@Article{Dai2016,
journal="Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej",
issn="1734-9338",
volume="12",
number="1",
year="2016",
title="Three-dimensional modeling and numerical analysis of fractional flow reserve in human coronary arteries",
abstract=" Introduction : Noninvasive fractional flow reserve (FFR) computed from CT (FFR CT ) is a novel method for determining the physiologic significance of coronary artery disease (CAD). Several clinical trials have been conducted, but its diagnostic performance varied among different trials.   Aim : To determine the cut-off value of FFR CT  and its correlation with the gold standard used to diagnose CAD in clinical practice.   Material and methods : Forty patients with single vessel disease were included in our study. Computed tomography scan and coronary angiography with FFR were conducted for these patients. Three-dimensional geometric reconstruction and numerical analysis based on the computed tomographic angiogram (CTA) of coronary arteries were applied to obtain the values of FFR CT . The correlation between FFR CT  and the gold standard used in clinical practice was tested.   Results : For FFR CT , the best cut-off value was 0.76, with the sensitivity, specificity, positive predictive value and negative predictive values of 84.6%, 92.9%, 88% and 73.3%, respectively. The area under the receiver-operator characteristics curve was 0.945 (p < 0.0001). There was a good correlation of FFR CT  values with FFR values (r = 0.94, p < 0.0001), with a slight overestimation of FFR CT  as compared with measured FFR (mean difference 0.01 ±0.11, p < 0.05). For inter-observer agreement, the mean κ value was 0.69 (0.61 to 0.78) and for intra-observer agreement the mean κ value was 0.61 (0.50 to 0.72).   Conclusions : FFR CT  derived from CT of the coronary artery is a reliable non-invasive way providing reliable functional information of coronary artery stenosis.",
author="Dai, Neng
and Lv, Hui-Jie
and Xiang, Ya-Fei
and Fan, Bing
and Li, Wei-Ming
and Xu, Ya-Wei",
pages="25--31",
doi="10.5114/pwki.2016.56946",
url="http://dx.doi.org/10.5114/pwki.2016.56946"
}