Synchronous assessment of CSF and cerebral arteriovenous flow interactions across ultra-low, low, respiratory, and cardiac frequencies using real-time phase-contrast MRI

IF 4.5 2区医学 Q1 NEUROIMAGING

NeuroImage Pub Date : 2025-09-30 DOI:10.1016/j.neuroimage.2025.121490

Pan Liu , Kimi Owashi , Heimiri Monnier , Jean-Marc Constans , Cyrille Capel , Olivier Balédent

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Abstract

Cerebrospinal fluid (CSF) oscillations are traditionally viewed as passive responses to cardiac-driven cerebral blood volume (CBV) fluctuations. However, the origins of their respiratory, low-, and ultra-low-frequency components remain unclear. This study employed a single-VENC (30 cm/s), long-duration (∼4 min) real-time phase-contrast MRI (RT-PC) protocol to synchronously quantify cerebral blood and CSF flows across multiple frequency bands, aiming to identify the primary drivers of CSF oscillations.

In seven healthy adults, arterial, venous, and CSF flows were simultaneously acquired at the C2–C3 level under free-breathing conditions. After image segmentation, background correction, and flow integration, CBV and CSF volume displacement (CSFV) curves were derived and spectrally decomposed into ultra-low (0.01–0.05 Hz), low (0.05–0.1 Hz), respiratory (∼0.3 Hz), and cardiac (∼1 Hz) bands.

Mean amplitudes (±SD, ml) in the ultra-low, low, respiratory, and cardiac bands were as follows: for CBV, 4.6 ± 2.0, 1.1 ± 0.5, 1.3 ± 0.9, and 0.8 ± 0.1; for CSFV, 1.9 ± 0.5, 0.8 ± 0.2, 0.5 ± 0.2, and 0.6 ± 0.2. Notably, CBV amplitude in the ultra-low band exhibited a bimodal distribution potentially linked to sleep state. Cross-correlation analysis revealed mirrored CBV–CSFV coupling across all frequency bands, ranging from moderate (ultra-low and low: –0.59) to strong correlation (cardiac: –0.88, respiratory: –0.91). However, band-specific lags indicated distinct underlying mechanisms. Cardiac oscillations (CBV leading CSFV; lag = –0.18 ± 0.08 s, p < 0.01) aligned with pressure-driven models. Low-frequency oscillations (CSFV preceding CBV; lag = 0.81 ± 0.67 s, p = 0.03) suggested cerebrovascular reactivity (CVR) mediated compliance changes. Respiratory oscillations showed near-synchronous coupling (lag = –0.13 ± 0.41 s, not significant), likely reflecting combined CBV and CVR effects. In the ultra-low-frequency band, CSFV led CBV by 5–8 seconds in over half of the data, potentially reflecting a complex neuro-respiratory regulatory pathway.

This study demonstrates the feasibility of RT-PC for synchronous quantification of cerebral blood and CSF dynamics. Our findings reveal that CSF oscillations are driven not only by CBV fluctuations but also by CVR-modulated changes in brain compliance. These results provide novel insights into frequency-dependent neurofluid coupling, offering a physiological foundation for disease understanding and diagnostic development in neurological disorders.

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使用实时相衬MRI同步评估脑脊液和脑动静脉流在超低、低、呼吸和心脏频率的相互作用。

脑脊液（CSF）振荡传统上被认为是对心脏驱动的脑血容量（CBV）波动的被动反应。然而，它们的呼吸、低频和超低频成分的来源仍不清楚。本研究采用单venc (30 cm/s)，长时间（~ 4 min）实时相对比MRI （RT-PC）方案，同步量化脑血和脑脊液在多个频段的流动，旨在确定脑脊液振荡的主要驱动因素。在7名健康成人中，在自由呼吸条件下，动脉、静脉和脑脊液血流在C2-C3水平同时获得。经过图像分割、背景校正和流量整合，导出CBV和CSF容积位移（CSFV）曲线，并将其光谱分解为超低（0.01-0.05 Hz）、低（0.05-0.1 Hz）、呼吸（~ 0.3 Hz）和心脏（~ 1 Hz）波段。超低、低、呼吸和心脏波段的平均振幅（±SD, ml）如下：CBV为4.6 ± 2.0,1.1 ± 0.5,1.3 ± 0.9和0.8 ± 0.1； CSFV, 1.9± 0.5、0.8 ± 0.2,0.5 ± 0.2,和0.6 ±0.2 。值得注意的是，超低频段CBV振幅呈现双峰分布，可能与睡眠状态有关。交叉相关分析显示，CBV-CSFV在所有频带上的镜像耦合，范围从中度（超低和低：-0.59）到强相关性（心脏：-0.88，呼吸：-0.91）。然而，波段特异性滞后表明了不同的潜在机制。心电振荡（CBV领先CSFV，滞后 = -0.18±0.08 s, p < 0.01）与压力驱动模型一致。低频振荡（CSFV先于CBV，滞后 = 0.81±0.67 s, p = 0.03）提示脑血管反应性（CVR）介导的顺应性改变。呼吸振荡表现为近同步耦合（滞后 = -0.13±0.41 s，无统计学意义），可能反映了CBV和CVR的联合效应。在超低频段，CSFV在超过一半的数据中领先CBV 5-8秒，可能反映了复杂的神经呼吸调节途径。本研究证明了RT-PC同步定量脑血和脑脊液动力学的可行性。我们的研究结果表明，脑脊液振荡不仅受CBV波动的驱动，还受cvr调节的脑顺应性变化的驱动。这些结果为频率依赖性神经流体耦合提供了新的见解，为神经系统疾病的疾病理解和诊断发展提供了生理学基础。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

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.