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Dynamic sodium (23Na) MRI for mapping CSF bulk flow in tissue extracellular space for clearance in human brains

Yongxian Qian¹, Karthik Lakshmanan¹, Yulin Ge¹, Yvonne W. Lui¹, Thomas Wisniewski², and Fernando E. Boada¹
¹Radiology, New York University, New York, NY, United States, ²Neurology, New York University, New York, NY, United States

Synopsis

This study presents preliminary data to demonstrate the potential of dynamic sodium MRI for mapping cerebrospinal fluid (CSF) bulk flow in extracellular space of tissues in whole brain.

INTRODUCTION

Recent studies have shown that disruption of cerebrospinal fluid (CSF) clearance of brain waste may contribute to development of Alzheimer’s disease (AD) which is characterized by excessive toxic deposits in the brain. Studies on mice demonstrated that impairment of CSF clearance led to 70% reduction in amyloid beta (Aβ) clearance^1,2 while sleep-induced enhancement of CSF flow increased Aβ clearance by 100% ³. It is unclear whether these impairment and enhancement exist in humans. Technical limitations on noninvasive in vivo approaches hinder adequate study on this important issue. Specifically, phase-contrast (PC) MRI usually measures CSF flow at aqueduct and ventricles, instead of brain tissues ^4-7. Contrast-enhanced (CE) MRI (including dynamic CE-MRI) only tracks CSF flow along vasculature^8,9. Low-b value diffusion tensor imaging (DTI) assesses local flow of CSF in drainage ^10-12. There’s no known proton (¹H)-based MRI approaches capable of distinguishing CSF from water in the brain parenchyma when external tracer is not appropriate^9,13. Here we leverage the high concentration of sodium in CSF and interstitial fluid in extracellular space against intracellular space in the parenchyma, and show a dynamic sodium (23Na) MRI for mapping CSF bulk flow in tissues in whole brain.

METHODS

Sodium MR signal is from sodium nuclei (²³Na), not protons (¹H), in tissues. CSF has a high sodium concentration of 145mM, which is nearly 10 times that in intracellular space (15mM) of human brain¹⁴ and can be more reliably measured. CSF exclusively occupies extracellular space in brain parenchyma and self-serves as an endogenous tracer on sodium imaging for bulk flow driven by pulsation. Sodium signal at an imaging voxel is defined (Eq. 1) by the voxel volume ∆V and intra-/extracellular volume fraction a and sodium concentration C. Any change in extracellular space a_e is amplified by a factor of 130 (=145-15) and leads to a scaled-up variation in signal (Eq. 2 and Fig. 1).
Eq. 1: s = ΔV (a_eC_e + a_iC_i) = ΔV (145 a_e + 15 a_i),
Eq. 2: Δs = ΔV [ Δa_e (C_e - C_i) + C_i] = ΔV (130 a_e + 15).
Dynamic sodium MRI employed an interleaved-viewing scheme in data acquisition to achieve a high temporal resolution (9.0 sec). To compensate for its intrinsically low signal-to-noise ratio (SNR), the sodium MRI used an SNR-efficient 3D trajectory, the twisted projection imaging (TPI)¹⁵, for data acquisition (Figs. 2a,b). Each frame has an independent full sampling of the k-space.
Velocity map (vector field) of CSF bulk flow was created based on the frame images using an open-source software OpenPIV (Particle Image Velocimetry, v2.5)¹⁶. It calculates pixel velocity between time frames using a correlation between image patches in an interrogation window centered at the pixel.
Numerical simulations were also performed to calculate sodium MR signal at a pixel with a given intensity varying with time at a range of frequencies of interest.

