Differentiation of liver abscess from liver metastasis using dual-energy spectral CT quantitative parameters

2019 ◽  
Vol 113 ◽  
pp. 204-208 ◽  
Author(s):  
Nan Wang ◽  
Ye Ju ◽  
Jingjun Wu ◽  
Ailian Liu ◽  
Anliang Chen ◽  
...  
2019 ◽  
Author(s):  
Yanchun Lv ◽  
Jian Zhou ◽  
Xiaofei Lv ◽  
Li Tian ◽  
Haoqiang He ◽  
...  

Abstract Background: Differentiating glioma recurrence from treatment-related changes can be challenging on conventional imaging. We evaluated the use of dual-energy spectral computed tomographic (CT) quantitative parameters for this differentiation. Methods: Twenty-eight patients were examined by dual-energy spectral imaging CT. The slope of the spectral Hounsfield unit curve (λ HU ), effective atomic number (Z eff ), normalized effective atomic number (Z eff-N ), iodine concentration (IC), and normalized iodine concentration (IC N ) in the post-treatment enhanced areas were calculated. Pathological results or clinicoradiologic follow-up of ≥2 months were used for final diagnosis. Nonparametric and t -tests were used to compare quantitative parameters between glioma recurrence and treatment-related changes. Positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated; sensitivity and specificity were calculated using receiver operating characteristic (ROC) curves. ROC curves were generated using predictive probabilities to evaluate the diagnostic value. Results: There were no significant differences in quantitative parameters based on examination of pre-contrast λ HU , Z eff , Z eff-N , IC, IC N and venous phase IC N ( P >0.05). Venous phase λ HU , Z eff , Z eff-N , and IC in glioma recurrence were higher than in treatment-related changes ( P <0.001). The optimal venous phase threshold was 1.03, 7.75, 1.04, and 2.85 mg/cm 3 , achieving 66.7%, 91.7%, 83.3%, and 91.7% sensitivity; 100.0%, 77.8%, 88.9%, and 77.8% specificity; 100.0%, 73.3%, 83.3%, and 73.3% PPV; 81.8%, 93.3%, 88.9%, and 93.3% NPV; and 86.7%, 83.3%, 86.7%, and 83.3% accuracy, respectively. The areas under the curve (AUC) were 0.912, 0.912, 0.931, and 0.910 in glioma recurrence and treatment-related changes, respectively. Conclusions: Dual-energy spectral CT imaging may provide quantitative values to aid in differentiation of glioma recurrence from treatment-related changes.


2019 ◽  
Author(s):  
Yanchun Lv ◽  
Jian Zhou ◽  
Xiaofei Lv ◽  
Li Tian ◽  
Haoqiang He ◽  
...  

Abstract Background: Differentiating glioma recurrence from treatment-related changes can be challenging on conventional imaging. We evaluated the use of dual-energy spectral computed tomographic (CT) quantitative parameters for this differentiation. Methods: Twenty-eight patients were examined by dual-energy spectral imaging CT. The slope of the spectral Hounsfield unit curve (λHU), effective atomic number (Zeff), normalized effective atomic number (Zeff-N), iodine concentration (IC), and normalized iodine concentration (ICN) in the post-treatment enhanced areas were calculated. Pathological results or clinicoradiologic follow-up of ≥2 months were used for final diagnosis. Nonparametric and t-tests were used to compare quantitative parameters between glioma recurrence and treatment-related changes. Positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated; sensitivity and specificity were calculated using receiver operating characteristic (ROC) curves. ROC curves were generated using predictive probabilities to evaluate the diagnostic value. Results: There were no significant differences in quantitative parameters based on examination of pre-contrast λHU, Zeff, Zeff-N, IC, ICN and venous phase ICN (P>0.05). Venous phase λHU, Zeff, Zeff-N, and IC in glioma recurrence were higher than in treatment-related changes (P<0.001). The optimal venous phase threshold was 1.03, 7.75, 1.04, and 2.85 mg/cm3, achieving 66.7%, 91.7%, 83.3%, and 91.7% sensitivity; 100.0%, 77.8%, 88.9%, and 77.8% specificity; 100.0%, 73.3%, 83.3%, and 73.3% PPV; 81.8%, 93.3%, 88.9%, and 93.3% NPV; and 86.7%, 83.3%, 86.7%, and 83.3% accuracy, respectively. The areas under the curve (AUC) were 0.912, 0.912, 0.931, and 0.910 in glioma recurrence and treatment-related changes, respectively. Conclusions: Dual-energy spectral CT imaging may provide quantitative values to aid in differentiation of glioma recurrence from treatment-related changes.


