Optimization of scan protocol for high temporal resolution magnetic resonance imaging of the liver under single breath-holding using compressed sensing and parallel imaging techniques in a 1.5-T magnetic resonance system

Author:

Fukamatsu Fumiaki1,Yamada Akira1ORCID,Hayashihara Hayato2,Kitou Yoshihiro2,Fujinaga Yasunari1

Affiliation:

1. Department of Radiology, Shinshu University School of Medicine, Matsumoto, Japan

2. Division of Radiology, Shinshu University Hospital, Matsumoto, Japan

Abstract

Objective: To optimize the scan protocol for high temporal resolution magnetic resonance (MR) imaging of the liver under single breath-holding, using compressed sensing (CS) and parallel imaging (PI) techniques in a 1.5 T MR system. Methods: 31 healthy volunteers who underwent fat-suppressed gradient-echo T1 weighted imaging using a 1.5 T MR system were included. Image quality was evaluated on altering various imaging parameters in CS and PI so that the scan time was adjusted to 10 and 6 s within a single breath-holding. Normalized standard deviation (nSD = SD/mean value) and signal-to-noise ratio (SNR = mean value/SD) of liver signal intensity were measured. Visual scores for the outline of the liver and inferior right hepatic vein (IRHV) were evaluated using a 4-point scale and compared with that of the reference standard (20 s scan without CS). Results: The nSD and SNR were not significantly different when the 10 s scan with CS factor 2.0 and the 6 s scan with CS factor 2.0 and 2.5 were compared to the 20 s scan. Overall visual score (mean score of the outline of the liver and IRHV) was significantly better (p < 0.05) with the 10 s scan with CS factor 2.0 compared to the other scan protocols. Conclusion: The 10 s scan with CS factor 2.0 should be recommended for high temporal resolution MR imaging of the liver using CS and PI in a 1.5 T MR system. Advances in knowledge: This study conducts a novel MR imaging of the liver using CS and PI in a 1.5 T MR system.

Publisher

British Institute of Radiology

Subject

Materials Chemistry,Economics and Econometrics,Media Technology,Forestry

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