INTRACORONARY FLOW VELOCITY ASSESSMENT

Flow measurements were performed in a reference coronary artery (DS <30% on visual estimation) using a 0.014-inch Doppler sensor-tipped guidewire (FloWire; Endosonics, Rancho Cordova, CA, USA, currently ComboWire™ XT; Philips Volcano, San Diego, CA, USA). Doppler flow velocity measurements were obtained during resting conditions (baseline average peak flow velocity [bAPV]), as well as during hyperaemia (hyperaemic average peak flow velocity [hAPV]) induced by an intracoronary bolus injection of adenosine (12-15 μg for the right coronary artery and 18-20 μg for the left coronary artery). Doppler flow velocity signals were used to calculate CFR, defined as the ratio of hAPV to bAPV. The definition of CFC was described previously elsewhere11,14,15. In brief, normal CFC was defined as CFR ≥2.8, as encountered in patients with risk factors for ischaemic heart disease (IHD) without epicardial narrowing14, with its corresponding hAPV ≥49.0 cm/s. Mildly reduced CFC was defined as CFR <2.8 but >2.1, which reflects the upper limit of reported CFR cut-off values for inducible ischaemia, and the corresponding hAPV <49.0 and >33.0 cm/s, respectively. Moderately reduced CFC was defined as CFR ≤2.1 and >1.7, analogous to the reported range of CFR cut-off values for inducible myocardial ischaemia, and the corresponding hAPV ≤33.0 and >26.0 cm/s, respectively. Finally, severely reduced CFC was defined as CFR ≤1.7, and corresponding hAPV ≤26.0 cm/s.

CFR AND CFC

Overall, mean CFR was 2.87±0.76 (Figure 1A). Men had higher mean CFR than women (2.96±0.04 versus 2.61±0.07, p=0.001). There was no significant difference in CFR between interrogated vessels: mean CFR was 2.83±0.79 for the RCx, 2.91±0.73 for the LAD and 2.90±0.75 for the RCA (p=0.16).

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Figure 1

Overall CFR and CFC distribution. A) Overall CFR distribution. CFR mean±SD was 2.87±0.76. B) Overall CFC distribution based on CFR and hAPV.

Overall CFC distribution is shown in Figure 1B. Mean CFR, bAPV, and hAPV across the CFC categories are shown in Table 2. Mean CFR was 3.14±0.70 for normal CFC (n=278), 2.28±0.30 for mildly reduced CFC (n=90), 1.80±0.27 for moderately reduced CFC (n=19) and 1.2±0.35 for severely reduced CFC (n=3). CFR and CFC distribution per vessel is shown in Table 3.

DETERMINANTS OF CFR IN REFERENCE VESSELS

The best model for CFR identified by AIC included age, female gender, a history of MI, hypercholesterolaemia, diastolic blood pressure, oral nitrates and RPP. Univariate linear regression analysis and subsequent multivariate linear regression analysis (Table 4) revealed age (slope –0.014, 95% CI: –0.021 to –0.007, p<0.001), female gender (slope –0.212, 95% CI: –0.376 to –0.030, p=0.021) and oral nitrates (slope 0.162, 95% CI: 0.003 to 0.321, p=0.046) to be independently associated with CFR. The relationship between CFR and age is shown in Figure 2.

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Figure 2

Inverse correlation between CFR and age (A), bAPV and age (B), and hAPV and age (C).

RESTING AND HYPERAEMIC FLOW IN CFR CALCULATION

The parameters associated with CFR in angiographically non-obstructed vessels listed above were subsequently evaluated for their association with bAPV and hAPV to determine whether their impact on CFR derived from an effect on resting or hyperaemic flow (Table 5, Table 6). Increasing age was associated with a decrease in hAPV (slope –0.194, p=0.024), but not in bAPV (slope 0.044, p=0.223) (Figure 2). Gender was associated with bAPV, where women had higher bAPV than men (mean bAPV 19.4±8.3 cm/s versus 17.3±7.5 cm/s, slope 2.129, p=0.017) (Figure 3), but there was no association between gender and hAPV (slope –2.33; p=0.275). RPP was associated with bAPV (slope 0.0007; p<0.001), but not with hAPV (slope 0.0006; p=0.174). A history of MI, hypercholesterolaemia and current or prior smoking were not associated with bAPV (p=0.710, p=0.231 and p=0.271, respectively) or hAPV (p=0.576, p=0.915 and p=0.063, respectively).

