Dual-Energy Parathyroid 4D-CT: Improved Discrimination of Parathyroid Lesions from Thyroid Tissue Using Noncontrast 40-keV Virtual Monoenergetic Images

2021 ◽  
Author(s):  
P.M. Bunch ◽  
A.A. Pavlina ◽  
M.E. Lipford ◽  
J.R. Sachs
Keyword(s):  
Thyroid Tissue ◽  
Dual Energy ◽  
4D Ct ◽  
Parathyroid Lesions ◽  
Virtual Monoenergetic Images ◽  
Monoenergetic Images

Advanced virtual monoenergetic images: improving the contrast of dual-energy CT pulmonary angiography

2015 ◽  
Vol 70 (11) ◽  
pp. 1244-1251 ◽  
Author(s):  
A. Meier ◽  
M. Wurnig ◽  
L. Desbiolles ◽  
S. Leschka ◽  
T. Frauenfelder ◽  
...  
Keyword(s):  
Pulmonary Angiography ◽  
Dual Energy ◽  
Dual Energy Ct ◽  
Ct Pulmonary Angiography ◽  
Virtual Monoenergetic Images ◽  
Monoenergetic Images

Optimizing window settings for improved presentation of virtual monoenergetic images in dual-energy computed tomography

2017 ◽  
Vol 44 (11) ◽  
pp. 5686-5696 ◽  
Author(s):  
Wanyi Fu ◽  
Daniele Marin ◽  
Juan Carlos Ramirez-Giraldo ◽  
Kingshuk Roy Choudhury ◽  
Justin Solomon ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Dual Energy ◽  
Dual Energy Computed Tomography ◽  
Virtual Monoenergetic Images ◽  
Monoenergetic Images

Image Quality on Dual-energy CTPA Virtual Monoenergetic Images

2018 ◽  
Vol 25 (8) ◽  
pp. 1075-1086 ◽  
Author(s):  
Bari Dane ◽  
Hersh Patel ◽  
Thomas O'Donnell ◽  
Francis Girvin ◽  
Geraldine Brusca-Augello ◽  
...  
Keyword(s):  
Image Quality ◽  
Dual Energy ◽  
Virtual Monoenergetic Images ◽  
Monoenergetic Images

Comparison of noise-optimized linearly blended images and noise-optimized virtual monoenergetic images evaluated by dual-source, dual-energy CT in cardiac vein assessment

2020 ◽  
pp. 028418512093324
Author(s):  
Gyeong Min Kim ◽  
Ki Seok Choo ◽  
Jin Hyeok Kim ◽  
Jae-Yeon Hwang ◽  
Chan Kyu Park ◽  
...  
Keyword(s):  
Dual Energy ◽  
Venous System ◽  
Treatment Modalities ◽  
Dual Energy Ct ◽  
Great Cardiac Vein ◽  
Coronary Venous System ◽  
Virtual Monoenergetic Images ◽  
Image Set ◽  
Noise Ratio ◽  
Monoenergetic Images

Background The coronary venous system is frequently used as an entry route to the heart and treatment modalities for many cardiac diseases and many procedures. Consequently, evaluation of the coronary venous system and understanding cardiac vein anatomy is crucial. Purpose To determine the optimal image set in a comparison of noise-optimized linearly blended images (F_0.6) and noise-optimized virtual monoenergetic images (VMI+) evaluated by dual-energy computed tomography (DECT) for cardiac vein assessment. Material and Methods Thirty-four patients (mean age 58.2 ± 14.2 years) who underwent DECT due to chest pain were enrolled. Images were post-processed with the F_0.6, and VMI+ algorithms at energy levels in the range of 40–100 keV in 10-keV increments. Enhancement (HU), noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were objectively measured at two points in the great cardiac vein by consensus of two radiologists. Two blinded observers evaluated the subjective image quality of the great cardiac vein on a 4-point scale. Results HU, noise, and SNR peaked at 40 keV VMI+ ( P < 0.05) among 50–100 keV VMI+. CNR peaked at 100 keV VMI+; however, there were no significant differences compared to CNR images processed at 40–90 keV VMI+. HU and noise were significantly higher in 40 keV VMI+ than F_0.6 images; however, both SNR and CNR were significantly higher in F_0.6 images. An assessment of subjective vein delineation revealed that F_0.6 images had the highest scores Conclusion F_0.6 images were superior to VMI+ and provided the optimal image set for cardiac vein assessment.

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