Hongpyo Lee1, Yoonho Nam2, Min-Oh Kim1, Dongyeob Han1, Sung-Min Gho1, and Dong-Hyun Kim1
1School of Electrical and Electronic Engineering, Yonsei University, Soeul, Korea, Republic of, 2Department of Radiology, Seoul St. Mary Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea, Republic of
Synopsis
Recently, myelin water fraction was investigated using
multi-echo GRE data. In case of complex model fitting for MWF, only a small fraction
of the total signal is used, small artifacts caused by physiological motion can
induce severe noise in MWF. To overcome this problem, radial trajectory which
is known to have robustness against object motion can be used. Also, this
trajectory has the additional advantage of acquiring the more center of k-space
than Cartesian trajectory which is helpful for detecting accurate T2* decay
curve, and it may provide higher SNR and improved quantification. In this
abstract, we
demonstrated that the radial acquisition can reduce artifacts and improve image
quality in MWF.Introduction
Recently, myelin water fraction (MWF) was investigated
using multi-echo GRE data
1,2,3. Some researchers suggested complex
signal models for generating more reliable myelin water images (MWI)
2.
Since complex model fitting uses only a small fraction of the total signal, small
artifacts caused by physiological motion can induce severe noise in MWF
3.
To overcome this problem, radial trajectory which is known to have robustness
against object motion
4 can be used. Also, this trajectory has the
additional advantage of acquiring the center of k-space more than Cartesian
trajectory which is helpful for detecting accurate T2* decay curve, and also
may provide higher SNR and improved quantification. Therefore, in this work, we
present the MWF using 3D Radial (Stack of Star) trajectory.
Methods
[Stack of Star Trajectory] To obtain radial
data, the sequence and trajectory shown in Figure 1 was implemented. For the
angular ordering, the sequence uses equidistant angular sampling. During radial
acquisition, linear eddy-current effects alter the gradient waveforms and lead
to a shift in k-space. To compensate this misalignment, a cross-correlation
method is applied. The cross-correlation function between a spoke and the
reflected opposite spoke is calculated. Next, this function is Fourier transformed
and slope for the compensation is found (see reference for more
detailed process) 5. The shift in k-space can be estimated by
acquiring a set of calibration spokes with opposing orientation (e.g. 0° and
180° for Gx, 90° and 270° for Gy). In this study, only 2 spokes were additionally
obtained for compensation.
[Data acquisition and processing] A healthy volunteer
was scanned at 3T (Tim Trio, Siemens Medical Solutions, Erlangen, Germany) with
a 4 channel head coil. For MWI, multi-echo 3D GRE sequence is used (Figure 1a).
The imaging parameters were as follows: matrix size: 128x128x32, spatial
resolution 2x2x3mm3, TR = 84ms, # of echoes = 16, TE1 = 1.65 ms, ΔTE = 2.08 ms, flip angle = 30°,
BW = 1560 Hz/Px, TBW = 6. 128 radial spokes were used for image reconstruction
and additional 2 spokes (kx, ky axis) were obtained for
k-space shift compensation. The total scan time was 5 min 49 s. For comparison
with conventional trajectory, Cartesian acquisition sequence was performed on
the same subject using identical parameters as in the radial sequence. The
subject maintained same breathing condition for both scans. To estimate MWF a
complex model was fitted to each voxel2.
Results
Figure
2 shows the phase images for radial and Cartesian acquisition. Ghosting
artifacts (arrow) can be seen in the phase image using Cartesian acquisition.
However, this artifact is averaged out using radial acquisition. That is, radial
acquisition is significantly higher robustness to object motion compared to the
Cartesian acquisition. Figure 3 shows the MWF maps. Severe
artifacts induced in the Cartesian acquisition are significantly reduced in the
radial case. In Cartesian case, MWF is noisy and overestimated (yellow arrows)
and does not show the structure accurately (red arrows). Radial acquisition
scheme gives higher SNR, and clearer delineation of white matter structure
compared to the Cartesian acquisition in MWF.
Discussion and Conclusion
In this
study, we demonstrated that the radial acquisition can reduce artifacts from
physiological motion in MWF. Plus, this scheme allowed accurate estimation of T2* decay by acquiring
the center of k-space more than Cartesian acquisition. Thus, the radial MWF maps were improved compared to the Cartesian acquisition
scheme. Although no interleaves were used in this study, use of interleaves or
the golden-angle ordering mode may be provide additional advantage against motion
inconsistencies and may improve the results. Furthermore, since radial trajectory
acquires the center of k-space at every TR, undersampling for scan time
reduction can applied.
Acknowledgements
No acknowledgement found.References
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Physiological noise compensation in gradient-echo myelin water imaging.
Neuroimage, 2015;120:345-349
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the nature and reduction of the displacement artifact in flow images. Magn
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method for adaptive gradient-delay compensation in radial MRI. In Proceedings
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