Ziwu Zhou^{1}, Fei Han^{1}, Lirong Yan^{2}, Danny J.J. Wang^{2}, and Peng Hu^{1}

In this abstract, we developed and evaluated an improved stack-of-stars (SOS) sampling strategy that can efficiently sample 3D k-space and reduce streaking artifacts. Compared with conventional SOS sampling strategies that collect the same radial angle for every slice, proposed method rotates the spokes in a golden-angle manner along the slice direction, which modifies the aliasing pattern resulted from k-space under-sampling. With either gridding reconstruction or more advanced methods, proposed rotated SOS sampling strategy provides improved image quality with reduced streaking artifacts and better delineation of fine structures.

* Rotating Stack-of-Stars*: In conventional aligned SOS (ASOS), angle $$$\theta_i$$$ of the $$$i^{th}$$$ spoke out of total $$$N_r$$$ spokes in each slice is calculated as: $$$\theta_i=\frac{\pi}{N_r}*(i-1)$$$, $$$i=1,2,...,N_r$$$. In the proposed RSOS-GR, non-zero azimuthal angle offsets that change across the slices are introduced as follows: $$$\varphi_G(j)=mod((j-1)*\frac{\pi}{N_r}*\frac{\sqrt{5}-1}{2},\frac{\pi}{N_r})$$$, $$$j=1,2,...,N_{PE}$$$, where $$$N_{PE}$$$ is the total number of slices and $$$j$$$ is the slice index. Subsequently, the angle for the $$$i^{th}$$$ radial spoke in the $$$j^{th}$$$ slice is calculated as $$$\theta_i+\varphi_G(j)$$$. As a comparison, the effect of using linear (RSOS-Linear) angle offset function $$$\varphi_L(j)=\frac{j-1}{N_{PE}}*\frac{\pi}{N_r}$$$, $$$j=1,2,...,N_{PE}$$$ was also studied in this work.

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Table 1. Imaging parameters in different applications.

Figure 1. (a) The PSF of fully-sampled and ASOS, RSOS-Linear and RSOS-GR k-space sampling with 20 spokes and 80 spokes per slice in transversal and coronal views. ASOS produces strong streaking artifact at high acceleration factor (20 spokes). With 80 spokes, there are no significant difference between the three sampling strategies; with 20 spokes, RSOS-GR has reduce energy in the PSF sidelobes compared with ASOS and RSOS-Linear in the coronal view. (b) Calculated incoherence based on the 3D PSFs with different number of spokes per slice. RSOS-GR has superior PSF incoherence compared with ASOS and RSOS-Linear.

Figure 2. Phantom images acquired with different sampling strategies and with 20, 40 and 80 spokes per slice. From left to right, each column in Fig (a), (b) and (c) shows two representative axial slices from the 3D images acquired with: fully-sampled, ASOS, GSOS-Linear, and RSOS-GR, respectively. Fig (a), (b) and (c) show three under-sampling scenarios: 20 spokes, 40 spokes and 80 spokes per slice, respectively.

Figure 3. Selected brain images acquired with different sampling strategies and number of spokes per slice. Similar to Figure 2, each column in Fig (a) and (b) shows two representative axial slices from the 3D images acquired with: fully-sampled, ASOS, GSOS-Linear, and RSOS-GR, respectively. Fig (a) and (b) show two under-sampling scenarios: 40 spokes and 80 spokes per slice, respectively.

Figure 4. (a) Two representative slices of abdominal images. RSOS-GR provides images with less streaking artifacts and sharper structures. (b) MIP images at two phases of dMRA-ASL images acquired with ASOS and RSOS-GR. Even with only 20 spokes per slice per phase, RSOS-GR is still able to reduce majority of streaking artifacts compared with ASOS using 3D gridding reconstruction. With a PI-CS reconstruction, overall image quality was improved for both acquisitions. However, blurring of vessels and residual streaking artifacts can still be seen on images with ASOS acquisition while RSOS-GR acquisition provides cleaner and sharper images.