Myelin Water Imaging using 3D Radial multi-echo GRE acquisition
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 data1,2,3. 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 MWF3. To overcome this problem, radial trajectory which is known to have robustness against object motion4 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

1. Sati P, et al. Micrto-compartment specific T2* relaxation in the brain. Neuroimage, 2013;77:268-278

2. Nam Y, et al. Improved Estimation of Myelin Water Fraction using Complex Model Fitting. Neuroimage, 2015;116:214-221

3. Nam Y, et al. Physiological noise compensation in gradient-echo myelin water imaging. Neuroimage, 2015;120:345-349

4. Nishimura DG, et al. On the nature and reduction of the displacement artifact in flow images. Magn Reson Med, 1991;22:481-492

5. Black KT, et al. Simple method for adaptive gradient-delay compensation in radial MRI. In Proceedings of the 19th Annual Meeting of ISMRM, Montreal, Canada, 2011. P.2816

Figures

Figure 1. (a) Pulse sequence diagram of the multi-echo radial sequence. (b) A trajectory of 3D radial (stack of star)

Figure 2. Phase image of Cartesian acquisition (left) and radial acquisition (right)

Figure 3. Myelin Water of Cartesian acquisition and Radial acquisition



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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