| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 2964343 | Journal of Cardiovascular Computed Tomography | 2015 | 6 Pages |
•Subtraction is a novel technique.•Designed to more accurately assess stenosis in coronaries with calcium or stents.•Subtraction appears feasible.•Subtraction could lead to improvement in reader confidence and diagnostic accuracy.
BackgroundThe 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.MethodsForty-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 (CCTAconv) and a subtracted CCTA (CCTAsub), 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 CCTAconv as motion-free coronary segments with calcification or stent and low reader confidence. The effect of CCTAsub was assessed. No approval from the ethics committee was required according to Danish law.ResultsA 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 CCTAsub compared to CCTAconv without loss in negative predictive value.ConclusionsOur 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.
