Robert Frost1, Aaron T. Hess2, Linqing Li3, Matthew D. Robson2, Luca Biasiolli2, and Peter Jezzard1
1FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom, 2Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine, University of Oxford, Oxford, United Kingdom, 3Section on Magnetic Resonance Spectroscopy, National Institute of Mental Health, Bethesda, MD, United States
Synopsis
Ghosting and blurring artifacts caused by swallowing or coughing can be a significant problem in quantitative T2 mapping of atherosclerotic plaque in the carotid artery. The method is based on a multi-slice multiple spin-echo sequence which acquires k-space lines sequentially with a 2 s gap between lines. A navigator echo was added at the end of the echo-train to identify and reacquire data corrupted by motion. The selective reacquisition reduced ghosting and blurring artifacts in healthy volunteer scans with intentional swallowing motion.Purpose
To reduce motion artifacts in quantitative T2 mapping of the
carotid vessel wall for characterisation of atherosclerotic plaques.
Introduction
Quantitative T2 mapping of the carotid artery has been
demonstrated as a promising technique for characterising atherosclerotic plaque1. The method uses a multiple
spin-echo (MSE) sequence to acquire data at 14 echo-times for fitting of T2. In
the current multi-slice implementation, phase-encode lines are acquired
sequentially with a ~2s repetition time (TR) between lines. This acquisition
scheme is sensitive to motion during and between phase-encode lines, which
generates inconsistencies in k-space leading to ghosting and blurring in the
reconstructed images. The majority of artifacts observed in acute patient scans
are believed to be related to swallowing or coughing.
Previous approaches to mitigating swallowing artifacts
include 1D tracking of the epiglottis, self-gating, and reacquisition with
free induction decay navigators2-4. In this study, a navigator
acquisition, consisting of a single phase-encode line at $$$k_y=0$$$,
was added after the MSE acquisition to identify echo-trains affected by swallowing or
coughing movements5,6.
Methods
The duration of each echo-train was increased by 9.1ms to
accommodate the navigator (see Fig. 1) with no increase in TR required
for an acquisition with 5 slices.
Reacquisition decision: the sum of the magnitude signal
across all channels in each navigator was used as a “slice score” $$$S_{sl}(k_y)$$$ for
each echo-train:
$$S_{sl}(k_y)=\sum_c\sum_{k_x} |N_{sl}(k_x,k_y,c)|\tag{1}$$
where $$$sl$$$ refers to the slice number and
the complex navigator signal for slice $$$sl$$$ and line $$$k_y$$$ at k-space location $$$k_x$$$ in channel $$$c$$$ is given by
$$$N_{sl}(k_x,k_y,c)$$$. TR periods were ranked and identified for reacquisition based
on the sum of slice scores within each TR block (5 slices
in this study); we call this the “TR score” $$$S_{TR}(k_y)=\sum_{sl}S_{sl}(k_y)$$$. The lowest TR scores were reacquired
at the end of the scan with the number of reacquisitions specified by the
scanner operator in advance.
Replacement decision: replacement for each $$$k_y$$$ line was determined on a
slice-specific basis using the “slice score” $$$S_{sl}(k_y)$$$. The originally-acquired
data were replaced with the reacquisitions when the original slice score was
lower than the corresponding reacquired slice score. This approach is intended
to reacquire a block of slices with the same $$$k_y$$$ line index by detecting
a drop in TR score, which can be affected by only one slice, but then only
replace the affected slice by judging replacement using slice scores.
Five healthy volunteers were scanned under a technical
development ethics agreement on a Siemens Verio 3T scanner with a 4-channel
surface coil. The following acquisition parameters were used: 14 echo-times
ranging from 9.1 to 127.4ms at 9.1ms intervals, TR=2s, FOV=128×128mm2, matrix size=192×192, 5/8 partial Fourier and five 2mm slices
(100% slice gap). A 60ms DANTE preparation module was used for flowing spin
suppression7 with the following
parameters: slice gradient amplitude 18mT/m, 120 pulses, flip angle 8°,
500μs
between RF pulses, 340μs gradient duration.
Three volunteers were scanned with 15 reacquisitions and two
were scanned with 30 reacquisitions. Scan times with 15 and 30 reacquisition TR
periods were 4:36 and 5:06min, respectively (additional 30 and 60s).
Images with reacquisition replacement described above were presented on the scanner. The “without reacquisitions” versus “with reacquisitions”
images shown in comparisons below were reconstructed offline in Matlab
(Mathworks).
Results
Figure 2 shows example plots of the TR scores (used to judge
reacquisition) for each phase-encode line. The drops in TR scores correspond well to periods when the
subject was asked to move intentionally (swallowing).
Figure 3 compares the images without and with reacquisitions
in a scan with 15 reacquisitions. Figure 4 demonstrates the differences in ghosting and
blurring around the carotid wall in scans with 30 reacquisitions. Figure 5 shows the effect of motion during the acquisition of the central k-space lines and the improvement possible with reacquisition.
Discussion
The addition of a navigator line at the centre of k-space
allows identification and reacquisition of data affected by motion on a
slice-specific basis. Images using reacquired data show reduced blurring and
ghosting compared to the original images without reacquisition.
Investigating the reliability of the TR score and testing the reacquisition scheme in patients will be the subject of future work. The
reacquisition technique is expected to reduce artifacts
caused by occasional motion under the assumption that the subject returns to
the original position after moving. Prospective motion techniques that can be
used for neuroimaging are challenging in this setting due to the non-rigid body
motion of the neck.
Conclusion
Selective reacquisition of data corrupted by occasional
swallowing motion reduces artifacts that compromise the accuracy of
quantitative T2 mapping of the carotid artery.
Acknowledgements
We are grateful to the National Institute for Health Research Oxford Biomedical Research Centre and for the facilities provided by the Acute Vascular Imaging Centre. We thank Andre van der Kouwe and Dylan Tisdall for code which the reacquisition scheme was based on. We are also grateful to Juliet Semple and Peter Manley for assistance with data acquisition.References
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