0981

Blood and CSF Dynamics During One Cardiac Cycle in the Healthy Brain Measured with Cine Phase-Contrast MRI

Marco Muccio^1,2, Zhe Sun^1,2,3, Chenyang Li^1,2,3, David Chu⁴, Lawrence Minkoff⁴, and Yulin Ge^1,2
¹Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York City, NY, United States, ²Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York City, NY, United States, ³Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York City, NY, United States, ⁴FONAR Corporation, Melville, NY, United States

Synopsis

Keywords: Neurofluids, Brain

Motivation: Quantitative analysis of blood and CSF flow dynamics is vital to understand the intracranial pulsating fluid movement environment and its role in brain homeostasis.

Goal(s): To characterize the correlation between blood (arterial/venous) and CSF flow within one cardiac cycle.

Approach: Flow dynamic measurements in neck arteries and veins, cervical CSF (CSFc) and CSF in the aqueduct of Sylvius (CSFAq) were obtained using cine phase-contrast MRI from 18 healthy volunteers.

Results: Net blood and CSFc flow wave curves depict a compensatory mechanism resulting in balance of total fluid inflow and outflow. CSFAq flow patterns mimic CSFc ones with some temporal delay.

Impact: Understanding how blood and CSF flow influence each other in healthy subjects provides a reference frame to investigate alterations caused by neurological disease. We showed a dynamic interplay between neck blood and CSF flow at the cervical and aqueduct level.

Introduction

The human central nervous system (CNS) is a complex system whose homeostatic support is ensured by a dynamic coordination of blood and cerebrospinal fluid (CSF) flow in and out of the cranium. Studies have in fact shown that CSF flow is driven by arterial pulsation[1,2]. The cerebral aqueduct (or aqueduct of Sylvius) has especially received growing interest since CSF flow in this structure has recently been observed to vary across different CNS diseases [3].Recent advancements in neuroimaging techniques have enabled investigation of the brain hydrodynamic properties within one cardiac cycle timeframe. However, only few studies have concomitantly investigated the dynamic fluctuations of blood flow (arterial and venous) and CSF flow (both at cervical and aqueduct levels) within such small timeframe[4,5]. Notably, studies have reported changes in such hydrodynamics properties, separately, in diseases[6], sleep[7] and body position[8]. This highlights the importance of establishing a comprehensive understanding of how blood and CSF flow changes within one cardiac cycle.

Methods

18 healthy volunteers (37.3±15.1 years old, 10 males) were recruited for technical development scans. MR images were acquired in a 3T scanner fitted with a 64 channels head-cervical coil. A retrospectively gated phase contrast (ReGa-PC) MRI sequence (TR=20.58ms, TE=6.12ms, FA=20, FOV matrix=0.7x0.7x0.4) was used to image CSF flow at the cervical (C2) level (CSFc; VENC=6cm/s) and CSF flow through the aqueduct of Sylvius (CSFAq; VENC=17cm/s; Fig.1A) and blood flow in the major neck arteries and veins: bilateral internal carotid (LICA and RICA) and bilateral vertebral arteries (LVA and RVA; VENC=60cm/s; Fig.1B). Positive phase direction was set for flow in the caudo-cranial direction. Each cardiac cycle was reconstructed from 128 timepoints/phases, greater than previous literature[4,8,9], using a distal pulse-oximeter. Flow measurements for each timepoint were extracted by hand-drawing regions of interest (ROIs) for each structure of interest (Fig.1C-E). A two-way ANOVA was used to address differences between arterial and venous blood and CSF flow with statistical threshold set at p<0.05. Pearson’s correlation was used to study the linear correlation between several combinations of measurements.

