments. With subject specific boundary conditions, the largest computed difference was a 75% greater fluid speed in the arterial perivascular space (PVS) in the iNPH group compared to the control group. Changes to material parameters changed fluid speeds by several orders of magnitude in some scenarios. A considerable amount of the CSF pass through the glymphatic pathway in our models during infusion, i.e., 28% and 38% in the healthy and iNPH patients, respectively.

conclusionsUsing computational models, we have found the relative importance of subject specific geometries to be less important than individual differences in resistance as measured with infusion tests and model parameters such as permeability, in determining the computed pressure and flow during infusion. Model parameters are uncertain, but certain variations have large impact on the simulation results. The computations resulted in a considerable amount of the infused volume passing through the brain either through the perivascular spaces or the extracellular space.

Indexed as

BrainGlymphatic SystemHydrocephalus, Normal PressureIntracranial PressureAdultAgedCerebrospinal FluidComputer SimulationFemaleHumansMagnetic Resonance ImagingMaleModels, BiologicalCSF circulationCSF dynamicsGlymphatic pathwayInfusion testIntracranial pressureParavascular flow

Identifiers

PMID39407250
PMCPMC11481529

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.