Dynamics of respiratory and cardiac CSF motion revealed with real-time simultaneous multi-slice EPI velocity phase contrast imaging
Introduction
Cerebrospinal fluid (CSF) velocity is a complex phenomenon and is known to be driven by vascular pulsations (Feinberg and Mark, 1987). Although respiration is known to influence CSF movement (Klose et al., 2000, Schroth and Klose, 1992), it is also known that breathing related susceptibility changes can influence the signal phase (Raj et al., 2000b, Raj et al., 2001b) in echo planar imaging (EPI) in fMRI. In general, MR signal magnitude changes seen with CSF motion have been found to be inherently non-quantitative and cannot show the direction of CSF motion (Bergstrand et al., 1985, Bradley et al., 1986). Spin labeling techniques have shown CSF displacement with breathing and valsalva maneuvers (Yamada et al., 2013, Bhadelia et al., 2013). To date, respiratory-driven CSF velocity has not been directly measured and consequently the relative effects of cardiac and respiratory changes on CSF motion are not well understood. More specifically, the directions and the phases of respiration-driven movement of CSF in distinct compartments of ventricles, cisterns, and cortical subarachnoid spaces are not known. Better understanding of these velocity distributions in time and space are likely occurring through links between cardiothoracic physiology, cerebrovascular, and intracranial CSF dynamics.
Earlier techniques of measuring velocity with phase imaging (Feinberg and Mark, 1987, Enzmann and Pelc, 1992) inherently could not detect respiratory changes since data over several minutes was sorted or regrouped by its time in the cardiac cycle; hence, each image has randomized respiratory phase contributions. Real-time EPI does not require the sorting and grouping of data as images can be acquired in less than 100 ms. Earlier techniques of velocity phase in spin echo EPI were cardiac gated to study cardiac-driven brain motion (Poncelet et al., 1992), and by not being real-time acquisitions, did not reveal respiratory changes in velocity. Conventional EPI time series data have shown signal intensity variations in aqueductal CSF synchronous with respiration (Klose et al., 2000, Schroth and Klose, 1992); however, these sequences could not show the direction of CSF motion nor quantify velocity as the work presented here.
Utilizing a recent development of simultaneous multi-slice (SMS) snapshot echo planar imaging (EPI) (Larkman et al., 2001, Feinberg et al., 2010, Moeller et al., 2010, Setsompop et al., 2012, Feinberg and Setsompop, 2013), time series data at different levels in the brain can be obtained simultaneously without compromising temporal resolution. We have combined SMS-EPI with bipolar gradient pulses (Hahn, 1960, Moran, 1982) for encoding fluid velocity in phase shifts in order to create an extremely fast and quantitative MRI technique to image CSF movement throughout the intraventricular passageways and subarachnoid spaces for real-time CSF imaging (Feinberg et al., 2012, Chen et al., 2014, Beckett et al., 2015). Given CSF velocity can be measured in real time without gating or reordering, we extended the length of the time series to half a minute in order to detect potential changes occurring over several respiratory cycles that would not be readily apparent over a single respiratory cycle. This takes advantage of simultaneous time series data by avoiding errors from normal variations occurring over time and has enabled studies of normal physiological breathing on CSF movement within the brain and subarachnoid spaces. Large regions of the brain and its surrounding CSF spaces were scanned to study CSF dynamics in normal subjects under different breathing conditions.
Section snippets
Methods
A pulse sequence for velocity phase imaging utilizing simultaneous multi-slice (SMS) EPI was developed as shown in Fig. 1. This is an adaptation of the SMS-EPI sequence with additional velocity encoding (VENC) bipolar gradient pulses. VENC is defined as the velocity range corresponding to phase shifts spanning from − 180° to + 180°. VENC ≥ 2.5 cm/s allowed real-time continuous imaging of multiple slices simultaneously at about 80 ms sampling rate. In early experiments, a dual-band saturation pulse
Data analysis
The subtraction of pairs of phase images acquired time sequentially in adjacent TRs generated the time series of phase difference images for velocity measurements. These phase difference images were corrected for phase offsets errors in the data (e.g., those introduced by eddy currents) (Walker et al., 1993): the phase difference images of static tissue region were used to calculate linearly varying phase offset errors in three spatial directions, and these linearly fitted phase offset were
Results
Fig. 2 shows the magnitude and phase difference images from a single SMS acquisition compared with the equivalent phase difference image from a standard single-slice acquisition. The two time series from an ROI placed in the aqueduct during an identical breathing scheme are also shown, showing good agreement between the two methods. Correlations were significantly higher between single- and multi-slice scans with same breathing scheme (two-sample t-test, p < 0.01) than two multi-slice scans with
Discussion
In this work, SMS-EPI phase contrast imaging was used to measure respiratory and cardiac modulated CSF velocity in a number of ROIs simultaneously. The respiratory modulation of CSF velocity was discovered by collecting data under different breathing conditions, in addition to the well-known cardiac modulations (Fig. 3, Fig. 4, Fig. 5). The frequency of modulations seen in the CSF velocity time series from a selection of ROIs primarily matched up with the frequency's of two physiological
Acknowledgments
NIH 1R44NS073417.
