Effect of Patient-Specific Coronary Flow Reserve Values on the Accuracy of MRI-Based Virtual Fractional Flow Reserve

Jackson Hair; Lucas Timmins; Retta El Sayed; Habib Samady; John Oshinski

doi:10.3389/fcvm.2021.663767

Effect of Patient-Specific Coronary Flow Reserve Values on the Accuracy of MRI-Based Virtual Fractional Flow Reserve

Front Cardiovasc Med. 2021 Jul 2:8:663767. doi: 10.3389/fcvm.2021.663767. eCollection 2021.

Authors

Jackson Hair^{1

2}, Lucas Timmins^{3

4}, Retta El Sayed², Habib Samady⁵, John Oshinski^{1

2}

Affiliations

¹ Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, United States.
² Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States.
³ Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States.
⁴ Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States.
⁵ Division of Cardiology, Department of Medicine, Emory School of Medicine, Atlanta, GA, United States.

Abstract

The purpose of this study is to investigate the effect of varying coronary flow reserve (CFR) values on the calculation of computationally-derived fractional flow reserve (FFR). CFR reflects both vessel resistance due to an epicardial stenosis, and resistance in the distal microvascular tissue. Patients may have a wide range of CFR related to the tissue substrate that is independent of epicardial stenosis levels. Most computationally based virtual FFR values such as FFR_CT do not measure patient specific CFR values but use a population-average value to create hyperemic flow conditions. In this study, a coronary arterial computational geometry was constructed using magnetic resonance angiography (MRA) data acquired in a patient with moderate CAD. Coronary flow waveforms under rest and stress conditions were acquired in 13 patients with phase-contrast magnetic resonance (PCMR) to calculate CFR, and these flow waveforms and CFR values were applied as inlet flow boundary conditions to determine FFR based on computational fluid dynamics (CFD) simulations. The stress flow waveform gave a measure of the functional significance of the vessel when evaluated with the physiologically-accurate behavior with the patient-specific CFR. The resting flow waveform was then scaled by a series of CFR values determined in the 13 patients to simulate how hyperemic flow and CFR affects FFR values. We found that FFR values calculated using non-patient-specific CFR values did not accurately predict those calculated with the true hyperemic flow waveform. This indicates that both patient-specific anatomic and flow information are required to accurately non-invasively assess the functional significance of coronary lesions.

Keywords: CFD; CFR; FFR; MRI; vFFR.

Abstract

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