Quantitative renal function assessment of atheroembolic renal disease using view-shared compressed sensing based dynamic-contrast enhanced MR imaging: An in vivo study

2020 ◽  
Vol 65 ◽  
pp. 67-74
Author(s):  
Hanjing Kong ◽  
Bin Chen ◽  
Xiaodong Zhang ◽  
Chengyan Wang ◽  
Min Yang ◽  
...  
2019 ◽  
Vol 18 (3) ◽  
pp. 200-207 ◽  
Author(s):  
Hajime Sagawa ◽  
Masako Kataoka ◽  
Shotaro Kanao ◽  
Natsuko Onishi ◽  
Marcel Dominik Nickel ◽  
...  

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Dong Wang ◽  
Lori R. Arlinghaus ◽  
Thomas E. Yankeelov ◽  
Xiaoping Yang ◽  
David S. Smith

Purpose. Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is used in cancer imaging to probe tumor vascular properties. Compressed sensing (CS) theory makes it possible to recover MR images from randomly undersampled k-space data using nonlinear recovery schemes. The purpose of this paper is to quantitatively evaluate common temporal sparsity-promoting regularizers for CS DCE-MRI of the breast. Methods. We considered five ubiquitous temporal regularizers on 4.5x retrospectively undersampled Cartesian in vivo breast DCE-MRI data: Fourier transform (FT), Haar wavelet transform (WT), total variation (TV), second-order total generalized variation (TGVα2), and nuclear norm (NN). We measured the signal-to-error ratio (SER) of the reconstructed images, the error in tumor mean, and concordance correlation coefficients (CCCs) of the derived pharmacokinetic parameters Ktrans (volume transfer constant) and ve (extravascular-extracellular volume fraction) across a population of random sampling schemes. Results. NN produced the lowest image error (SER: 29.1), while TV/TGVα2 produced the most accurate Ktrans (CCC: 0.974/0.974) and ve (CCC: 0.916/0.917). WT produced the highest image error (SER: 21.8), while FT produced the least accurate Ktrans (CCC: 0.842) and ve (CCC: 0.799). Conclusion. TV/TGVα2 should be used as temporal constraints for CS DCE-MRI of the breast.


Radiology ◽  
2008 ◽  
Vol 249 (1) ◽  
pp. 307-320 ◽  
Author(s):  
Tong San Koh ◽  
Choon Hua Thng ◽  
Puor Sherng Lee ◽  
Septian Hartono ◽  
Helmut Rumpel ◽  
...  

2008 ◽  
Vol 16 (4) ◽  
pp. 597-611 ◽  
Author(s):  
Louisa Bokacheva ◽  
Henry Rusinek ◽  
Jeff L. Zhang ◽  
Vivian S. Lee

2012 ◽  
Vol 32 (suppl_1) ◽  
Author(s):  
Jie Sun ◽  
Yan Song ◽  
Huijun Chen ◽  
William Kerwin ◽  
Li Dong ◽  
...  

Objectives: To characterize adventitial vasa vasorum (VV) in unilaterally symptomatic patients and evaluate its association with intraplaque hemorrhage (IPH) and symptom status. Background: Adventitial VV is thought to be a primary source of IPH and a potential marker for plaque instability. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been shown capable of quantifying adventitial VV in the carotid artery. Methods: Patients with ischemic cerebrovascular symptoms within the past 6 months and ipsilateral carotid plaques underwent MR imaging examination, which included a multi-contrast protocol for detecting IPH and a DCE-MRI protocol for measuring adventitial VV. Both the symptomatic and contralateral asymptomatic arteries were studied. Adventitial VV was measured at consecutive slices as adventitial Ktrans from kinetic modeling. Maximum adventitial Ktrans across all slices were calculated for each artery. Results: From the 27 patients (22 men; 69±10 years) recruited, 50 arteries had adventitial Ktrans measurements. IPH arteries (0.142±0.042 vs. 0.112±0.029 min-1, p<0.001) and symptomatic arteries (0.134±0.038 vs. 0.107±0.027 min-1, p=0.001) were shown to have higher adventitial Ktrans compared to their counterparts. In multivariate analysis, IPH, symptom status and male sex were independently associated with adventitial Ktrans. Conclusions: Adventitial VV demonstrated significant associations with IPH and symptom status. In vivo assessment of adventitial VV by DCE-MRI may be useful in studying plaque pathogenesis or risk stratification, but further examination through prospective studies is needed.


2004 ◽  
Vol 112 (S 1) ◽  
Author(s):  
C Maier ◽  
M Riedl ◽  
M Clodi ◽  
C Bieglmayer ◽  
V Mlynarik ◽  
...  

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