Competing interests: Authors of this work, L Chen, A Beckett and DA Feinberg are employees of Advanced MRI Technologies, which is engaged in the development of MRI pulse sequences.
References (30)
- et al.
Ultra-fast MRI of the human brain with simultaneous multi-slice imaging
J. Magn. Reson.
(2013) - et al.
The respiratory modulation of intracranial cerebrospinal fluid pulsation observed on dynamic echo planar images
Magn. Reson. Imaging
(2008) - et al.
Computational methods for predicting drug transport in anisotropic and heterogeneous brain tissue
J. Biomech.
(2008) A flow velocity zeugmatographic interlace for NMR imaging in humans
Magn. Reson. Imaging
(1982)- et al.
Measurement of peak CSF flow velocity at cerebral aqueduct, before and after lumbar CSF drainage, by use of phase-contrast MRI: utility in the management of idiopathic normal pressure hydrocephalus
Clin. Neurol. Neurosurg.
(2008) - et al.
Phase-contrast cine MR imaging of normal aqueductal CSF flow. Effect of aging and relation to CSF void on modulus MR
Acta Radiol.
(1994) - et al.
Velocity phase imaging with simultaneous multi-slice EPI reveals respiration driven motion in spinal CSF
- et al.
Cardiac gated MR imaging of cerebrospinal fluid flow
J. Comput. Assist. Tomogr.
(1985) - et al.
Physiology-based MR imaging assessment of CSF flow at the foramen magnum with a Valsalva maneuver
Am. J. Neuroradiol.
(2013) - et al.
Flowing cerebrospinal fluid in normal and hydrocephalic states: appearance on MR images
Radiology
(1986)
7D velocity phase imaging with zoomed simultaneous multi-slice EPI reveals respiration driven motion in brain and CSF
Brain motion: measurement with phase-contrast MR imaging
Radiology
Human brain motion and cerebrospinal fluid circulation demonstrated with MR velocity imaging
Radiology
Multiplexed echo planar imaging for sub-second whole brain FMRI and fast diffusion imaging
PLoS One
Multiband Velocity EPI
Cited by (78)
An in vitro experimental investigation of oscillatory flow in the cerebral aqueduct
2024, European Journal of Mechanics, B/FluidsUse of real-time phase-contrast MRI to quantify the effect of spontaneous breathing on the cerebral arteries
2022, NeuroImageCitation Excerpt :Several EPI- or EPI-PC - based studies have been designed to investigate the effect of breathing on intracranial circulation. Effects of various respiratory patterns on CSF have been observed (Aktas et al., 2019; Chen et al., 2015; Yildiz et al., 2017). However, there is no consensus on the mechanism of CSF flow; some researchers suggest that CSF oscillations are mainly influenced by breathing (Dreha-Kulaczewski et al., 2015), while others suggest that the oscillations are influenced by both breathing and cardiac activity (Daouk et al., 2017).
Cerebrovascular activity is a major factor in the cerebrospinal fluid flow dynamics
2022, NeuroImageCitation Excerpt :The former is 500 mL for both men and women, and the latter is 3300 mL for men and 1900 mL for women (Tortora and Derrickson, 2016). In addition to revealing the myoactive flow, we were also able to quantify cardiorespiratory effects on flow at the fourth ventricle, yielding similar results to a previous study using fast PC-MRI (Chen et al., 2015). We confirmed that cardiac modulated velocity was higher than respiratory modulated velocity in the fourth ventricle, regardless of the respiration depth.
Measurement of CSF pulsation from EPI-based human fMRI
2022, NeuroImageValidating the accuracy of real-time phase-contrast MRI and quantifying the effects of free breathing on cerebrospinal fluid dynamics
2024, Fluids and Barriers of the CNS
- 1
Authors made equal contribution.