Daniel D Borup1, Sandeep K Ganji2, Petrice Mostardi Cogswell1, and James G Pipe1
1Radiology, Mayo Clinic, Rochester, MN, United States, 2Philips Healthcare, Gainesville, FL, United States
Synopsis
The use of a 2D golden-angle
spiral trajectory is demonstrated for the measurement of CSF flow at the
cerebral aqueduct and foramen magnum. The results compare favorably with a
standard cardiac-gated Cartesian scan when retrospectively binned using the
cardiac waveform. The spiral data also show variation in the CSF flow waveforms
across the respiratory cycle and can be reconstructed as a time-resolved image
series for spectral analysis of the flow dynamics.
Introduction
The dynamics of cerebrospinal
fluid (CSF) flow are of interest for their potential relevance to a range of
disorders. In addition to a strong cardiac-induced pulsatility, recent studies
have shown that CSF flow has a significant respiratory component that
varies with breathing pattern1,2. Golden-angle spiral trajectories
offer a reconstruction flexibility3,4 that is well suited to
investigating the multi-frequency dynamics of CSF flow. The aim of this work is
to demonstrate the measurement and analysis of 2D, through-plane CSF flow measurements
using a spiral readout trajectory with golden angle (111.246°) arm
incrementation.Methods
CSF phase contrast images were
collected in three healthy volunteers on a 3T Elition scanner (Philips
Healthcare, Netherlands). Data were obtained at the foramen magnum (VENC = 5
cm/s) and aqueduct (10 cm/s). All sequences had a flip angle of α = 15
degrees, 3 mm slice thickness, and 21.7 cm field of view with ~1.25 mm in-plane
resolution. Three k-space trajectories were employed:
- Cartesian with retrospective cardiac gating (TE/TR = 8.3/11.9 ms),
typical for a clinical exam
- Single-shot EPI (TE/TR = 39/150 ms, in-plane SENSE factor 3, 1:48 dynamic
series)
- Continuous golden-angle spiral
(TE/TR = 6.5/17.5 ms, readout dur. τ = 7 ms, 1:48 acquisition
time)
Online reconstruction was
used for the Cartesian and EPI scans. The spiral data were reconstructed offline
using a combination of Python scripts and Graphical Programming Interface (GPI)
5.
Continuous golden angle spiral data can be binned in several different ways for
reconstruction, as shown in Fig. 1. For comparison to the Cartesian data, retrospective
cardiac binning was performed. An additional binned reconstruction was
performed using respiratory data to produce cine flow waveforms at end-inspiration
and end-expiration.
For comparison to EPI, time-resolved
images were generated by selecting spiral arms using a sliding window that
advanced Δt = 70 ms from image to image. Two sliding window
types were compared: one with 21 sequential arms and a Gaussian weighting scheme
applied during gridding to preferentially weight the central arms
6, and
a second with 5 preferentially weighted sequential arms added to the full data
set from the same cardiac phase.
Results
Figure 2 shows a comparison
of the cardiac-synchronized CSF flow waveforms for regions of interest (ROIs)
defined in the aqueduct and foramen magnum of one subject. The waveforms are in
good agreement, although the spiral data appear to underestimate the strength
of the downward pulse in the aqueduct.
Figure 3 shows the effects of
respiration on the CSF flux. In the aqueduct, the flux curve is higher at peak
inspiration and lower at peak expiration for all cardiac phases, which agrees with
previous findings1,2,7. At the foramen magnum the same trend was
observed during the cranial-flow phases (positive values), but the flux was relatively unchanged during
the caudal flow phases.
Figures 4 and 5 show comparisons
of time-resolved imaging using EPI and spiral at the aqueduct and foramen
magnum, respectively. The top row shows the power spectra from the cardiac and
respiratory signals as a reference (scaling between the two curves is arbitrary).
Several respiratory peaks appear from 0.1–0.4 Hz, while there are distinct
cardiac peaks at ~1.2 Hz (the heart rate) and ~2.4 Hz (the first harmonic). All
three spectral peaks have been identified previously in CSF flow7.
The EPI data are shown in the
second row. The magnitude images highlight the poor image quality and aliasing present
in these scans, which caused difficulty choosing a suitable ROI at the cerebral
aqueduct. All three peaks are observed in the CSF flux spectrum at the foramen
magnum, but only the first two are observed at the aqueduct due to noise within the small ROI.
The spiral scans yielded significantly
improved image quality at both locations for both reconstruction approaches employed.
The flow spectrum from the 21-arm reconstruction shows the respiratory and first
cardiac peaks, while the harmonic peak at 2.4 Hz is missing due to the long
temporal width of the sliding window. Both cardiac peaks are visible in the
view sharing reconstruction, but the respiratory peak is visible only in the
aqueduct flow data. Because cardiac view sharing uses data from across the full
2-minute scan, the low frequency components from respiration are attenuated in
this method.Discussion and Conclusions
Continuous spiral sampling
with golden-angle arm incrementation offers high flexibility in the reconstruction
stage. The present results show that this technique can produce similar flow
waveforms to Cartesian imaging when averaged across many cardiac cycles, and that
the underlying data can be used to demonstrate changes to the flow across the
respiratory cycle. Time-resolved reconstructions of the spiral data showed superior image quality versus single-shot EPI and were successfully used to
identify the same spectral peaks in the CSF flow waveform.
We conclude that golden angle
spiral acquisition performs similarly to EPI for time-resolved measurements,
with improved image quality coming at the expense of temporal resolution. The
key limitation is the number of spiral arms required for spiral reconstruction;
in future studies, use of a variable-density spiral trajectory and/or longer
readout duration will reduce the number of arms needed, which could allow for improved
temporal resolution at similar image quality.Acknowledgements
Thanks to Guruprasad Krishnamoorthy for assistance with data export for offline reconstruction.References
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