Shengxian Tu1, Emanuele Barbato2, Zsolt Köszegi3, Junqing Yang4, Zhonghua Sun5, Niels R Holm6, Balázs Tar3, Yingguang Li7, Dan Rusinaru2, William Wijns2, Johan H C Reiber7. 1. Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands. Electronic address: S.T.Tu@lumc.nl. 2. Cardiovascular Center Aalst, Onze-Lieve-Vrouwziekenhuis (OLV) Hospital, Aalst, Belgium. 3. Invasive Cardiology Laboratory, Jósa András Teaching Hospital, Nyíregyháza, Hungary. 4. Department of Cardiology, Guangdong General Hospital, Guangzhou, China. 5. Department of Cardiology, TEDA International Cardiovascular Hospital, Tianjin, China. 6. Department of Cardiology, Aarhus University Hospital, Skejby, Denmark. 7. Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands.
Abstract
OBJECTIVES: This study sought to present a novel computer model for fast computation of myocardial fractional flow reserve (FFR) and to evaluate it in patients with intermediate coronary stenoses. BACKGROUND: FFR is an indispensable tool to identify individual coronary stenoses causing ischemia. Calculation of FFR from x-ray angiographic data may increase the utility of FFR assessment. METHODS: Consecutive patients with intermediate coronary stenoses undergoing pressure wire-based FFR measurements were analyzed by a core laboratory. Three-dimensional quantitative coronary angiography (QCA) was performed and the mean volumetric flow rate at hyperemia was calculated using TIMI (Thrombolysis In Myocardial Infarction) frame count combined with 3-dimensional QCA. Computational fluid dynamics was applied subsequently with a novel strategy for the computation of FFR. Diagnostic performance of the computed FFR (FFRQCA) was assessed using wire-based FFR as reference standard. RESULTS: Computation of FFRQCA was performed on 77 vessels in 68 patients. Average diameter stenosis was 46.6 ± 7.3%. FFRQCA correlated well with FFR (r = 0.81, p < 0.001), with a mean difference of 0.00 ± 0.06 (p = 0.541). Applying the FFR cutoff value of ≤0.8 to FFRQCA resulted in 18 true positives, 50 true negatives, 4 false positives, and 5 false negatives. The area under the receiver-operating characteristic curve was 0.93 for FFRQCA, 0.73 for minimum lumen area, and 0.65 for percent diameter stenosis. CONCLUSIONS: Computation of FFRQCA is a novel method that allows the assessment of the functional significance of intermediate stenosis. It may emerge as a safe, efficient, and cost-reducing tool for evaluation of coronary stenosis severity during diagnostic angiography.
OBJECTIVES: This study sought to present a novel computer model for fast computation of myocardial fractional flow reserve (FFR) and to evaluate it in patients with intermediate coronary stenoses. BACKGROUND: FFR is an indispensable tool to identify individual coronary stenoses causing ischemia. Calculation of FFR from x-ray angiographic data may increase the utility of FFR assessment. METHODS: Consecutive patients with intermediate coronary stenoses undergoing pressure wire-based FFR measurements were analyzed by a core laboratory. Three-dimensional quantitative coronary angiography (QCA) was performed and the mean volumetric flow rate at hyperemia was calculated using TIMI (Thrombolysis In Myocardial Infarction) frame count combined with 3-dimensional QCA. Computational fluid dynamics was applied subsequently with a novel strategy for the computation of FFR. Diagnostic performance of the computed FFR (FFRQCA) was assessed using wire-based FFR as reference standard. RESULTS: Computation of FFRQCA was performed on 77 vessels in 68 patients. Average diameter stenosis was 46.6 ± 7.3%. FFRQCA correlated well with FFR (r = 0.81, p < 0.001), with a mean difference of 0.00 ± 0.06 (p = 0.541). Applying the FFR cutoff value of ≤0.8 to FFRQCA resulted in 18 true positives, 50 true negatives, 4 false positives, and 5 false negatives. The area under the receiver-operating characteristic curve was 0.93 for FFRQCA, 0.73 for minimum lumen area, and 0.65 for percent diameter stenosis. CONCLUSIONS: Computation of FFRQCA is a novel method that allows the assessment of the functional significance of intermediate stenosis. It may emerge as a safe, efficient, and cost-reducing tool for evaluation of coronary stenosis severity during diagnostic angiography.
Authors: Juan Luis Gutiérrez-Chico; Carlos Cortés; Miłosz Jaguszewski; Michele Schincariol; Ignacio J Amat-Santos; Juan A Franco-Peláez; Grzegorz Żuk; Dariusz Ciećwierz; Wojciech Wojakowski; Felipe Navarro; Shengxian Tu; Borja Ibáñez Journal: Cardiol J Date: 2019-07-01 Impact factor: 2.737
Authors: Shengxian Tu; Tim P van de Hoef; Young-Hak Kim; Javier Escaned; William Wijns Journal: Int J Cardiovasc Imaging Date: 2017-07 Impact factor: 2.357
Authors: Xinlei Wu; Clemens von Birgelen; Zehang Li; Su Zhang; Jiayue Huang; Fuyou Liang; Yingguang Li; William Wijns; Shengxian Tu Journal: Int J Cardiovasc Imaging Date: 2018-02-03 Impact factor: 2.357
Authors: Xinlei Wu; Clemens von Birgelen; Su Zhang; Daixin Ding; Jiayue Huang; Shengxian Tu Journal: Int J Cardiovasc Imaging Date: 2019-05-03 Impact factor: 2.357