Comparison of 270 Versus 320 mg I/mL of Iodixanol in 1 Image Assessment of Both Renal Arteries and Veins With Dual-Energy Spectral CT Imaging in Late Arterial Phase and Their Influence on Renal Function

2017 ◽  
Vol 41 (5) ◽  
pp. 798-803 ◽  
Author(s):  
Kefeng Zhou ◽  
Jian He ◽  
Feng Qu ◽  
Haijian Fan ◽  
Yi Ma ◽  
...  

2017 ◽  
Vol 95 ◽  
pp. 222-227 ◽  
Author(s):  
Chuang-bo Yang ◽  
Shuang Zhang ◽  
Yong-jun Jia ◽  
Yong Yu ◽  
Hai-feng Duan ◽  
...  


2012 ◽  
Vol 81 (10) ◽  
pp. 2487-2494 ◽  
Author(s):  
Xiao Zhu Lin ◽  
Zhi Yuan Wu ◽  
Ran Tao ◽  
Yan Guo ◽  
Jian Ying Li ◽  
...  


2020 ◽  
Vol 28 (2) ◽  
pp. 345-356
Author(s):  
Xiaohu Li ◽  
Zhijie Li ◽  
Jianying Li ◽  
Jian Song ◽  
Yongqiang Yu ◽  
...  


2020 ◽  
Vol 128 ◽  
pp. 109061
Author(s):  
Xiaoqian Jia ◽  
Xianjun Li ◽  
Jianying Li ◽  
Qian Tian ◽  
Yue Yao ◽  
...  


2019 ◽  
Author(s):  
Zhiqiang Yang ◽  
Xinyi Wang ◽  
Hao Shi

Abstract Objective The goal of this study is to evaluate the performance of spectral CT-based quantitative analysis in differential diagnosis of hypervascular hepatic metastasis (HVHM) and hepatocellular carcinoma (HCC). Methods Spectral CT scans were performed for 47 patients with hepatic malignant tumors, including 20 patients with HVHM and 27 patients with HCC, which generated the following sets of data: single energy images in the arterial phase; iodine and water maps; marginal areas of lesions that manifested apparent signal intensification; and energy spectral parameters of normal liver tissues and abdominal aorta. Subsequently, we calculated the normalized iodine concentrations (NIC), lesion-normal parenchyma iodine concentration ratio (LNR), iodine concentration difference (ICD) between the arterial phase and the venous phase, and the spectral curve slope. An independent samples t test and receiver operating characteristic (ROC) curve analysis were applied to examine these quantitative parameters. Results In the arterial phase, the HVHM and HCC groups displayed no differences in NIC, LNR, or spectral curve slope (P > 0.05). In the venous phase, the two groups displayed significant differences in NIC, LNR, and spectral curve slope; the NIC was 0.59 ± 0.08 for the HVHM group and 0.4 5 ± 0.10 for the HCC group; the LNR was 1.17 ± 0.22 and 0.92 ± 0.16, respectively; the spectral curve slope was 1.85 ± 0.49 and 1.18 ± 0.34, respectively. In addition, there was no significant difference in ICD between the HVHM group (0.54 ± 0.39 g/L) and HCC group (0.45 ± 0.39 g/L) (P > 0.05). Finally, there were no significant differences of water or iodine concentration between the arterial phase and venous phase (P > 0.05). Taken together, the spectral curve slope in the portal venous phase had the best performance in differentiating HVHM from HCC. Conclusions HVHM and HCC have apparent differences in spectral curve and concentrations of radiocontrast agents in the portal venous phase. Hence, spectral CT imaging provides a new multiparameter quantitative approach for differentiating HVHM and HCC.



Author(s):  
Yidi Yao ◽  
Liang Li ◽  
Zhiqiang Chen

Abstract Multi-energy spectral CT has a broader range of applications with the recent development of photon-counting detectors. However, the photons counted in each energy bin decrease when the number of energy bins increases, which causes a higher statistical noise level of the CT image. In this work, we propose a novel iterative dynamic dual-energy CT algorithm to reduce the statistical noise. In the proposed algorithm, the multi-energy projections are estimated from the dynamic dual-energy CT data during the iterative process. The proposed algorithm is verified on sufficient numerical simulations and a laboratory two-energy-threshold PCD system. By applying the same reconstruction algorithm, the dynamic dual-energy CT's final reconstruction results have a much lower statistical noise level than the conventional multi-energy CT. Moreover, based on the analysis of the simulation results, we explain why the dynamic dual-energy CT has a lower statistical noise level than the conventional multi-energy CT. The reason is that: the statistical noise level of multi-energy projection estimated with the proposed algorithm is much lower than that of the conventional multi-energy CT, which leads to less statistical noise of the dynamic dual-energy CT imaging.



2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Sai-Ming Cheng ◽  
Wei Ling ◽  
Jiong Zhu ◽  
Jian-Rong Xu ◽  
Lian-Ming Wu ◽  
...  


PLoS ONE ◽  
2013 ◽  
Vol 8 (2) ◽  
pp. e53651 ◽  
Author(s):  
Zilai Pan ◽  
Lifang Pang ◽  
Bei Ding ◽  
Chao Yan ◽  
Huan Zhang ◽  
...  




2012 ◽  
Vol 22 (10) ◽  
pp. 2178-2185 ◽  
Author(s):  
Li Jun Qian ◽  
Jiong Zhu ◽  
Zhi Guo Zhuang ◽  
Qiang Xia ◽  
Yu Fan Cheng ◽  
...  


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