Modelling The Hemodynamics of Coronary Ischemia

• Published in: Fluids (Basel) Vol. 8; no. 5; p. 159
• Main Authors: Baraikan, Abdulaziz Al, Czechowicz, Krzysztof, Morris, Paul D, Halliday, Ian, Gosling, Rebecca C, Gunn, Julian P, Narracott, Andrew J, Williams, Gareth, Garg, Pankaj, Malawski, Maciej, Vosse, Frans van de, Lungu, Angela, Rafiroiu, Dan, Hose, David Rodney
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-05-2023
• Subjects: Analysis; Arteries; Cardiac function; Cardiovascular disease; compartmental models; Compliance; Coronary artery disease; Coronary heart disease; Coronary vessels; Data acquisition; fluid dynamics; haemodynamics; Heart; Hemodynamics; Ischemia; Mathematical models; Ordinary differential equations; parameter identification; Parameterization; Percutaneous treatment; Physiological aspects; Physiology; United Kingdom
• ISSN: 2311-5521; 2311-5521
• DOI: 10.3390/fluids8050159

Acting upon clinical patient data, acquired in the pathway of percutaneous intervention, we deploy hierarchical, multi-stage, data-handling protocols and interacting low- and high-order mathematical models (chamber elastance, state-space system and CFD models), to establish and then validate a framework to quantify the burden of ischaemia. Our core tool is a compartmental, zero-dimensional model of the coupled circulation with four heart chambers, systemic and pulmonary circulations and an optimally adapted windkessel model of the coronary arteries that reflects the diastolic dominance of coronary flow. We guide the parallel development of protocols and models by appealing to foundational physiological principles of cardiac energetics and a parameterisation (stenotic Bernoulli resistance and micro-vascular resistance) of patients’ coronary flow. We validate our process first with results which substantiate our protocols and, second, we demonstrate good correspondence between model operation and patient data. We conclude that our core model is capable of representing (patho)physiological states and discuss how it can potentially be deployed, on clinical data, to provide a quantitative assessment of the impact, on the individual, of coronary artery disease.