The impact of image resolution on computation of fractional flow reserve: coronary computed tomography angiography versus 3-dimensional quantitative coronary angiography

  • Lili Liu
  • Wenjie Yang
  • Yasuomi Nagahara
  • Yingguang Li
  • Saeb R. Lamooki
  • Takashi Muramatsu
  • Pieter Kitslaar
  • Masayoshi Sarai
  • Yukio Ozaki
  • Peter Barlis
  • Fuhua Yan
  • Johan H. C. Reiber
  • Shengxian Tu
Original Paper


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.


Computational 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.


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Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Lili Liu
    • 1
  • Wenjie Yang
    • 2
  • Yasuomi Nagahara
    • 3
  • Yingguang Li
    • 4
  • Saeb R. Lamooki
    • 1
  • Takashi Muramatsu
    • 3
  • Pieter Kitslaar
    • 4
  • Masayoshi Sarai
    • 3
  • Yukio Ozaki
    • 3
  • Peter Barlis
    • 5
  • Fuhua Yan
    • 2
  • Johan H. C. Reiber
    • 4
  • Shengxian Tu
    • 1
  1. 1.Biomedical Instrument Institute, School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghaiChina
  2. 2.Department of Radiology, Rui Jin HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
  3. 3.Department of CardiologyFujita Health University HospitalToyoakeJapan
  4. 4.Division of Image Processing, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
  5. 5.Department of Medicine, Faculty of Medicine, Dentistry & Health SciencesThe University of MelbourneMelbourneAustralia

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