바로가기  >

Abstract
Objective.To develop a novel, unenhanced magnetic resonance angiography (MRA) exploiting cardiac-gated, single-slab 3D chemical-shift-encoded gradient- and spin-echo (GRASE) imaging for robust background suppression.Approach.The proposed single-slab 3D GRASE employs variable-flip-angles (VFA) in the refocusing radio-frequency (RF) pulse train to promote sensitivity to blood flow as well as imaging encoding efficiency. Phase encoding blips are inserted between adjacent lobes of the switching readout gradients such that chemical shift-induced phase information is encoded into different locations in k-space. Based on the assumption that most background signals in the angiogram come from the fatty tissues, the proposed method directly separates angiograms from fatty background tissue signals from highly incomplete measurements by solving a constrained optimization problem with sparsity prior. Numerical simulations and experiments were performed to validate the effectiveness of the proposed method in healthy volunteers as compared with conventional fresh blood imaging (FBI).Main results.Compared with conventional FBI, the proposed method yields clearer delineation of small branching arteries and robust fatty background suppression without apparent loss of signals.Significance.We have successfully demonstrated the feasibility of the proposed, single-slab 3D VFA GRASE with chemical-shift-encoded reconstruction for the generation of robust unenhanced peripheral MRA.

Affiliations

Hyunkyung Maeng 1, Hahnsung Kim 2 3, Jeong-Woo Sohn 4, Jaeseok Park 1 5
1Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea.
2Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, United States of America.
3Emory National Primate Research Center, Emory University, Atlanta, GA, United States of America.
4Department of Medical Science, College of Medicine, Catholic Kwandong University, Gangneung, Republic of Korea.
5Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea.