机构：[1]Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, California, USA.[2]Department of Bioengineering, University of California, Los Angeles, California, USA.[3]Department of Neurology, University of California, Los Angeles, California, USA.[4]Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.重点科室诊疗科室神经外科神经外科首都医科大学附属天坛医院[5]Department of Radiology, University of Pennsylvania Medical Center, Philadelphia, Pennsylvania, USA.[6]Laboratory of Functional MRI Technology, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
PurposeTo evaluate the feasibility and performance of compressed sensing (CS) with magnitude subtraction regularization in accelerating non-contrast-enhanced dynamic intracranial MR angiography (NCE-dMRA). MethodsA CS algorithm was introduced in NCE-dMRA by exploiting the sparsity of the magnitude difference of the control and label images. The NCE-dMRA data were acquired using golden-angle stack-of-stars trajectory on six healthy volunteers and one patient with arteriovenous fistula. Images were reconstructed using (i) the proposed magnitude-subtraction CS (MS-CS); (ii) complex-subtraction CS; (iii) independent CS; and (iv) view-sharing with k-space weighted image contrast (KWIC). The dMRA image quality was compared across the four reconstruction strategies. The proposed MS-CS method was further compared with KWIC for temporal fidelity of depicting dynamic flow. ResultsThe proposed MS-CS method was able to reconstruct NCE-dMRA images with detailed vascular structures and clean background. It provided better subjective image quality than the other two CS strategies (P<0.05). Compared with KWIC, MS-CS showed similar image quality, but reduced temporal blurring in delineating the fine distal arteries. ConclusionsThe MS-CS method is a promising CS technique for accelerating NCE-dMRA acquisition without compromising image quality and temporal fidelity. Magn Reson Med 79:867-878, 2018. (c) 2017 International Society for Magnetic Resonance in Medicine.
基金：
AHAAmerican Heart Association [16SDG29630013]; NIHUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [R01EB014922, UH2NS100614, R01HL127153]
第一作者机构：[1]Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, California, USA.[2]Department of Bioengineering, University of California, Los Angeles, California, USA.
通讯作者：
通讯机构：[6]Laboratory of Functional MRI Technology, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.[*1]Laboratory of Functional MRI Technology, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, 2025 Zonal Ave, Los Angeles, CA 90033 USA.
推荐引用方式(GB/T 7714)：
Zhou Ziwu,Han Fei,Yu Songlin,et al.Accelerated noncontrast-enhanced 4-dimensional intracranial MR angiography using golden-angle stack-of-stars trajectory and compressed sensing with magnitude subtraction[J].MAGNETIC RESONANCE IN MEDICINE.2018,79(2):867-878.doi:10.1002/mrm.26747.
APA：
Zhou, Ziwu,Han, Fei,Yu, Songlin,Yu, Dandan,Rapacchi, Stanislas...&Yan, Lirong.(2018).Accelerated noncontrast-enhanced 4-dimensional intracranial MR angiography using golden-angle stack-of-stars trajectory and compressed sensing with magnitude subtraction.MAGNETIC RESONANCE IN MEDICINE,79,(2)
MLA：
Zhou, Ziwu,et al."Accelerated noncontrast-enhanced 4-dimensional intracranial MR angiography using golden-angle stack-of-stars trajectory and compressed sensing with magnitude subtraction".MAGNETIC RESONANCE IN MEDICINE 79..2(2018):867-878
医学