Cerebrospinal Fluid Flow within Ventricles and Subarachnoid Space Evaluated by Velocity Selective Spin Labeling MRI.

IF 4.7 2区 医学 Q1 NEUROIMAGING NeuroImage Pub Date : 2025-02-19 DOI:10.1016/j.neuroimage.2025.121095
Yihan Wu, Feng Xu, Dan Zhu, Anna Li, Kexin Wang, Qin Qin, Jiadi Xu
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引用次数: 0

Abstract

This study aims to evaluate cerebrospinal fluid (CSF) flow dynamics within ventricles, and the subarachnoid space (SAS) using the velocity selective spin labeling (VSSL) MRI method with Fourier-transform-based velocity selective inversion preparation. The study included healthy volunteers who underwent MRI scanning with specific VSSL parameters optimized for CSF flow quantification. The VSSL sequence was calibrated against phase-contrast MRI (PC-MRI) to ensure accurate flow velocity measurements. The CSF flow patterns observed in the ventricles were consistent with those obtained using 3D amplified MRI and other advanced MRI techniques, verifying the reliability of the VSSL method. The VSSL method successfully measured CSF flow in the SAS along major arteries, including the middle cerebral artery (MCA), anterior cerebral artery (ACA), and posterior cerebral artery (PCA), with an average flow velocity of 0.339±0.117cm/s. The diffusion component was well suppressed by flow-compensated gradients, enabling comprehensive mapping of the rapid CSF flow pattern in the SAS system and ventricles. The flow pattern in the SAS system closely resembles the recently discovered perivascular subarachnoid space (PVSAS) system. CSF flow around the MCA, PCA, and ACA arteries in the SAS exhibited a weak orientation dependency. CSF flow in the ventricles was also measured, with an average flow velocity of0.309±0.116cm/s, and the highest velocity observed along the superior-inferior direction. This study underscores the potential of VSSL MRI as a non-invasive tool for investigating CSF dynamics in both SAS and ventricles.

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来源期刊
NeuroImage
NeuroImage 医学-核医学
CiteScore
11.30
自引率
10.50%
发文量
809
审稿时长
63 days
期刊介绍: NeuroImage, a Journal of Brain Function provides a vehicle for communicating important advances in acquiring, analyzing, and modelling neuroimaging data and in applying these techniques to the study of structure-function and brain-behavior relationships. Though the emphasis is on the macroscopic level of human brain organization, meso-and microscopic neuroimaging across all species will be considered if informative for understanding the aforementioned relationships.
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