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 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.

[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 G_x, 90° and 270° for G_y). 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 (k_x, k_y 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.

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. 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.