Rotating single-shot acquisition (RoSA) with composite reconstruction for fast high-resolution diffusion imaging.
OBJECTIVE
To accelerate high-resolution diffusion imaging, rotating single-shot acquisition (RoSA) with composite reconstruction is proposed. Acceleration was achieved by acquiring only one rotating single-shot blade per diffusion direction, and high-resolution diffusion-weighted (DW) images were reconstructed by using similarities of neighboring DW images. A parallel imaging technique was implemented in RoSA to further improve the image quality and acquisition speed. RoSA performance was evaluated by simulation and human experiments.


METHODS
A brain tensor phantom was developed to determine an optimal blade size and rotation angle by considering similarity in DW images, off-resonance effects, and k-space coverage. With the optimal parameters, RoSA MR pulse sequence and reconstruction algorithm were developed to acquire human brain data. For comparison, multishot echo planar imaging (EPI) and conventional single-shot EPI sequences were performed with matched scan time, resolution, field of view, and diffusion directions.


RESULTS
The simulation indicated an optimal blade size of 48 × 256 and a 30 ° rotation angle. For 1 × 1 mm2in-plane resolution, RoSA was 12 times faster than the multishot acquisition with comparable image quality. With the same acquisition time as SS-EPI, RoSA provided superior image quality and minimum geometric distortion.


CONCLUSIONS
RoSA offers fast, high-quality, high-resolution diffusion images. The composite image reconstruction is model-free and compatible with various diffusion computation approaches including parametric and nonparametric analyses. Magn Reson Med 79:264-275, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Qiuting
Q
Wen
Department of Psychological and Brain Sciences and Dartmouth Brain Imaging Center, Dartmouth College, Hanover, New Hampshire, USA.
Chandana
C
Kodiweera
Siemens Medical Solutions, Inc, Morrisville, North Carolina, USA.
Brian M
BM
Dale
Siemens Medical Solutions, Inc., Customer Solutions Group, Chicago, Illinois, USA.
Giri
G
Shivraman
Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Yu-Chien
YC
Wu
D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging*; D003198:Computer Simulation; D038524:Diffusion Magnetic Resonance Imaging; D017352:Echo-Planar Imaging; D064368:Healthy Volunteers; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted; D007091:Image Processing, Computer-Assisted; D019047:Phantoms, Imaging; D015203:Reproducibility of Results
blade; dMRI; diffusion imaging; fast; high resolution; single shot