EXPERIMENTS

Two male subjects of age 27 and 72 years were studied on a 3T MRI scanner (Prisma, Siemens) with a custom-built 8-channel dual-tuned (¹H-²³Na) head array coil¹⁷. Approved IRB and written consent forms were obtained. A custom-developed TPI sequence¹⁵ was used with FOV=220mm, matrix size=64, 3D isotropic, TE/TR=5/100ms, flip angle=90°, averages=1, frames=4, p=0.4, and TA=10min28sec. The image reconstruction was implemented offline with custom-developed programs in C++ (MS Visual Studio 2012). A image slice in each subject was selected for OpenPIV to perform with interrogation window 32x32 pixels and spacing step 8x8 pixels for the best output. The velocity map was then displayed in MATLAB (R2018a). Mean and standard deviation (SD) of the velocity magnitude were computed at each frame.

RESULTS

The simulated sodium image intensity in Fig. 2c correlated with the true CSF intensity although the amplitude was not matched well. The frequency of true CSF variation was also captured by the simulated image intensity but with an unmatched value: regular heart beats (50-80/min) and normal respiration (7-11/min)¹⁸ were wraparound into 0.02-0.55 Hz (Fig. 2b). Nevertheless, the simulation clearly suggested that the dynamic sodium MRI can detect whether CSF is in motion (0.02-1.5 Hz) or at rest (0.0-0.02 Hz). Fig. 3 shows the 3D frame images of the young subject. CSF bulk flow velocity map at a slice was demonstrated in Fig. 4. For a dynamic display, two video clips for the subjects (Fig. 5) will be demonstrated at on-site presentation. The mean magnitude of CSF velocity was found decreasing by 41.4% (0.1328 vs. 0.0778 mm/s) from the young to older subject.

DISCUSSION

The mismatch between simulated and true frequencies of CSF variation in Fig. 2d was due to the relatively low temporal resolution (9 sec), which needs to be improved in the future. The decrease in velocity with aging in Fig. 4c is consistent with expectation. But it needs to be confirmed with more subjects. Sodium MRI however is not distinguishing CSF from blood or interstitial fluid in the parenchyma as they have the same sodium concentration and co-exist in extracellular space^19,20.

CONCLUSION

Dynamic sodium MRI has been demonstrated for the first time the feasibility to map velocity of CSF bulk flow in tissues in whole brain. This will encourage more efforts to invest in the improvement of temporal resolution and velocity measurement accuracy in the future.

Acknowledgements

This work was financially supported in part by NIH grants R56 AG060822, R01 NS113517, and R01 CA111996. This work was also performed under the rubric of the Center for Advanced Imaging Innovation and Research (CAI2R, www.cai2r.net), an NIBIB Biomedical Technology Resource Center (NIH P41 EB017183).

References

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Figures

Fig. 1. Schematic of tissue basis for sodium MRI in the brain: a) sodium in intra- and extracellular compartments at a voxel, b) the a-C graph for volume fraction a and sodium concentration C, and c) relative (%) sodium signal intensity at a voxel.

Fig. 2. Dynamic sodium MRI: a) the 3D k-space sampling along TPI trajectory¹⁵, b) the interleaved-viewing (dots) with measured (black) and true (green) signals varying with respiration, c) CSF signal changing with frame (dynamic MRI vs. true value), and d) frequency measured at the frames. The change of CSF signal at respiration and heart beat frequencies is detectable by the technique within 10.64min for 4 frames. Data acquisition: along the 1st ring (±kz≈0) for the 1st frame followed by the 2nd, 3rd frames, and so on; and then repeat for the next ring until all the rings are acquired.

Fig. 3. Time frames of dynamic 3D sodium MRI on a young male subject age 27 years. Color scale is the relative image intensity. There was no correction for coil sensitivity modulation.

Fig. 4. Time frames of CSF velocity (blue arrows) maps from the dynamic 3D sodium MRI on two male subjects (young at age of 27 years and older at 72 years): a) the young brain, b) the older brain, and c) the mean magnitude of in-plane velocity.

Fig. 5. Video clips, which are not available to this web-based version of the abstract but will be available at on-site presentation, of the dynamic sodium MRI images showing a continuous flow of CSF into and out of the tissues for clearance: a) the 27-year-old brain, and b) the 72-year-old brain.

Proc. Intl. Soc. Mag. Reson. Med. 28 (2020)

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