Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 West 16 Street, Suite 4100, Indianapolis, IN, 46202, USA.
Weldon School of Biomedical Engineering Department, Purdue University, 206 S Martin Jischke Drive, West Lafayette, IN, 47907, USA.
Fluids Barriers CNS. 2024 Sep 11;21(1):71. doi: 10.1186/s12987-024-00572-2.
Cardiac pulsation propels blood through the cerebrovascular network to maintain cerebral homeostasis. The cerebrovascular network is uniquely surrounded by paravascular cerebrospinal fluid (pCSF), which plays a crucial role in waste removal, and its flow is suspected to be driven by arterial pulsations. Despite its importance, the relationship between vascular and paravascular fluid dynamics throughout the cardiac cycle remains poorly understood in humans.
In this study, we developed a non-invasive neuroimaging approach to investigate the coupling between pulsatile vascular and pCSF dynamics within the subarachnoid space of the human brain. Resting-state functional MRI (fMRI) and dynamic diffusion-weighted imaging (dynDWI) were retrospectively cardiac-aligned to represent cerebral hemodynamics and pCSF motion, respectively. We measured the time between peaks (∆TTP) in and dynDWI waveforms and measured their coupling by calculating the waveforms correlation after peak alignment (correlation at aligned peaks). We compared the ∆TTP and correlation at aligned peaks between younger [mean age: 27.9 (3.3) years, n = 9] and older adults [mean age: 70.5 (6.6) years, n = 20], and assessed their reproducibility within subjects and across different imaging protocols.
Hemodynamic changes consistently precede pCSF motion. ∆TTP was significantly shorter in younger adults compared to older adults (-0.015 vs. -0.069, p < 0.05). The correlation at aligned peaks were high and did not differ between younger and older adults (0.833 vs. 0.776, p = 0.153). The ∆TTP and correlation at aligned peaks were robust across fMRI protocols (∆TTP: -0.15 vs. -0.053, p = 0.239; correlation at aligned peaks: 0.813 vs. 0.812, p = 0.985) and demonstrated good to excellent within-subject reproducibility (∆TTP: intraclass correlation coefficient = 0.36; correlation at aligned peaks: intraclass correlation coefficient = 0.89).
This study proposes a non-invasive technique to evaluate vascular and paravascular fluid dynamics. Our findings reveal a consistent and robust cardiac pulsation-driven coupling between cerebral hemodynamics and pCSF dynamics in both younger and older adults.
心脏搏动推动血液通过脑血管网络,以维持脑内稳态。脑血管网络被独特的脑脊髓液围绕(pCSF),它在废物清除中起着至关重要的作用,其流动被怀疑是由动脉搏动驱动的。尽管其重要性,在人类中,整个心动周期内血管和 pCSF 动力学之间的关系仍知之甚少。
在这项研究中,我们开发了一种非侵入性的神经影像学方法来研究人类大脑蛛网膜下腔的脉动血管和 pCSF 动力学之间的耦合。静息态功能磁共振成像(fMRI)和动态扩散加权成像(dynDWI)被回顾性地与心脏对齐,分别代表脑血流动力学和 pCSF 运动。我们测量了和 dynDWI 波形之间的峰值时间间隔(∆TTP),并通过在峰值对齐后计算波形相关性来测量它们的耦合(对齐峰值的相关性)。我们比较了年轻组(平均年龄:27.9(3.3)岁,n=9)和老年组(平均年龄:70.5(6.6)岁,n=20)之间的 ∆TTP 和对齐峰值的相关性,并评估了它们在个体内和不同成像方案之间的可重复性。
血流动力学变化始终先于 pCSF 运动。与老年人相比,年轻人的 ∆TTP 明显缩短(-0.015 对-0.069,p<0.05)。对齐峰值的相关性很高,年轻人和老年人之间没有差异(0.833 对 0.776,p=0.153)。∆TTP 和对齐峰值的相关性在 fMRI 方案中是稳健的(∆TTP:-0.15 对-0.053,p=0.239;对齐峰值的相关性:0.813 对 0.812,p=0.985),并表现出良好到极好的个体内可重复性(∆TTP:组内相关系数=0.36;对齐峰值的相关性:组内相关系数=0.89)。
本研究提出了一种评估血管和 pCSF 动力学的非侵入性技术。我们的发现揭示了在年轻和老年人中,大脑血流动力学和 pCSF 动力学之间存在一致且稳健的心脏搏动驱动的耦合。