4 research outputs found
Hybrid-space reconstruction with add-on distortion correction for simultaneous multi-slab diffusion MRI
Purpose: This study aims to propose a model-based reconstruction algorithm
for simultaneous multi-slab diffusion MRI acquired with blipped-CAIPI gradients
(blipped-SMSlab), which can also incorporate distortion correction.
Methods: We formulate blipped-SMSlab in a 4D k-space with kz gradients for
the intra-slab slice encoding and km (blipped-CAIPI) gradients for the
inter-slab encoding. Because kz and km gradients share the same physical axis,
the blipped-CAIPI gradients introduce phase interference in the z-km domain
while motion induces phase variations in the kz-m domain. Thus, our previous
k-space-based reconstruction would need multiple steps to transform data back
and forth between k-space and image space for phase correction. Here we propose
a model-based hybrid-space reconstruction algorithm to correct the phase errors
simultaneously. Moreover, the proposed algorithm is combined with distortion
correction, and jointly reconstructs data acquired with the blip-up/down
acquisition to reduce the g-factor penalty.
Results: The blipped-CAIPI-induced phase interference is corrected by the
hybrid-space reconstruction. Blipped-CAIPI can reduce the g-factor penalty
compared to the non-blipped acquisition in the basic reconstruction.
Additionally, the joint reconstruction simultaneously corrects the image
distortions and improves the 1/g-factors by around 50%. Furthermore, through
the joint reconstruction, SMSlab acquisitions without the blipped-CAIPI
gradients also show comparable correction performance with blipped-SMSlab.
Conclusion: The proposed model-based hybrid-space reconstruction can
reconstruct blipped-SMSlab diffusion MRI successfully. Its extension to a joint
reconstruction of the blip-up/down acquisition can correct EPI distortions and
further reduce the g-factor penalty compared with the separate reconstruction.Comment: 10 figures+tables, 8 supplementary figure
High-resolution whole-brain diffusion MRI at 3T using simultaneous multi-slab (SMSlab) acquisition
High-resolution diffusion MRI (dMRI) is a crucial tool in neuroscience studies to detect fine fiber structure, depict complex fiber architecture and analyze cortical anisotropy. However, high-resolution dMRI is limited by its intrinsically low SNR due to diffusion attenuation. A series of techniques have been proposed to improve the SNR performance, but most of them are at the cost of long scan time, which in turn sacrifice the SNR efficiency, especially for large FOV imaging, such as whole-brain imaging. Recently, a combination of 3D multi-slab acquisition and simultaneous multi-slice (SMS) excitation, namely simultaneous multi-slab (SMSlab), has been demonstrated to have potential for high-resolution diffusion imaging with high SNR and SNR efficiency. In our previous work, we have proposed a 3D Fourier encoding and reconstruction framework for SMSlab acquisition. In this study, we extend this 3D k-space framework to diffusion imaging, by developing a novel navigator acquisition strategy and exploring a k-space-based phase correction method. In vivo brain data are acquired using the proposed SMSlab method and compared with a series of different acquisitions, including the traditional 3D multi-slab, 2D SMS and 2D single-shot EPI (ss-EPI) acquisitions. The results demonstrate that SMSlab has a better SNR performance compared with 3D multi-slab and 2D SMS. The detection capacity of fine fiber structures is improved using SMSlab, compared with the low-resolution diffusion imaging using conventional 2D ss-EPI