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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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Abstract

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.

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Abbreviations

ADCT:

320-row area detector CT

CCTA:

Coronary computed tomography angiography

CFD:

Computational fluid dynamics

DSCT:

128-slice dual-source CT

FFR:

Fractional flow reserve

ICA:

Invasive coronary angiography

MLA:

Minimum lumen area

OCT:

Optical coherence tomography

QCA:

Quantitative coronary angiography

VFR:

Volumetric flow rate

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Acknowledgments

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).

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    Authors and Affiliations

    1. Biomedical Instrument Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China

      Lili Liu, Saeb R. Lamooki & Shengxian Tu

    2. Department of Radiology, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

      Wenjie Yang & Fuhua Yan

    3. Department of Cardiology, Fujita Health University Hospital, Toyoake, Japan

      Yasuomi Nagahara, Takashi Muramatsu, Masayoshi Sarai & Yukio Ozaki

    4. Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands

      Yingguang Li, Pieter Kitslaar & Johan H. C. Reiber

    5. Department of Medicine, Faculty of Medicine, Dentistry & Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia

      Peter Barlis

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    Correspondence to Shengxian Tu.

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    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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    Lili Liu and Wenjie Yang have contributed equally to this work.

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    Liu, L., Yang, W., Nagahara, Y. et al. The impact of image resolution on computation of fractional flow reserve: coronary computed tomography angiography versus 3-dimensional quantitative coronary angiography. Int J Cardiovasc Imaging 32, 513–523 (2016). https://doi.org/10.1007/s10554-015-0797-5

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