Blooming Artifact Reduction in Coronary Artery Calcification by A New De-blooming Algorithm: Initial Study

Abstract The aim of this study was to investigate the use of de-blooming algorithm in coronary CT angiography (CCTA) for optimal evaluation of calcified plaques. Calcified plaques were simulated on a coronary vessel phantom and a cardiac motion phantom. Two convolution kernels, standard (STND) and h...

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Autores principales:	Ping Li, Lei Xu, Lin Yang, Rui Wang, Jiang Hsieh, Zhonghua Sun, Zhanming Fan, Jonathon A. Leipsic
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/8027e5fb090b4a72ba74791e9250a140
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spelling	oai:doaj.org-article:8027e5fb090b4a72ba74791e9250a1402021-12-02T16:08:03ZBlooming Artifact Reduction in Coronary Artery Calcification by A New De-blooming Algorithm: Initial Study10.1038/s41598-018-25352-52045-2322https://doaj.org/article/8027e5fb090b4a72ba74791e9250a1402018-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-018-25352-5https://doaj.org/toc/2045-2322Abstract The aim of this study was to investigate the use of de-blooming algorithm in coronary CT angiography (CCTA) for optimal evaluation of calcified plaques. Calcified plaques were simulated on a coronary vessel phantom and a cardiac motion phantom. Two convolution kernels, standard (STND) and high-definition standard (HD STND), were used for imaging reconstruction. A dedicated de-blooming algorithm was used for imaging processing. We found a smaller bias towards measurement of stenosis using the de-blooming algorithm (STND: bias 24.6% vs 15.0%, range 10.2% to 39.0% vs 4.0% to 25.9%; HD STND: bias 17.9% vs 11.0%, range 8.9% to 30.6% vs 0.5% to 21.5%). With use of de-blooming algorithm, specificity for diagnosing significant stenosis increased from 45.8% to 75.0% (STND), from 62.5% to 83.3% (HD STND); while positive predictive value (PPV) increased from 69.8% to 83.3% (STND), from 76.9% to 88.2% (HD STND). In the patient group, reduction in calcification volume was 48.1 ± 10.3%, reduction in coronary diameter stenosis over calcified plaque was 52.4 ± 24.2%. Our results suggest that the novel de-blooming algorithm could effectively decrease the blooming artifacts caused by coronary calcified plaques, and consequently improve diagnostic accuracy of CCTA in assessing coronary stenosis.Ping LiLei XuLin YangRui WangJiang HsiehZhonghua SunZhanming FanJonathon A. LeipsicNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 8, Iss 1, Pp 1-8 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ping Li Lei Xu Lin Yang Rui Wang Jiang Hsieh Zhonghua Sun Zhanming Fan Jonathon A. Leipsic Blooming Artifact Reduction in Coronary Artery Calcification by A New De-blooming Algorithm: Initial Study
description	Abstract The aim of this study was to investigate the use of de-blooming algorithm in coronary CT angiography (CCTA) for optimal evaluation of calcified plaques. Calcified plaques were simulated on a coronary vessel phantom and a cardiac motion phantom. Two convolution kernels, standard (STND) and high-definition standard (HD STND), were used for imaging reconstruction. A dedicated de-blooming algorithm was used for imaging processing. We found a smaller bias towards measurement of stenosis using the de-blooming algorithm (STND: bias 24.6% vs 15.0%, range 10.2% to 39.0% vs 4.0% to 25.9%; HD STND: bias 17.9% vs 11.0%, range 8.9% to 30.6% vs 0.5% to 21.5%). With use of de-blooming algorithm, specificity for diagnosing significant stenosis increased from 45.8% to 75.0% (STND), from 62.5% to 83.3% (HD STND); while positive predictive value (PPV) increased from 69.8% to 83.3% (STND), from 76.9% to 88.2% (HD STND). In the patient group, reduction in calcification volume was 48.1 ± 10.3%, reduction in coronary diameter stenosis over calcified plaque was 52.4 ± 24.2%. Our results suggest that the novel de-blooming algorithm could effectively decrease the blooming artifacts caused by coronary calcified plaques, and consequently improve diagnostic accuracy of CCTA in assessing coronary stenosis.
format	article
author	Ping Li Lei Xu Lin Yang Rui Wang Jiang Hsieh Zhonghua Sun Zhanming Fan Jonathon A. Leipsic
author_facet	Ping Li Lei Xu Lin Yang Rui Wang Jiang Hsieh Zhonghua Sun Zhanming Fan Jonathon A. Leipsic
author_sort	Ping Li
title	Blooming Artifact Reduction in Coronary Artery Calcification by A New De-blooming Algorithm: Initial Study
title_short	Blooming Artifact Reduction in Coronary Artery Calcification by A New De-blooming Algorithm: Initial Study
title_full	Blooming Artifact Reduction in Coronary Artery Calcification by A New De-blooming Algorithm: Initial Study
title_fullStr	Blooming Artifact Reduction in Coronary Artery Calcification by A New De-blooming Algorithm: Initial Study
title_full_unstemmed	Blooming Artifact Reduction in Coronary Artery Calcification by A New De-blooming Algorithm: Initial Study
title_sort	blooming artifact reduction in coronary artery calcification by a new de-blooming algorithm: initial study
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/8027e5fb090b4a72ba74791e9250a140
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Blooming Artifact Reduction in Coronary Artery Calcification by A New De-blooming Algorithm: Initial Study

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