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Erschienen in: Machine Vision and Applications 8/2018

28.09.2018 | Special Issue Paper

Validation of right coronary artery lumen area from cardiac computed tomography against intravascular ultrasound

verfasst von: Hengfei Cui, Yong Xia, Yanning Zhang, Liang Zhong

Erschienen in: Machine Vision and Applications | Ausgabe 8/2018

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Abstract

Quantification of coronary artery disease (CAD) from cardiac computed tomography angiography (CTA) is important both structurally (lumen area stenosis) and functionally (combined with computational fluid dynamics to determine fractional flow reserve) for assessment of ischemic stenosis and to guide treatment. Hence, it is important to have CTA image processing technique for segmentation and reconstruction of coronary arteries. In this study, we developed segmentation and reconstruction techniques, based on fast marching and Runge–Kutta methods for centerline extraction, and surface mesh generation. The accuracy of the reconstructed models was validated with direct intravascular ultrasound (IVUS) measurements in 1950 cross sections within 4 arteries. High correlation was found between CTA and IVUS measurements for lumen areas (\(r=0.993\), \(p<0.001\)). Receiver-operating characteristic (ROC) curves showed excellent accuracies for detection of different cutoff values of cross-lumen area (5 \(\text {mm}^2\), 6 \(\text {mm}^2\), 7 \(\text {mm}^2\) and 8 \(\text {mm}^2\), all ROC values >0.99). We conclude that our technique has sufficient accuracy for quantifying coronary lumen area. The accuracy and efficiency demonstrated that our approach can facilitate quantitative evaluation of coronary stenosis and potentially help in real-time assessment of CAD.

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Metadaten
Titel
Validation of right coronary artery lumen area from cardiac computed tomography against intravascular ultrasound
verfasst von
Hengfei Cui
Yong Xia
Yanning Zhang
Liang Zhong
Publikationsdatum
28.09.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
Machine Vision and Applications / Ausgabe 8/2018
Print ISSN: 0932-8092
Elektronische ISSN: 1432-1769
DOI
https://doi.org/10.1007/s00138-018-0978-z

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