Related Experiment Video
Updated: Dec 29, 2025
Ultrasound Based Assessment of Coronary Artery Flow and Coronary Flow Reserve Using the Pressure Overload Model in Mice
Published on: April 13, 2015
Fractional Flow Reserve Evaluated as Metric of Coronary Stenosis - A Mathematical Model Study
Theo J C Faes1, Romain Meer1, Guy R Heyndrickx2
1Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands.
Insights
Fractional flow reserve (FFR) shows an S-shaped relation to coronary stenosis severity. Other factors like pressure and resistance significantly influence FFR, suggesting a need to consider a new co-metric for better clinical interpretation.
Area of Science:
- Cardiovascular Physiology
- Medical Imaging and Diagnostics
- Computational Biology
Background:
- Coronary arterial stenosis can lead to myocardial ischemia, increasing morbidity and mortality.
- Fractional flow reserve (FFR) is a key clinical index for assessing stenosis severity.
Purpose of the Study:
- To investigate the relationship between FFR and the degree of coronary arterial stenosis.
- To explore the influence of hemodynamic factors on FFR using a mathematical model.
Main Methods:
- Development of a mathematical model of coronary circulation with variable stenosis.
- Analysis of FFR in relation to stenosis index, aortic/venous pressures, and capillary resistance.
- Comparison of in silico findings with clinical data from 22 coronary artery disease patients.
Main Results:
- FFR exhibits an S-shaped relationship with the stenosis index.
- Venous pressure, aortic pressure, and capillary resistance significantly impact FFR.
- A new co-metric, FFR , showed a strong correlation with post-stenotic pressure (R=0.91) in patients.
Conclusions:
- The S-shaped FFR dependence classifies it as an ordinal scale measure.
- Variations in clinical FFR findings are partly due to neglecting FFR and other hemodynamic factors.
- Baseline FFR differs from hyperemia-induced FFR, warranting further investigation into hyperemia-based evaluations.
Abstract:
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 ), defined by the Pythagorean sum of the two pressures in the definition formula for FFR. In the patient group the FFR is strongly related to the post-stenotic pressure (R = 0.91). The FFR 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 . 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.
