Erpeng Dai^{1}, Xiaodong Ma^{1}, Zhe Zhang^{1}, Chun Yuan^{1,2}, and Hua Guo^{1}

Recently, simultaneous multi-slice (SMS) has been proved to be effective for accelerating single-shot EPI (ssh-EPI) based diffusion weighted imaging (DWI). More importantly, SMS can be combined with multi-shot interleaved EPI (iEPI) DWI to achieve high resolution and high throughput simultaneously. However, signal dropout problems may exist in the final DW images, especially at high SMS acceleration factors. The main reason is the prominent cerebrospinal fluid (CSF) pulsation, which may degrade the reconstruction performance. In this study, the reconstruction algorithm is augmented by using iteration and data rejection. In-vivo experiments have demonstrated that the augmented algorithm can effectively alleviate the signal dropout problems.

**Methods**

*Experiments* All scans were performed on a Philips 3.0T Achieva TX MRI
scanner (Philips Healthcare, Best, The Netherlands) using a 32-channel head
coil. All human studies were performed under IRB approval from our institution.
For the SMS acquisitions, traditional 90° excitation and 180° refocusing RF
pulses were frequency modulated and summed. An 8-shot iEPI DWI acquisition with
SMS acceleration factor MB=3 was performed with gap=44 mm and FOV/3 shift. The
sequence diagram was the same as described in ref. (3),
with an SMS 3D navigator to record the inter-shot phase variations. Other
imaging parameters were: FOV=216×216×132 mm^{3} (sagittal orientation),
voxel size=1×1×4 mm^{3}, TE=72 ms, TR=3.6 s, partial Fourier=0.7. Diffusion
encoding was applied in 3 orthogonal directions with b=800 s/mm^{2}. Meanwhile, an 8-shot iEPI acquisition
without SMS acceleration were also performed as references, with other imaging
parameters kept the same.

*Reconstruction* The flowchart of the augmented 3D
k-space reconstruction with iteration and data rejection is shown in Fig. 1.

Step 1: The initial 3D k-space reconstruction. As described in ref. (3), the under-sampled SMS 3D navigator is first recovered to calculate the phase variations. Then the SMS 3D k-space reconstruction (3) is performed to recover the image $$$I_{i,j,s}^{0}$$$, where $$${i,j,s}$$$ is the index for shot, channel and slice, respectively.

Step 2: The iterative reconstruction. The iteration process is similar to ref. (4), including:

2.1) $$$I_{i,j,s}^{n}$$$ from different channels and shots are combined to generate an average image $$$I_{avg}$$$. The initial result from step 1 is used as $$$I_{i,j,s}^{0}$$$.

2.2) The image estimation is updated by $$$I^{n}=I_{avg}$$$.

2.3) If the difference between $$$I^{n}$$$ and $$$I^{n-1}$$$ is smaller than a predefined tolerance τ or the iteration number exceeds the predefined maximum iteration number $$$N_{iter}$$$, the iteration ends and $$$I_{i,j,s}^{n}$$$ is selected as the final result. Otherwise, the inter-shot phase estimation for each shot is updated with $$$I_{i,j,s}^{n}$$$ and $$$I^{n}$$$, which will be used in next iteration.

Step 3: The data rejection step. Previous study has shown that the distribution width of the navigator can be used to detect the severely corrupted data (5). The distribution width $$$W_{i,j,s}$$$ of the recovered navigator from each shot and each slice is first calculated. If $$$W_{i,j,s}$$$ is larger than a predefined threshold (1.05 in this study), $$$I_{i,j,s}$$$ is excluded from the calculation of the final DW image.

It should be noted that step 2 and 3 can be used independently or together. Once the final DW images are obtained, ADC maps are calculated and compared with the un-accelerated 8-shot iEPI DWI results.

**Results and Discussion**

**Conclusion**

1. Setsompop K, Cohen-Adad J, Gagoski BA, Raij T, Yendiki A, Keil B, Wedeen VJ, Wald LL. Improving diffusion MRI using simultaneous multi-slice echo planar imaging. Neuroimage 2012;63:569-580.

2. Feinberg DA, Moeller S, Smith SM, Auerbach E, Ramanna S, Glasser MF, Miller KL, Ugurbil K, Yacoub E. Multiplexed echo planar imaging for sub-second whole brain FMRI and fast diffusion imaging. PLoS One 2010;5e15710.

3. Dai E, Ma X, Zhang Z, Yuan C, Guo H. Simultaneous multislice accelerated interleaved EPI DWI using generalized blipped-CAIPI acquisition and 3D K-space reconstruction. Magn Reson Med 2016; DOI: 10.1002/mrm.26249.

4. Guo H, Ma X, Zhang Z, Zhang B, Yuan C, Huang F. POCS-enhanced inherent correction of motion-induced phase errors (POCS-ICE) for high-resolution multishot diffusion MRI. Magn Reson Med 2016;75:169-180.

5. Porter DA, Heidemann RM. High resolution diffusion-weighted imaging using readout-segmented echo-planar imaging, parallel imaging and a two-dimensional navigator-based reacquisition. Magn Reson Med 2009;62:468-475.

Fig.
1 The flowchart
of the augmented 3D k-space reconstruction with iteration and data rejection.

Fig.
2 DW image
(from one diffusion encoding direction) comparisons among different
reconstruction: (a) without iteration or data rejection; (b) only with
iteration; (c) only with data rejection; (d) with both iteration and data
rejection.

Fig.
3
ADC map comparisons among
un-accelerated
(MB=1) acquisition (a); MB=3 accelerated acceleration, reconstructed without iteration
or data rejection
(b);
only
with iteration
(c);
only
with data rejection
(d);
with
both iteration and data rejection
(e). The corresponding ADC differences between the MB=3 accelerated acquisition
and the reference are shown in the lower row.