A novel reconstruction method was proposed for dual-band EPI in an MRI system equipped with four-channel receiver coils. This method was based on a conventional kernel method utilizing an iterative calculation with regional constraints in the image domain. The method significantly improves the quality of the reconstructed images, even in the regions with less coil sensitivity. The results showed higher signal-to-noise ratio, less signal leakage, and better long-term stability in repetitions in comparison to the conventional method. The proposed method can be applied to clinical systems that have relatively few receiver coils, as well as animal systems.
Simultaneous multi-slice (SMS) acquisition can be performed fairly well on a recent high-specification MRI system for humans with a redundant number of receiver coil elements. Thus, accurate slice separation for SMS data reconstruction continues to be challenging, especially when scanners equipped with relatively few receiver coil elements are used. In a system with relatively few receiver coil elements, it is difficult to implement SMS due to the gaps in signal sensitivity between the adjacent coil elements.
In this study, we propose a novel reconstruction method using regional constraints in the image domain for the dual-band EPI of in vivo normal rat brains scanned with an animal scanner with four-channel receiver coils. The method proposed in this study aims to reduce artifacts, such as Nyquist ghosts and inter-slice signal leakage, and to maximize and stabilize the signal-to-noise ratio (SNR) in reconstructed multi-band images.
In vivo male Wister rat brains (n = 12) were scanned using a 7T animal scanner (Bruker, BioSpec70/20) equipped with a transceiver radiofrequency (RF) coil and a receiver array coil with four elements. A custom-built single-shot dual-band gradient echo 2D EPI sequence was used with blipped-controlled aliasing for the main scans, which were preceded by reference scans with a single-band 2D EPI sequence. Dual-band excitation pulses were designed on the basis of sinc functions with frequency offsets. A total of 78 slices (39 dual-band excitations) were imaged in a single repetition. The repetition time was 2,500 ms. The voxel size in the plane was 0.25 × 0.25 mm, and the slice thickness was 0.25 mm. The encoding and imaging matrix sizes in the read-out and phase-encoding directions were 96 and 56, respectively.
All the single-band and dual-band EPI raw data were
processed using custom-built reconstruction software designed for the purpose
of this study. The first step in the reconstruction was the slice separation from
the folded images using a slice-GRAPPA method with 1x1-sized kernels in the
k-space, which was followed by the EPI phase correction between the odd and
even lines in the k-space. Then, slice separation was performed again using the
optimal 3x3 size kernels on the phase-corrected data. Finally, to ensure better
quality, regional constraints were introduced by masking the resulting images
to correct the minor errors in the k-space data due to the relatively poor
signal sensitivity. The workflow of the procedures is shown
in Figure 1. The performance of the reconstruction
methods was evaluated in terms of SNR, inter-slice leakage, and g-factor.
The proposed reconstruction method can provide accurate and stable results in reconstructed images for dual-band EPI scans obtained on a 7T animal scanner (equipped with a four-channel receiver coil). The reconstructed images using the proposed method were compared with those obtained using conventional kernel methods (Figure 2). Compared to the conventional method, the proposed method shows better image quality even in the region with insufficient signal sensitivity.
Figure 3 shows all the slices of the magnitude images reconstructed using the proposed method. Figure 4 shows the g-factor maps. The mean inter-slice leakage errors with the proposed method were remarkably improved compared to those of the conventional method (from 5.07 to 3.04), while the mean g-factor remained unchanged (from 0.60 to 0.61),
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