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 FFRCT 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.
Highlights
Coronary artery disease (CAD) is responsible for half of all deaths attributed to cardiovascular disease, making it a leading cause of death globally [1, 2]
computational fluid dynamics (CFD) was used to determine Virtual fractional flow reserve (vFFR) values with various applied hyperemic flow conditions, including: (i) in vivo hyperemic flow by phasecontrast magnetic resonance (PCMR) measurement, (ii) basal flow scaled by the patientspecific coronary flow reserve (CFR), and (iii) basal flow scaled by population-average CFR estimates
Mean vFFR error was seen to monotonically decrease with increasing simulated CFR value, and, in general, the distribution of the error was seen to be larger with deviation from the cohort-average CFR, and increasing significance was observed on either end of the range of tested values (Figure 5A)
Summary
Coronary artery disease (CAD) is responsible for half of all deaths attributed to cardiovascular disease, making it a leading cause of death globally [1, 2]. The pressure is expected to scale linearly with the flow rate if the resistance is constant and minimized, which is achieved through induction of hyperemia using an injected vasodilator—such as adenosine—and averaging measurements across multiple cardiac cycles [3] This pressure ratio provides an approximation for the flow reduction caused by the plaque. Despite its proven efficacy, survey data from coronary interventions of intermediate stenoses have shown that FFR is used in only 6.1% of patients while 73.6% of patients are evaluated with angiography alone [6, 7] This underutilization can be attributed largely to the extra time and cost of the pressure wire, as well as the small but non-negligible risk to the patient. There have been considerable efforts in recent years to develop non-invasive alternative methods of determining FFR
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