Sizes and shapes of perivascular spaces surrounding murine pial arteries

Abstract

Background Flow 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. Methods We 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. Results The 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 $$1.73\times 10^{15}$$ 1.73 × 10 15 Pa s/m$$^{5}$$ 5 and $$1.44\times 10^{15}$$ 1.44 × 10 15 Pa s/m$$^{5}$$ 5 for the segmentation and its closest idealized fit, respectively. Conclusions PVS 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.

Parenchymal CSF fraction is a measure of brain glymphatic clearance and positively associated with amyloid beta deposition on PET

“… 21 , 53 PVS load has been supposed to be at a similar scale as the cerebral blood volume (CBV: 3%–5%) in the human brain, 9 which might be inferred from mice research where it has been shown a ratio of 1.12 to 1.88 between PVS to vessel cross‐sectional area. 54 Therefore, CSFF is a more PVS volume‐centered measure, while the DTI‐FW is an extracellular space–dominated measure.…”

“…be inferred from mice research where it has been shown a ratio of 1.12 to 1.88 between PVS to vessel cross-sectional area. 54 Therefore, CSFF is a more PVS volume-centered measure, while the DTI-FW is an extracellular space-dominated measure.…”

Is CAA a perivascular brain clearance disease? A discussion of the evidence to date and outlook for future studies

“…First, models can serve as a generalized framework where data of different types and from distinct sources can be integrated to inform biological processes. For example, three different recent imaging and histological studies have reported direct measurements of the shapes and sizes of perivascular spaces at the pial surface [ 139 ], flow velocities within these perivascular spaces [ 66 ] and perivascular astroglial endfoot dimensions within the cortex [ 140 ], aspects that are anticipated to influence perivascular fluid and solute transport. While each study was conducted in isolation, and their results are not directly inter-relatable, computational models provide a medium for integrating these observations and understanding their respective and combined influences on fluid and solute transport along perivascular compartments.…”