The impact of image resolution on computation of fractional flow reserve: coronary computed tomography angiography versus 3-dimensional quantitative coronary angiography
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Calculation of fractional flow reserve (FFR) based on computational fluid dynamics (CFD) requires reconstruction of patient-specific coronary geometry and estimation of hyperemic flow rate. Coronary computed tomography angiography (CCTA) and invasive coronary angiography (ICA) are two dominating imaging modalities used for the geometrical reconstruction. Our aim was to investigate the impact of image resolution as inherently associated with these two imaging modalities on geometrical reconstruction and subsequent FFR calculation. Patients with mild or intermediate coronary stenoses who underwent both CCTA and ICA were included. CCTA images were acquired either by 320-row area detector CT or by 128-slice dual-source CT. Two geometrical models were reconstructed separately from CCTA and ICA, from which FFRCTA and FFRQCA were subsequently calculated using CFD simulations, applying the same hyperemic flow rate derived from the ICA images at the inlet boundaries. A total of 57 vessels in 41 patients were analyzed. Average diameter stenosis was 43.4 ± 10.8 % by 3D QCA. Reasonably good correlation between FFRCTA and FFRQCA was observed (r = 0.71, p < 0.001). The difference between FFRCTA and FFRQCA was correlated with the deviation between minimal lumen areas by CCTA and by ICA (ρ = 0.34, p = 0.01), but not with plaque volume (ρ = −0.09, p = 0.51) or calcified plaque volume (ρ = 0.01, p = 0.95). Applying the cutoff value of ≤0.8 to both FFRCTA and FFRQCA, the agreement between FFRCTA and FFRQCA in discriminating functional significant stenoses was moderate (kappa 0.47, p < 0.001). Disagreement was found in 10 (17.5 %) vessels. Acceptable correlation between FFRCTA and FFRQCA was observed, while their agreement in distinguishing functional significant stenosis was moderate. Our results suggest that image resolution has a significant impact on FFR computation.
KeywordsComputational fluid dynamics Coronary computed tomography angiography Fractional flow reserve Quantitative coronary angiography
320-row area detector CT
Coronary computed tomography angiography
Computational fluid dynamics
128-slice dual-source CT
Fractional flow reserve
Invasive coronary angiography
Minimum lumen area
Optical coherence tomography
Quantitative coronary angiography
Volumetric flow rate
This work was supported in part by the Natural Science Foundation of China under Grant 31500797 and 81501467. Shengxian Tu would also like to acknowledge the support by the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning and by Shanghai Pujiang Program (No. 15PJ1404200).
Compliance with ethical standards
Conflict of interest
Y. Li and P. Kitslaar are employed by Medis medical imaging systems bv and have a research appointment at the Leiden University Medical Center (LUMC). J. H. C. Reiber is the CEO of Medis, and has a part-time appointment at LUMC as Prof. of Medical Imaging. S. Tu receives research grant support from Medis. All other authors declare that they have no conflict of interest.
- 16.Sun G et al (1016) 320-detector row CT coronary angiography: effects of heart rate and heart rate variability on image quality, diagnostic accuracy and radiation exposure. Br J Radiol 2012(85):e388–e394Google Scholar
- 18.Dehmer GJ et al (2012) A contemporary view of diagnostic cardiac catheterization and percutaneous coronary intervention in the United States: a report from the CathPCI Registry of the National Cardiovascular Data Registry, 2010 through June 2011. J Am Coll Cardiol 60(20):2017–2031CrossRefPubMedGoogle Scholar
- 19.Eric KW, Poon UH, Thondapu V, Andrew SH, Ooi SM, Asrar-Ul-Haq M, Foin N, Tu S, Chin C, Monty JP, Marusic I, Barlis P (2015) Advances in three-dimensional coronary imaging and computational fluid dynamics: Is virtual fractional flow reserve more than just a pretty picture? J Coron Artery Dis. doi: 10.1097/MCA.0000000000000219 (in press)Google Scholar
- 20.Koo BK et al (2011) Diagnosis of ischemia-causing coronary stenoses by noninvasive fractional flow reserve computed from coronary computed tomographic angiograms. Results from the prospective multicenter DISCOVER-FLOW (Diagnosis of Ischemia-Causing Stenoses Obtained Via Noninvasive Fractional Flow Reserve) study. J Am Coll Cardiol 58(19):1989–1997CrossRefPubMedGoogle Scholar
- 21.Norgaard BL et al (2014) 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 Flow Using CT Angiography: Next Steps). J Am Coll Cardiol 63(12):1145–1155CrossRefPubMedGoogle Scholar
- 23.Bourantas CV et al (2009) Comparison of quantitative coronary angiography with intracoronary ultrasound Can quantitative coronary angiography accurately estimate the severity of a luminal stenosis? Angiography 60(2):169–179Google Scholar