2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Yanchun Lv ◽  
Jian Zhou ◽  
Xiaofei Lv ◽  
Li Tian ◽  
Haoqiang He ◽  
...  

2017 ◽  
Vol 92 ◽  
pp. 145-152 ◽  
Author(s):  
Ji Eun Kim ◽  
Hyun Ok Kim ◽  
Kyungsoo Bae ◽  
Jae Min Cho ◽  
Ho Cheol Choi ◽  
...  

2019 ◽  
Author(s):  
Yanchun Lv ◽  
Jian Zhou ◽  
Xiaofei Lv ◽  
Li Tian ◽  
Haoqiang He ◽  
...  

Abstract Background: Differentiating glioma recurrence from treatment-related changes can be challenging on conventional imaging. We evaluated the efficacy of quantitative parameters measured by dual-energy spectral computed tomographic (CT) for this differentiation. Methods: Twenty-eight patients were examined by dual-energy spectral CT. The effective and normalized atomic number (Zeff and Zeff-N, respectively); spectral Hounsfield unit curve (λHU) slope; and iodine and normalized iodine concentration (IC and ICN, respectively) in the post-treatment enhanced areas were calculated. Pathological results or clinicoradiologic follow-up of ≥2 months were used for final diagnosis. Nonparametric and t-tests were used to compare quantitative parameters between glioma recurrence and treatment-related changes. Sensitivity, specificity, positive and negative predictive values (PPV and NPV, respectively), and accuracy were calculated using receiver operating characteristic (ROC) curves. Predictive probabilities were used to generate ROC curves to determine the diagnostic value. Results: Examination of pre-contrast λHU, Zeff, Zeff-N, IC, ICN, and venous phase ICN showed no significant differences in quantitative parameters (P>0.05). Venous phase λHU, Zeff, Zeff-N, and IC in glioma recurrence were higher than in treatment-related changes (P<0.001). The optimal venous phase threshold was 1.03, 7.75, 1.04, and 2.85 mg/cm3, achieving 66.7%, 91.7%, 83.3%, and 91.7% sensitivity; 100.0%, 77.8%, 88.9%, and 77.8% specificity; 100.0%, 73.3%, 83.3%, and 73.3% PPV; 81.8%, 93.3%, 88.9%, and 93.3% NPV; and 86.7%, 83.3%, 86.7%, and 83.3% accuracy, respectively. The respective areas under the curve (AUCs) were 0.912, 0.912, 0.931, and 0.910 in glioma recurrence and treatment-related changes. Conclusions: Glioma recurrence could be potentially differentiated from treatment-related changes based on quantitative values measured by dual-energy spectral CT imaging.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qian Liu ◽  
Yajuan Wang ◽  
Haicheng Qi ◽  
Yaohui Yu ◽  
Yan Xing

AbstractIn this study, the optimal monochromatic energy level in dual-energy spectral CT required for imaging coronary stents after percutaneous coronary intervention (PCI) was explored. Thirty-five consecutive patients after PCI were examined using the dual-energy spectral CT imaging mode. The original images were reconstructed at 40–140 keV (10-keV interval) monochromatic levels. The in-stent and out-stent CT values at each monochromatic level were measured to calculate the signal-to-noise ratio(SNR) and contrast-to-noise ratio (CNR) for the vessel and the CT value difference between the in-stent and out-stent lumen (dCT (in–out)), which reflects the artificial CT number increase due to the beam hardening effect caused by the stents. The subjective image quality of the stent and in-stent vessel was evaluated by two radiologists using a 5-point scale. With the increase in energy level, the CT value, SNR, CNR, and dCT (in–out) all decreased. At 80 keV, the mean CT value in-stent reached (345.24 ± 93.43) HU and dCT (in–out) started plateauing. In addition, the subjective image quality of the stents and vessels peaked at 80 keV. The 80 keV monochromatic images are optimal for imaging cardiac patients with stents after PCI, balancing the enhancement and SNR and CNR in the vessels while minimizing the beam hardening artifacts caused by the stents.


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

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