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Feasibility of coronary calcium and stent image subtraction using 320-detector row CT angiography.

Authors :
Fuchs, Andreas
Kühl, J. Tobias
Chen, Marcus Y.
Helqvist, Steffen
Razeto, Marco
Arakita, Kazumasa
Steveson, Chloe
Arai, Andrew E.
Kofoed, Klaus F.
Source :
Journal of Cardiovascular Computed Tomography; Sep2015, Vol. 9 Issue 5, p393-398, 6p
Publication Year :
2015

Abstract

Background The reader confidence and diagnostic accuracy of coronary CT angiography (CCTA) can be compromised by the presence of calcified plaques and stents causing blooming artifacts. Compared to conventional invasive coronary angiography (ICA), this may cause an overestimation of stenosis severity leading to false-positive results. In a pilot study, we tested the feasibility of a new coronary calcium image subtraction algorithm in relation to reader confidence and diagnostic accuracy. Methods Forty-three patients underwent clinically indicated ICA and CCTA using a 320-detector row CT. Median Agatston score was 510. Two data sets were reconstructed: a conventional CCTA (CCTA conv ) and a subtracted CCTA (CCTA sub ), where calcifications detected on noncontrast images were subtracted from the CCTA. Reader confidence and concordance with ICA for identification of >50% stenosis were recorded. We defined target segments on CCTA conv as motion-free coronary segments with calcification or stent and low reader confidence. The effect of CCTA sub was assessed. No approval from the ethics committee was required according to Danish law. Results A total of 76 target segments were identified. The use of coronary calcium image subtraction improved the reader confidence in 66% of these segments. In target segments, specificity (86% vs 65%; P < .01) and positive predictive value (71% vs 51%, P = .03) were improved using CCTA sub compared to CCTA conv without loss in negative predictive value. Conclusions Our initial experience with coronary calcium image subtraction suggests that it is feasible and could lead to an improvement in reader confidence and diagnostic accuracy for identification of significant coronary artery disease. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19345925
Volume :
9
Issue :
5
Database :
Supplemental Index
Journal :
Journal of Cardiovascular Computed Tomography
Publication Type :
Academic Journal
Accession number :
109493564
Full Text :
https://doi.org/10.1016/j.jcct.2015.03.016