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

Authors :
Kim, Gyeong Min
Choo, Ki Seok
Kim, Jin Hyeok
Hwang, Jae-Yeon
Park, Chan Kyu
Lee, Ji Won
Lim, Soo Jin
Source :
Acta Radiologica. May2021, Vol. 62 Issue 5, p594-602. 9p.
Publication Year :
2021

Abstract

<bold>Background: </bold>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.<bold>Purpose: </bold>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.<bold>Material and Methods: </bold>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.<bold>Results: </bold>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.<bold>Conclusion: </bold>F_0.6 images were superior to VMI+ and provided the optimal image set for cardiac vein assessment. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02841851
Volume :
62
Issue :
5
Database :
Academic Search Index
Journal :
Acta Radiologica
Publication Type :
Academic Journal
Accession number :
150228545
Full Text :
https://doi.org/10.1177/0284185120933242