Background: Periarterial cerebrospinal fluid (CSF) flow has been hypothesized to contribute to brain waste clearance but is poorly understood. Animal studies suggest arterial pulsatility drives perivascular CSF in the direction of cerebral arterial blood flow (CBF), but human validation has relied on MRI approaches that do not inform on flow-directionality. Here, we use a high-performance gradient system enabling low velocity encoding (Venc) 4D flow MRI, to characterize cardiac-driven periarterial CSF flow and CBF-to-CSF flow coupling.
Methods: Healthy participants (N = 10) underwent high resolution (0.8 mm isotropic) 4D flow MRI of blood (Venc = 120 cm/s) and CSF (Venc = 1.0 cm/s) on a 3.0T head-only system (MAGNUS, GE Healthcare; Gmax = 300mT/m, Smax = 750T/m/s). Images were reconstructed using local low rank (LLR) constrained parallel imaging and background field corrected using iterative, complex domain fitting. Luminal blood and associated periarterial CSF waveforms were extracted along the left and right anterior (ACA A1), middle (MCA M1 and M2), and posterior (PCA P2) cerebral arteries using a centerline approach, and characterized individually by amplitude and stroke volume and jointly by coupling coefficients from maximum cross-correlation ([Formula: see text]) and time-lags.
Results: For low Venc 4D flow MRI, MAGNUS dramatically reduced the echo time and temporal resolution compared to whole-body systems. CBF and CSF measurements were successful in 61/80 locations (up to 8 per participant) with 19 measurements excluded due to velocity aliasing and/or poor local quality of the flow data. Inverse (anti-correlated) CBF-to-CSF coupling ([Formula: see text]) was observed for most segments (56/61), with strong coupling observed for all vessels, including M1 (-0.85 ± 0.06), A1 (-0.80 ± 0.12), P2 (-0.79 ± 0.08), and M2 (-0.78 ± 0.08). Further, CBF preceded CSF for most (43/56) segments, with short CBF-to-CSF lags in A1 (5.30 ± 64 ms) and P2 (4.13 ± 63 ms), higher in M1 (43 ± 39 ms), and highest in M2 (115 ± 39 ms). CBF and CSF flow metrics were also correlated in terms of flow rate amplitude (r = 0.40, p = 0.015) and stroke volume (r = 0.56, p < 0.001).
Conclusions: High-performance gradient systems facilitate 4D flow imaging of very slow CSF. Joint analysis of CBF and periarterial CSF allowed assessment of CBF-to-CSF dynamics coupling. For most vessels, an inverse coupling and a positive time-lag was found from CBF to periarterial CSF, suggesting that the systolic arterial expansion drives CSF backwards and inwards again during diastolic relaxation. The proposed approach can be used to improve our understanding of CBF and CSF dynamics in aging and dementia.
Clinical trial number: Not applicable.
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