Abstract
Computed tomography angiography (CCTA)-based calculations of fractional flow reserve (FFR) can improve the diagnostic performance of CCTA for physiologically significant stenosis but the computational resource requirements are high. This study aimed at establishing a simple and efficient algorithm for computing simulated FFR (S-FFR). A total of 107 patients who underwent CCTA and invasive FFR measurements were enrolled in the study. S-FFR was calculated using 145 evaluable coronary arteries with off-the-shelf softwares. FFR ≤ 0.80 was a reference threshold for diagnostic performance of diameter stenosis (DS) ≥ 50%, DS ≥ 70%, or S-FFR ≤ 0.80. FFR ≤ 0.80 was identified in 78 vessels (54%). In per-vessel analysis, S-FFR showed good correlation (r = 0.83) and agreement (mean difference = 0.02 ± 0.08) with FFR. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of S-FFR ≤ 0.80 for FFR ≤ 0.80 were 84%, 92%, 92%, 83%, and 88%, respectively. S-FFR ≤ 0.80 showed much higher predictive performance for FFR ≤ 0.80 compared with DS ≥ 50% or DS ≥ 70% (c-statistics = 0.92 vs. 0.58 or 0.65, p < 0.001, all). The classification agreement between FFR and S-FFR was > 80% when the average of FFR and S-FFR was < 0.76 or > 0.86. Per-patient analysis showed consistent results. In this study, a simple and computationally efficient simulated FFR (S-FFR) algorithm is designed and tested using non-proprietary off-the-shelf software. This algorithm may expand the accessibility of clinical applications for non-invasive coronary physiology study.
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Abbreviations
- 3D:
-
3-Dimensional
- CAG:
-
Coronary angiography
- CFD:
-
Computational flow dynamics
- CCTA:
-
Coronary computed tomography angiography
- DS:
-
Diameter stenosis
- FFR:
-
Fractional flow reserve
- IDI:
-
Integrated discrimination improvement
- NPV:
-
Negative predictive value
- NRI:
-
Net reclassification improvement
- PPV:
-
Positive predictive value
- ROC:
-
Receive-operating characteristics
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Acknowledgements
We thank Seon A Jeong and So Hyeon Park for their excellent and devoted contributions.
Funding
This study was funded by This study was supported by Korean Society of Circulation Grant (201301-01), Korean Society of Interventional Cardiology Grant [2014-1], Samsung Biomedical Research Institute Grant [GL1B33211], Samsung Medical Center Heart Vascular and Stroke Institute Clinical Research Project (OTC1601861), and National Research Foundation of Korea (2017R1A2B3010918).
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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
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Samsung Medical Center institutional review board approved this study investigating anonymized image and physiological data and informed consent was waived.
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Han, H., Bae, Y.G., Hwang, S.T. et al. Computationally simulated fractional flow reserve from coronary computed tomography angiography based on fractional myocardial mass. Int J Cardiovasc Imaging 35, 185–193 (2019). https://doi.org/10.1007/s10554-018-1432-z
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DOI: https://doi.org/10.1007/s10554-018-1432-z