• Bo Li, Hao Li, Li Dong, and Guofu Huang.
• Center Laboratory, The Third Affiliated Hospital of Nanchang University, 330008 Nanchang, P.R. China; Department of Radiology, The Third Affiliated Hospital of Nanchang University, 330008 Nanchang, P.R. China.
• Magn Reson Imaging. 2017 Nov 1; 43: 129-135.

ObjectiveIn this study, we sought to investigate the feasibility of fast carotid artery MR angiography (MRA) by combining three-dimensional time-of-flight (3D TOF) with compressed sensing method (CS-3D TOF).Materials And MethodsA pseudo-sequential phase encoding order was developed for CS-3D TOF to generate hyper-intense vessel and suppress background tissues in under-sampled 3D k-space. Seven healthy volunteers and one patient with carotid artery stenosis were recruited for this study. Five sequential CS-3D TOF scans were implemented at 1, 2, 3, 4 and 5-fold acceleration factors for carotid artery MRA. Blood signal-to-tissue ratio (BTR) values for fully-sampled and under-sampled acquisitions were calculated and compared in seven subjects. Blood area (BA) was measured and compared between fully sampled acquisition and each under-sampled one.ResultsThere were no significant differences between the fully-sampled dataset and each under-sampled in BTR comparisons (P>0.05 for all comparisons). The carotid vessel BAs measured from the images of CS-3D TOF sequences with 2, 3, 4 and 5-fold acceleration scans were all highly correlated with that of the fully-sampled acquisition. The contrast between blood vessels and background tissues of the images at 2 to 5-fold acceleration is comparable to that of fully sampled images. The images at 2× to 5× exhibit the comparable lumen definition to the corresponding images at 1×.ConclusionBy combining the pseudo-sequential phase encoding order, CS reconstruction, and 3D TOF sequence, this technique provides excellent visualizations for carotid vessel and calcifications in a short scan time. It has the potential to be integrated into current multiple blood contrast imaging protocol.Copyright © 2017. Published by Elsevier Inc.

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