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Figure 3

Correlation between CFR and bAPV in men (A) and women (B).

ORIGIN OF ASSOCIATION BETWEEN CLINICAL AND HAEMODYNAMIC PARAMETERS AND FLOW ABNORMALITIES

CFR is a physiological parameter that has been extensively validated and is associated with improved risk stratification regarding major adverse cardiac events (MACE), regardless of the methodology used for its assessment6,17,18,19. However, in part due to its presumed sensitivity to variations in resting haemodynamics, its implementation in larger clinical practice has been limited. In the present study, age, female gender and oral nitrates significantly influenced CFR in a reference vessel. Interestingly, ageing was associated with lower CFR, mainly driven by a decrease in hAPV, as documented previously8,20. Female gender, in contrast, was associated with lower CFR, potentially due to a lower vascular tone and subsequently higher bAPV21. Cardiac workload estimated by RPP has generally been associated with an increase in both bAPV and hAPV22,23. Although a decrease in CFR is generally assumed with increases in cardiac workload, a simultaneous increase in maximal hyperaemic flow together with a proportional increase of baseline flow can result in a normal CFR24. Furthermore, de Bruyne et al25 found a significant association between CFR and haemodynamic changes in heart rate, blood pressure and contractility, but measured CFR under clinically challenging haemodynamic situations in which physiological assessment is usually not applied, since vasodilatory capacity is naturally impaired in these situations.

Oral nitrates induce vasodilation and a subsequent increase in coronary blood flow to the myocardium, resulting in higher CFR and CFC26.

Diabetes mellitus was not associated with lower CFR values in the present cohort. However, we found that diabetic patients had higher bAPV compared with non-diabetic patients (20.5±10.4 cm/s vs 17.6±7.5 cm/s, for diabetics and non-diabetics, respectively; p=0.046) but similar hAPV (52.6±18.4 cm/s vs 48.2±18.4 cm/s, for diabetics and non-diabetics, respectively; p=0.182). Higher bAPV in diabetics has been previously documented, and has been attributed to malfunctioning of the myocardial metabolism27,28, as well as impaired endothelial function, or even structural anatomical changes of the microcirculatory vasculature9,29. Although mean CFR values were not different between diabetics and non-diabetics in this study, higher resting flows evidently lead to lower CFR values in the individual patient and may impact on clinical decision making. Such an impact of diabetes on resting flow would be vanquished by using CFC.

Despite these considerations, the prognostic value of CFR in angiographically non-obstructed coronary arteries remains undisputed. Several studies have documented that lower CFR is associated with an increased risk of MACE, both in vessels with6,30 and in those without31 obstructive CAD.

THE CONCEPT OF CFC: hAPV COMPLEMENTING CFR

The concept of CFC was originally validated using PET imaging12, and has been extrapolated to invasive coronary flow measurements11. These studies suggested an improved risk stratification by using CFC over the application of CFR alone, although more definitive data are required for confirmation of these findings. In the present study, we found that CFC is mostly independent of clinical and haemodynamic factors except for age, overcoming most of the potential limitations of using CFR alone. By integrating CFR and hAPV, CFC is less prone to variations in baseline flow compared with CFR. As documented in the present study, this applies to alterations in flow in diabetics, female patients, and increases in cardiac workload. In the present study, age was the only parameter associated with lower CFC, which is anticipated since age impacts on CFR through a solitary decrease in hAPV, leading to a decrease in CFC through impairment of both CFR and hyperaemic flow.