scholarly journals Reducing Artifacts during Arterial Phase of Gadoxetate Disodium–enhanced MR Imaging: Dilution Method versus Reduced Injection Rate

Radiology ◽  
2017 ◽  
Vol 283 (2) ◽  
pp. 429-437 ◽  
Author(s):  
Young Kon Kim ◽  
Wei-Chan Lin ◽  
Kyunghyun Sung ◽  
Steven S. Raman ◽  
Daniel Margolis ◽  
...  
Keyword(s):  
Mr Imaging ◽  
Injection Rate ◽  
Arterial Phase ◽  
Dilution Method ◽  
Gadoxetate Disodium

CAIPIRINHA-Dixon-TWIST (CDT)-VIBE MR imaging of the liver at 3.0T with gadoxetate disodium: a solution for transient arterial-phase respiratory motion-related artifacts?

2017 ◽  
Vol 28 (5) ◽  
pp. 2013-2021 ◽  
Author(s):  
Leonhard Gruber ◽  
Vera Rainer ◽  
Michaela Plaikner ◽  
Christian Kremser ◽  
Werner Jaschke ◽  
...  
Keyword(s):  
Mr Imaging ◽  
Respiratory Motion ◽  
Arterial Phase ◽  
Gadoxetate Disodium

MR imaging of renal collecting system with gadoxetate disodium: Feasibility for MR urography

2013 ◽  
Vol 38 (4) ◽  
pp. 816-823 ◽  
Author(s):  
R. Joshua Dym ◽  
Victoria Chernyak ◽  
Alla M. Rozenblit
Keyword(s):  
Mr Imaging ◽  
Gadoxetate Disodium ◽  
Mr Urography ◽  
Collecting System

Hepatic hemangiomas: Difference in enhancement pattern on 3T MR imaging with gadobenate dimeglumine versus gadoxetate disodium

2012 ◽  
Vol 81 (10) ◽  
pp. 2457-2462 ◽  
Author(s):  
Rajan T. Gupta ◽  
Daniele Marin ◽  
Daniel T. Boll ◽  
Daniela B. Husarik ◽  
Drew E. Davis ◽  
...  
Keyword(s):  
Mr Imaging ◽  
Gadobenate Dimeglumine ◽  
Gadoxetate Disodium ◽  
Enhancement Pattern ◽  
Hepatic Hemangiomas ◽  
3T Mr

scholarly journals Reduction of respiratory motion artifacts in gadoxetate-enhanced MR with a deep learning–based filter using convolutional neural network

2020 ◽  
Vol 30 (11) ◽  
pp. 5923-5932
Author(s):  
M.-L. Kromrey ◽  
D. Tamada ◽  
H. Johno ◽  
S. Funayama ◽  
N. Nagata ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
Arterial Phase ◽  
Artifact Reduction ◽  
Gadoxetate Disodium ◽  
Mr Images ◽  
Liver Mri ◽  
Lesion Conspicuity

Abstract Objectives To reveal the utility of motion artifact reduction with convolutional neural network (MARC) in gadoxetate disodium–enhanced multi-arterial phase MRI of the liver. Methods This retrospective study included 192 patients (131 men, 68.7 ± 10.3 years) receiving gadoxetate disodium–enhanced liver MRI in 2017. Datasets were submitted to a newly developed filter (MARC), consisting of 7 convolutional layers, and trained on 14,190 cropped images generated from abdominal MR images. Motion artifact for training was simulated by adding periodic k-space domain noise to the images. Original and filtered images of pre-contrast and 6 arterial phases (7 image sets per patient resulting in 1344 sets in total) were evaluated regarding motion artifacts on a 4-point scale. Lesion conspicuity in original and filtered images was ranked by side-by-side comparison. Results Of the 1344 original image sets, motion artifact score was 2 in 597, 3 in 165, and 4 in 54 sets. MARC significantly improved image quality over all phases showing an average motion artifact score of 1.97 ± 0.72 compared to 2.53 ± 0.71 in original MR images (p < 0.001). MARC improved motion scores from 2 to 1 in 177/596 (29.65%), from 3 to 2 in 119/165 (72.12%), and from 4 to 3 in 34/54 sets (62.96%). Lesion conspicuity was significantly improved (p < 0.001) without removing anatomical details. Conclusions Motion artifacts and lesion conspicuity of gadoxetate disodium–enhanced arterial phase liver MRI were significantly improved by the MARC filter, especially in cases with substantial artifacts. This method can be of high clinical value in subjects with failing breath-hold in the scan. Key Points • This study presents a newly developed deep learning–based filter for artifact reduction using convolutional neural network (motion artifact reduction with convolutional neural network, MARC). • MARC significantly improved MR image quality after gadoxetate disodium administration by reducing motion artifacts, especially in cases with severely degraded images. • Postprocessing with MARC led to better lesion conspicuity without removing anatomical details.

scholarly journals Thoracic Complications in Behçet’s Disease: Imaging Findings

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Kemal Ödev ◽  
Recep Tunç ◽  
Salih Varol ◽  
Harun Aydemir ◽  
Pınar Didem Yılmaz ◽  
...  
Keyword(s):  
Mr Imaging ◽  
Behçet’S Disease ◽  
Behcet’S Disease ◽  
Behçet's Disease ◽  
Vascular Complications ◽  
Arterial Phase ◽  
Thoracic Inlet ◽  
Ultrashort Echo Time ◽  
Behcet's Disease ◽  
Wide Range

Behçet’s disease (BD) causes vascular inflammation and necrosis in a wide range of organs and tissues. In the thorax, it may cause vascular complications, affecting the aorta, brachiocephalic arteries, bronchial arteries, pulmonary arteries, pulmonary veins, capillaries, and mediastinal and thoracic inlet veins. In BD, chest radiograph is commonly used for the initial assessment of pulmonary symptoms and complications and for follow-up and establishment of the response to treatment. With the advancement of helical or multislice computed tomography (CT) technologies, such noninvasive imaging techniques have been employed for the diagnosis of vascular lesions, vascular complications, and pulmonary parenchymal manifestations of BD. CT scan (especially, CT angiography) has been used to determine the presence and severity of pulmonary complications without resorting to more invasive procedures, in conjunction with gadolinium-enhanced three-dimensional (3D) gradient-echo magnetic resonance (MR) imaging with the subtraction of arterial phase images. These radiologic methods have characteristics that are complementary to each other in diagnosis of the thoracic complications in BD. 3D ultrashort echo time (UTE) MR imaging (MRI) could potentially yield superior image quality for pulmonary vessels and lung parenchyma when compared with breath-hold 3D MR angiography.

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