Accuracy of electron density, effective atomic number, and iodine concentration determination with a dual-layer dual-energy computed tomography system

2018 ◽  
Vol 45 (6) ◽  
pp. 2486-2497 ◽  
Author(s):  
Chia-ho Hua ◽  
Nadav Shapira ◽  
Thomas E. Merchant ◽  
Paul Klahr ◽  
Yoad Yagil
2018 ◽  
Vol 25 (6) ◽  
pp. 1797-1802 ◽  
Author(s):  
Zhijun Chi ◽  
Yingchao Du ◽  
Lixin Yan ◽  
Dong Wang ◽  
Hongze Zhang ◽  
...  

Unlike large-scale and expensive synchrotron radiation facilities, the Thomson scattering X-ray source can provide quasi-monochromatic, energy-tunable and high-brightness X-ray pulses with a small footprint and moderate cost, making it an excellent candidate for dual-energy and multi-energy imaging at laboratories and hospitals. Here, the first feasibility study on dual-energy computed tomography (CT) based on this type of light source is reported, and the effective atomic number and electron-density distribution of a standard phantom consisting of polytetrafluoroethylene, water and aluminium is derived. The experiment was carried out at the Tsinghua Thomson scattering X-ray source with peak energies of 29 keV and 68 keV. Both the reconstructed effective atomic numbers and the retrieved electron densities of the three materials were compared with their theoretical values. It was found that these values were in agreement by 0.68% and 2.60% on average for effective atomic number and electron density, respectively. These results have verified the feasibility of dual-energy CT based on the Thomson scattering X-ray source and will further expand the scope of X-ray imaging using this type of light source.


2017 ◽  
Vol 261 ◽  
pp. 138-143 ◽  
Author(s):  
Shun Nakajima ◽  
Hiroyuki Ito ◽  
Tetsuya Mitsuhashi ◽  
Yutaka Kubo ◽  
Kazuhiro Matsui ◽  
...  

2020 ◽  
Vol 2020 ◽  
pp. 1-8 ◽  
Author(s):  
Hayato Tomita ◽  
Hirofumi Kuno ◽  
Kotaro Sekiya ◽  
Katharina Otani ◽  
Osamu Sakai ◽  
...  

Background and Objectives. Thyroid nodules are increasingly being detected during cross-sectional imaging of the neck and chest. The purpose of this study is to investigate the efficacy of dual-energy computed tomography (DECT) using iodine concentration measurement and multiparametric texture analysis of monochromatic images for differentiating between benign and malignant thyroid nodules. Materials and Methods. This retrospective study included 34 consecutive patients who presented with thyroid nodules and underwent noncontrast DECT between 2015 and 2016. Manual segmentation of each thyroid nodule by monochromatic imaging (40, 60, and 80 keV) was performed, and an in-house developed MATLAB-based texture analysis program was used to extract 41 textures. Iodine material decomposition and CT attenuation slopes were also measured. Histopathologic findings of ultrasound-guided biopsies over a follow-up period of at least one year were used as reference standards. Basic descriptive statistics and areas under receiver operating characteristic curves (AUCs) were evaluated. Results. The 34 nodules comprised 14 benign nodules and 20 malignant nodules. Iodine content and Hounsfield unit curve slopes did not differ significantly between benign and malignant thyroid nodules (P=0.480–0.670). However, significant differences in the texture features of monochromatic images were observed between benign and malignant nodules: histogram mean and median, co-occurrence matrix contrast, gray-level gradient matrix (GLGM) skewness, and mean gradients and variance of gradients for GLGM at 80 keV (P=0.014–0.044). The highest AUC was 0.77, for the histogram mean and median of images acquired at 80 keV. Conclusions. Texture features extracted from monochromatic images using DECT, specifically acquired at high keV, may be a promising diagnostic approach for thyroid nodules. A further large study for incidental thyroid nodules using DECT texture analysis is required to validate our results.


2016 ◽  
Author(s):  
Christian David Trujillo-Bastidas ◽  
Olivia Amanda García-Garduño ◽  
José Manuel Lárraga-Gutiérrez ◽  
Arnulfo Martínez-Dávalos ◽  
Mercedes Rodríguez-Villafuerte

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