Diagnostic performance of noninvasive fractional flow reserve derived from coronary computed tomography angiography in suspected coronary artery disease: the NXT trial (Analysis of Coronary Blood…
By B. Nørgaard, J. Leipsic, S. Gaur, S. Seneviratne, B. Ko, Hiroshi Ito, J. Jensen, L. Mauri, B. de Bruyne, H. Bezerra and 10 more. Journal of the American College of Cardiology, 2014
1,457 citations recorded by the source corpus.
Subfields: Radiology, Nuclear Medicine and Imaging, Surgery
View Paper: https://www.semanticscholar.org/paper/ba32e7e5e259c551238893e7d12735a63d05e784
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- Bogdan Georgescu
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Citations in the corpus
- A machine-learning approach for computation of fractional flow reserve from coronary computed tomography. (2016, methodology): “, computed tomography (CT) scans of the heart and the coronary arteries, have shown great promise in being able to predict invasive, lesion-specific FFR from patient’s medical images taken at resting conditions (9, 24, 32, 33, 36, 38, 43, 53).”
- 2018 ESC/EACTS Guidelines on myocardial revascularization. (2019, neutral): “A number of trials have shown that correlation between CT-derived FFR and invasive FFR is high.(2,3) The non-randomized PLATFORM (Prospective LongitudinAl Trial of FFRct: Outcome and Resource Impacts) study showed that in patients referred for invasive angiogra-”