A novel method for measuring absolute coronary blood flow and microvascular resistance in patients with ischaemic heart disease

Abstract

Aims: Ischaemic heart disease is the reduction of myocardial blood flow, caused by epicardial and/or microvascular disease. Both are common and prognostically important conditions, with distinct guideline-indicated management. Fractional flow reserve (FFR) is the current gold-standard assessment of epicardial coronary disease but is only a surrogate of flow and only predicts percentage flow changes. It cannot assess absolute (volumetric) flow or microvascular disease. The aim of this study was to develop and validate a novel method that predicts absolute coronary blood flow and microvascular resistance (MVR) in the catheter laboratory.

Methods and results: A computational fluid dynamics (CFD) model was used to predict absolute coronary flow (QCFD) and coronary MVR using data from routine invasive angiography and pressure-wire assessment. QCFD was validated in an in vitro flow circuit which incorporated patient-specific, three-dimensional printed coronary arteries; and then in vivo, in patients with coronary disease. In vitro, QCFD agreed closely with the experimental flow over all flow rates [bias +2.08 mL/min; 95% confidence interval (error range) -4.7 to +8.8 mL/min; R2 = 0.999, P < 0.001; variability coefficient <1%]. In vivo, QCFD and MVR were successfully computed in all 40 patients under baseline and hyperaemic conditions, from which coronary flow reserve (CFR) was also calculated. QCFD-derived CFR correlated closely with pressure-derived CFR (R2 = 0.92, P < 0.001). This novel method was significantly more accurate than Doppler-wire-derived flow both in vitro (±6.7 vs. ±34 mL/min) and in vivo (±0.9 vs. ±24.4 mmHg).

Conclusions: Absolute coronary flow and MVR can be determined alongside FFR, in absolute units, during routine catheter laboratory assessment, without the need for additional catheters, wires or drug infusions. Using this novel method, epicardial and microvascular disease can be discriminated and quantified. This comprehensive coronary physiological assessment may enable a new level of patient stratification and management.

Keywords: Computational fluid dynamics; Coronary angiography; Coronary blood flow; Coronary microvascular dysfunction; Coronary physiology.

Figure 1

The computational method for computing absolute coronary blood flow. Coronary angiographic images are used to reconstruct the coronary anatomy. Pressure data are used to tune boundary conditions. CFD simulation computes the volumetric flow rate (Q_CFD), which enables coronary microvascular resistance (MVR), stenosis resistance (SR), and coronary flow reserve (CFR) to be calculated automatically.

Figure 2

The in vitro test-rig used for validating the method for determining absolute flow. A gear pump (a) (TA Instruments, USA) delivered steady flow through the circuit. In the pulsatile experiments, a pulsatile manifold (Bose Corp, USA) was used to deliver pulsatile flow. Both devices were controlled by WinTest^® software (Bose) (c). A compliance chamber (d) was used in tandem with the pump and manifold to remove high frequency signal artefact. The blood analogue fluid (40/60 glycerol/water, viscosity 0.0035 Pa⋅s, 1082 kg⋅m⁻³ at room temperature) passed through the 3D printed artery (e) reconstructed from patient data. Clinical haemostatic valves were used to instrument the system with pressure and flow transducers through f. The photographs demonstrate a 3D printed artery within the circuit and the pressure wire tip can be seen on the zoomed image (g). The flow rate was regularly calibrated by measuring the volume of fluid draining into the reservoir chamber (not seen in this idealized diagram).

Figure 3

Bland–Altman plots demonstrating the accuracy of Q_CFD and Q_Dop. (A) The accuracy of the novel Q_CFD method over all flow rates [bias +2.08 mL/min; limits of agreement (±1.96 SD) ±6.75 mL/min]. (B) The accuracy of Q_CFD for cases with Re ≤ 500 (bias +0.31 mL/min; limits of agreement ±5.0 mL/min). (C) The accuracy of the Doppler method (Q_Dop) over all flow rates (bias −14.9 mL/min; limits of agreement ±33.5 mL/min). (D) The accuracy of the Doppler method for cases with Re ≤ 500 (bias −8.34 mL/min; limits of agreement ±28.1 mL/min). The solid line indicates the bias (mean delta) and the broken lines indicate the limits of agreement (±1.96 SD). Both methods were plotted against the gold-standard of the calibrated experimental flow rate (Q_exp). Note the difference in Y-axis scale between the two methods. Each dot represents the average of three recordings, i.e. 70 data points and 210 samples.

Figure 4

Pressure gradient vs. flow during in vitro testing for each of the five models over all flow rates. There was close agreement between the experimental (gold-standard) flow (Q_exp) indicated by the black line and the flow rate computed by the novel method (Q_CFD) indicated by the grey line (R² 0.999, P < 0.001, by Pearson’s correlation coefficient). The vertical dashed line represents the transition between physiological (Re < 500) and supra-physiological (Re ≥ 500) flow rates. For Q_exp, error bars represent the maximum and minimum values obtained from three measurements. Because CFD results are inherently reproducible given identical setup parameters, error bars for the Q_CFD model were calculated from simulation data representing the influence of small errors in viscosity and density of the experimental blood analogue. Each data point represents the mean of three repeated measurements, i.e. 42 samples per model and 210 all together.

Figure 5

Example result from the virtuQ software graphical user interface. Absolute flow (mL/min), resting Pd/Pa, FFR, microvascular resistance (MVR), stenosis resistance (SR), and coronary flow reserve (CFR) are reported alongside the angiogram images (for reference), interactive 3D reconstructed artery (physiologically colour mapped) and a 3D vessel-sizing application to facilitate potential stent choice. The operator can select any two points within the vessel and the results update live. In this case, the FFR is negative, but flow, according to CFR, is borderline, likely due to the increased MVR.