Results and Discussion

Blood flow measurements showed recognizable cardiac cycle changes in flow[10,11] (Fig.2A). Combining the total blood inflow (arterial) and outflow (venous) per timepoint we obtained a measure of net blood flow which peaked in the later stages of the cardiac cycle due to the sudden increase in arterial blood flow and a delay reaction in the increase of venous blood outflow (Fig.2B). A correlation between net blood and CSFc flow is evident by overlapping the two flow curves (Fig.3A), further supported by the negative linear correlation observed between CSFc and arterial blood flow (R2=0.93; p<0.0001; slope=-2.74;Fig.3B) as well as with venous blood flow (R2=0.52; p<0.0001; slope=-4.24; Fig.3C). This suggests that, in order to maintain appropriate pressure within the cranium, as net blood flow increases (caudo-cranial direction), CSFc flow increases in the opposite (cranio-caudal) direction, more closely following the changes in venous blood flow. Moreover, we observed that the waveform of CSFc flow matches the bidirectional CSF flow in the aqueduct although with an observable constant delay (Fig.3D). We hypothesize this is due to the distance between the cervical level(C2) and the aqueduct measurement locations. Nonetheless, this link represents a great potential to indirectly investigate the characteristics of the aqueduct of Sylvius. This structure is especially important since recent studies have observed alterations in aqueduct CSF flow in both aging[12] and neurological diseases [13,14], however, the findings are still under discussion.
To better have a comprehensive picture of the whole brain hydrodynamics we separated the total inflow contributions by adding the mean arterial blood flow (22.7±7.1 mL/s) and CSF flow in the cranial direction (15.8±8.9 mL/s) from the total outflow contributions of total venous blood flow (-15.5±3.4 mL/s) and the CSF flow in the caudal direction (-20.5±11.2 mL/s;Fig.4A). An interactions difference was obtained (p<0.0001), suggesting that the contribution of CSF flow differs between inflow and outflow. However, by plotting the time course of such calculated parameters (Fig.4B), it is evident that the first part of the cardiac cycle is led by a greater total inflow and that the second phase is instead governed mainly by a larger total outflow. Further investigations are warranted to clarify whether these differences might translate to changes in intracranial pressure and potentially drive glymphatic activity. Representation of such hydrodynamic system, within one cardiac cycle, is represented in figure 5.

Conclusion

Our results provide a strong proof of the close dynamic interplay between cervical net blood and CSF flow, and showed a similarity in flow curve between cervical and interventricular CSF flow, providing a comprehensive picture of the brain hydrodynamics.

Acknowledgements

This study was performed under the rubric of the Center for Advanced Imaging Innovation and Research (CAI2R, www.cai2r.net), an NIBIB National Center for Biomedical Imaging and Bioengineering (NIH P41 EB017183).

References

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2. Yang, H.C., Inglis, B., Talavage, T.M., Nair, V.V., Yao, J., Fitzgerald, B., Schwichtenberg, A.J. and Tong, Y., 2022. Coupling between cerebrovascular oscillations and CSF flow fluctuations during wakefulness: An fMRI study. Journal of Cerebral Blood Flow & Metabolism, 42(6), pp.1091-1103.

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Figures

Figure 1. Example placement of the retrospectively gated phase contrast (ReGa-PC) MRI imaging slice onto structural image for CSF flow measurements in the aqueduct of Sylvius (CSFAq) and at the cervical (C2; CSFc) level (A) and onto a time-of-flight (TOF) angiogram for measurements of arterial and venous blood flow (B). Examples of phase image (right) and magnitude image (left) used to draw region of interests (ROIs) around the CSFAq (C), CSFc (D) and neck vessels (E): bilateral internal carotid (LICA & RICA) and vertebral (LVA & RVA) arteries and bilateral jugular veins (LIJV & RIJV).

Figure 2. (A) Group average flow measured in the bilateral internal carotid (LICA and RICA) and vertebral (LVA and RVA) arteries and bilateral jugular veins (LIJV and RIJV). (B) Net blood flow calculated from combining arterial and venous measurements. Notice how the peak in net blood flow corresponds to sudden increase of arterial blood flow and the delay increase in venous blood outflow shown on the left graph.

Figure 3. (A) Comparison of cervical net blood and CSF flow (CSFc). Positive values represent flow in the caudo-cranial direction. Notice how the directionality is opposing between the two flows with a peak CSFc flow in the cranio-caudal direction compensated by a peak blood flow in the opposite direction. This is supported by the negative linear correlation with both the total arterial blood flow (B) and the venous blood flow (C). (D) Comparison of CSFc and CSF flow through the aqueduct (CSFAq) showing proportional curve patterns with an observable constant delay.

Figure 4. (A) Bar plot representing the total inflow and outflow over one cardiac cycle (cc). Inflow is composed of arterial "A" blood flow and the fraction of cervical CSF flow in the caudo-cranial direction. Outflow is composed of the venous "V" blood flow and the fraction of cervical CSF flow in the cranio-caudal direction (interaction p<0.0001). (B) Timeseries of the dynamic changes in total inflow (black) and outflow (white) over one cardiac cycle. Notice how the first part of the cardiac cycle is characterized by a greater inflow whilst the later one by a greater outflow.

Figure 5. Diagram showing the hypothesized comprehensive model of brain hydrodynamics obtained from our results. Over one cardiac cycle, we proposed that the initial balance between arterial (red arrows) and venous (green arrows) blood flow causes a caudo-cranial CSF (blue arrows) flow at both the cervical and aqueduct level (A). The subsequent increase in arterial blood flow and the slow increase in venous blood flow, we suggest, causes a change in direction of the CSF flow first at the cervical level (B) and then also in the aqueduct (C).

Proc. Intl. Soc. Mag. Reson. Med. 32 (2024)

0981

DOI: https://doi.org/10.58530/2024/0981