ArticleFluids and barriers of the CNS2023
Sizes and shapes of perivascular spaces surrounding murine pial arteries.
Article in Fluids and barriers of the CNS, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 19 citations in OpenAlex.
- High frame ratebioRxiv : the preprint server for biology · 2026Article
- Solvent-free Nanoparticle Assembly Protocol (SNAP): one-pot formulation of drug loaded polyester nanoparticles and their vessel size-dependent perivascular transport in the brain.bioRxiv : the preprint server for biology · 2026Article
- Quantifying cerebrospinal fluid flow in pial perivascular spaces of rats.Fluids and barriers of the CNS · 2026Article
- White Matter Geometry Confounds Diffusion Tensor Imaging Along Perivascular Space (DTI-ALPS) Measures.Human brain mapping · 2025Article
- Advection and diffusion in perivascular and extracellular spaces in the brain.Journal of the Royal Society, Interface · 2025Article
- Arterial pulsations and transmantle pressure synergetically drive glymphatic flow.Scientific reports · 2025Article
- InferringInterface focus · 2024Article
- A brain-wide solute transport model of the glymphatic system.Journal of the Royal Society, Interface · 2024Article
- Perivascular spaces around arteries exceed perivenous spaces in the mouse brain.Scientific reports · 2024Article
- Is CAA a perivascular brain clearance disease? A discussion of the evidence to date and outlook for future studies.Cellular and molecular life sciences : CMLS · 2024Review
- Parenchymal CSF fraction is a measure of brain glymphatic clearance and positively associated with amyloid beta deposition on PET.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Hydraulic resistance of three-dimensional pial perivascular spaces in the brain.Fluids and barriers of the CNS · 2024Article
- The directional flow generated by peristalsis in perivascular networks-Theoretical and numerical reduced-order descriptions.Journal of applied physics · 2023Article
- Hydraulic resistance of three-dimensional pial perivascular spaces in the brain.Research square · 2023Article
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7 authors at 2 institutions in 2 countries.
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Abstract
backgroundFlow of cerebrospinal fluid (CSF) through brain perivascular spaces (PVSs) is essential for the clearance of interstitial metabolic waste products whose accumulation and aggregation is a key mechanism of pathogenesis in many diseases. The PVS geometry has important implications for CSF flow as it affects CSF and solute transport rates. Thus, the size and shape of the perivascular spaces are essential parameters for models of CSF transport in the brain and require accurate quantification.
methodsWe segmented two-photon images of pial (surface) PVSs and the adjacent arteries and characterized their sizes and shapes of cross sections from 14 PVS segments in 9 mice. Based on the analysis, we propose an idealized model that approximates the cross-sectional size and shape of pial PVSs, closely matching their area ratios and hydraulic resistances.
resultsThe ratio of PVS-to-vessel area varies widely across the cross sections analyzed. The hydraulic resistance per unit length of the PVS scales with the PVS cross-sectional area, and we found a power-law fit that predicts resistance as a function of the area. Three idealized geometric models were compared to PVSs imaged in vivo, and their accuracy in reproducing hydraulic resistances and PVS-to-vessel area ratios were evaluated. The area ratio was obtained across different cross sections, and we found that the distribution peaks for the original PVS and its closest idealized fit (polynomial fit) were 1.12 and 1.21, respectively. The peak of the hydraulic resistance distribution is [Formula: see text] Pa s/m[Formula: see text] and [Formula: see text] Pa s/m[Formula: see text] for the segmentation and its closest idealized fit, respectively.
conclusionsPVS hydraulic resistance can be reasonably predicted as a function of the PVS area. The proposed polynomial-based fit most closely captures the shape of the PVS with respect to area ratio and hydraulic resistance. Idealized PVS shapes are convenient for modeling, which can be used to better understand how anatomical variations affect clearance and drug transport.
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