Applying residence time distribution theory to coronary thermodilution curves.

Cardiovascular diseases remain the leading cause of death worldwide and coronary microvascular dysfunction is one cardiovascular disease which is particularly challenging to diagnose and treat. Coronary thermodilution is a widely used, invasive procedure to evaluate microvascular function by generating physiological indices such as coronary flow reserve and the index of microvascular resistance. Although commonly cited as an indicator dilution method in the cardiovascular literature, current coronary thermodilution techniques lack rigorous application of the accompanying mathematical framework, thereby leaving potentially valuable diagnostic information unexploited. This study bridges that gap by demonstrating the equivalence between indicator-dilution theory and residence time distribution theory from chemical engineering, introducing a novel framework for analyzing coronary thermodilution curves as probability distributions of transit times. These innovations are applied to model artery geometries, patient artery geometries, and in vivo thermodilution data. A mathematical model was developed to analyze the dynamics of coronary flow by representing the coronary artery as a combination of idealized flow systems. This model was validated using computational fluid dynamics simulations of 135 model arteries under physiologically informed conditions and preliminary data from two real patient arteries. The mathematical model was able to accurately describe the thermodilution curves generated by the model arteries (RAE=0.086 ± 0.03). Parameters derived from the model, such as stagnant zone volume and turbulence intensity, showed strong correlations with flow patterns observed in both model and patient-specific geometries, providing novel insights into coronary hemodynamics. The model was also fitted to coronary thermodilution data measured in vivo and was found to be a good visual fit to the measured data. The results demonstrate the ability of this framework to quantify clinically relevant hemodynamic features, such as areas of stagnant blood and turbulence, directly from thermodilution curves without altering current clinical procedures. The proposed framework provides a more rigorous calculation of mean transit time calculations as compared to current state of the art. This interdisciplinary approach highlights the potential of existing thermodilution data to provide a more comprehensive understanding of coronary flow dynamics without procedural changes, paves the way for improved patient care, advances the integration of hemodynamic information into interventional cardiology.