Sex-Specific Interpretation of Coronary Flow Reserve and Fractional Flow Reserve Metrics, Including Their Companions

Coronary Flow Velocity Reserve by Echocardiography: Beyond Atherosclerotic Disease

Coronary flow velocity reserve (CFVR) is defined as the ratio between coronary flow velocity during maximal hyperemia and coronary flow at rest. Gold-standard techniques to measure CFVR are either invasive or require radiation and are therefore inappropriate for large-scale adoption. More than 30 years ago, echocardiography was demonstrated to be a reliable tool to assess CFVR, and its field of application rapidly expanded. Although initially validated to assess the hemodynamic relevance of a coronary stenosis, CFVR by echocardiography was later used to investigate coronary microcirculation. Microvascular dysfunction was detected in many different conditions, ranging from organ transplantation to inflammatory disorders and from metabolic diseases to cardiomyopathies. Moreover, it has been proven that CFVR by echocardiography not only detects coronary microvascular involvement but is also an effective prognostic factor that allows a precise risk stratification of the patients. In this review, we will summarize the many applications of CFVR by echocardiography, focusing on the coronary involvement of systemic diseases.

Coronary Flow Evaluation in Heart Transplant Patients Compared to Healthy Controls Documents the Superiority of Coronary Flow Velocity Reserve Companion as Diagnostic and Prognostic Tool

Background

Distinct contributions by functional or structural alterations of coronary microcirculation in heart transplantation (HT) and their prognostic role have not been fully elucidated. We aimed to identify the mechanisms of coronary microvascular dysfunction (CMD) in HT and their prognostic implications.

Methods

134 patients, surviving at least 5 years after HT, without evidence of angiographic vasculopathy or symptoms/signs of rejection were included. 50 healthy volunteers served as controls. All underwent the assessment of rest and hyperemic coronary diastolic peak flow velocity (DPVr and DPVh) and coronary flow velocity reserve (CFVR) and its inherent companion that is based on the adjusted quadratic mean: CCFVR = √{(DPVr)2 + (DPVh)2}. Additionally, basal and hyperemic coronary microvascular resistance (BMR and HMR) were estimated.

Results

Based on CFVR and DPVh, HT patients can be assigned to four endotypes: endotype 1, discordant with preserved CFVR (3.1 ± 0.4); endotype 2, concordant with preserved CFVR (3.4 ± 0.5); endotype 3, concordant with impaired CFVR (1.8 ± 0.3) and endotype 4, discordant with impaired CFVR (2.0 ± 0.2). Intriguingly, endotype 1 showed lower DPVr (p < 0.0001) and lower DPVh (p < 0.0001) than controls with lower CFVR (p < 0.0001) and lower CCFVR (p < 0.0001) than controls. Moreover, both BMR and HMR were higher in endotype 1 than in controls (p = 0.001 and p < 0.0001, respectively), suggesting structural microvascular remodeling. Conversely, endotype 2 was comparable to controls. A 13/32 (41%) patients in endotype 1 died in a follow up of 28 years and mortality rate was comparable to endotype 3 (14/31, 45%). However, CCFVR was < 80 cm/s in all 13 deaths of endotype 1 (characterized by preserved CFVR). At multivariable analysis, CMD, DPVh < 75 cm/s and CCFVR < 80 cm/s were independent predictors of mortality. The inclusion of CCFVR < 80 cm/s to models with clinical indicators of mortality better predicted survival, compared to only adding CMD or DPVh < 75 cm/s (p < 0.0001 and p = 0.03, respectively).

Conclusion

A normal CFVR could hide detection of microvasculopathy with high flow resistance and low flow velocities at rest. This microvasculopathy seems to be secondary to factors unrelated to HT (less rejections and more often diabetes). The combined use of CFVR and CCFVR provides more complete clinical and prognostic information on coronary microvasculopathy in HT.

Valvulo-Arterial Impedance and Dimensionless Index for Risk Stratifying Patients With Severe Aortic Stenosis

The hemodynamic effects of aortic stenosis (AS) consist of increased left ventricular (LV) afterload, reduced myocardial compliance, and increased myocardial workload. The LV in AS patients faces a double load: valvular and arterial loads. As such, the presence of symptoms and occurrence of adverse events in AS should better correlate with calculating the global burden faced by the LV in addition to the transvalvular gradient and aortic valve area (AVA). The valvulo-arterial impedance (Zva) is a useful parameter providing an estimate of the global LV hemodynamic load that results from the summation of the valvular and vascular loads. In addition to calculating the global LV afterload, it is paramount to estimate the stenosis severity accurately. In clinical practice, the management of low-flow low-gradient (LF-LG) severe AS with preserved LV ejection fraction requires careful confirmation of stenosis severity. In addition to the Zva, the dimensionless index (DI) is a very useful parameter to express the size of the effective valvular area as a proportion of the cross-section area of the left ventricular outlet tract velocity-time integral (LVOT-VTI) to that of the aortic valve jet (dimensionless velocity ratio). The DI is calculated by a ratio of the sub-valvular velocity obtained by pulsed-wave Doppler (LVOT-VTI) divided by the maximum velocity obtained by continuous-wave Doppler across the aortic valve (AV-VTI). In contrast to AVA measurement, the DI does not require the calculation of LVOT cross-sectional area, a major cause of erroneous assessment and underestimation of AVA. Hence, among patients with LG severe AS and preserved LV ejection fraction, calculation of DI in routine echocardiographic practice may be useful to identify a subgroup of patients at higher risk of mortality who may derive benefit from aortic valve replacement. This article aims to elucidate the Zva and DI in different clinical situations, correlate with the standard indexes of AS severity, LV geometry, and function, and thus prove to improve risk stratification and clinical decision making in patients with severe AS.

Fractional Flow Reserve Evaluated as Metric of Coronary Stenosis - A Mathematical Model Study

Introduction: Coronary arterial stenosis may impair myocardial perfusion with myocardial ischemia and associated morbidity and mortality as result. The myocardial fractional flow reserve (FFR) is clinically used as a stenosis-specific index. Aim: This study aims to identify the relation between the FFR and the degree of coronary arterial stenosis using a simple mathematical model of the coronary circulation. Methods: A mathematical model of the coronary circulation, including an arterial stenosis of variable degree, was developed. The relation between the FFR and the degree of stenosis (defined as the fractional cross sectional area narrowing) was investigated, including the influence of the aortic and venous pressures and the capillary resistance. An additional study concerning 22 patients with coronary artery disease permits comparison of clinical data and in silico findings. Results: The FFR shows an S-shaped relationship with the stenosis index. We found a marked influence of venous and aortic pressure and capillary resistance. The FFR is accompanied by a clinically relevant co-metric (FFR C ), defined by the Pythagorean sum of the two pressures in the definition formula for FFR. In the patient group the FFR C is strongly related to the post-stenotic pressure (R = 0.91). The FFR C requires establishment of a validated cut-off point using future trials. Conclusion: The S-shaped dependence of FFR on the severity of the stenosis makes the FFR a measure of the ordinal scale. The marked influences of the aortic and venous pressures and the capillary resistance on the FFR will be interpreted as significant variations in intra- and inter-individual clinical findings. These fluctuations are partly connected to the neglect of considering the FFR C . At otherwise identical conditions the FFR as measured at baseline differs from the value obtained during hyperemic conditions. This expected observation requires further investigation, as the current hyperemia based evaluation fails to take advantage of available baseline data.