The physiological limitations of the Fontan circulation have been extensively addressed in the literature. Many studies emphasized the importance of pulmonary vascular resistance in determining cardiac output (CO) but gave little attention to other cardiovascular properties that may play considerable roles as well. The present study was aimed to systemically investigate the effects of various cardiovascular properties on clinically relevant hemodynamic variables (e.g., CO and central venous pressure). To this aim, a computational modeling method was employed. The constructed models provided a useful tool for quantifying the hemodynamic effects of any cardiovascular property of interest by varying the corresponding model parameters in model-based simulations. Herein, the Fontan circulation was studied compared with a normal biventricular circulation so as to highlight the unique characteristics of the Fontan circulation. Based on a series of numerical experiments, it was found that 1) pulmonary vascular resistance, ventricular diastolic function, and systemic vascular compliance play a major role, while heart rate, ventricular contractility, and systemic vascular resistance play a secondary role in the regulation of CO in the Fontan circulation; 2) CO is nonlinearly related to any single cardiovascular property, with their relationship being simultaneously influenced by other cardiovascular properties; and 3) the stability of central venous pressure is significantly reduced in the Fontan circulation. The findings suggest that the hemodynamic performance of the Fontan circulation is codetermined by various cardiovascular properties and hence a full understanding of patient-specific cardiovascular conditions is necessary to optimize the treatment of Fontan patients.

Non‐invasive coronary computed tomography (CT) angiography‐derived fractional flow reserve (cFFR) is an emergent approach to determine the functional relevance of obstructive coronary lesions. Its feasibility and diagnostic performance has been reported in several studies. It is unclear if differences in sensitivity and specificity between these studies are due to study design, population, or "computational methodology." We evaluate the diagnostic performance of four different computational workflows for the prediction of cFFR using a limited data set of 10 patients, three based on reduced‐order modelling and one based on a 3D rigid‐wall model. The results for three of these methodologies yield similar accuracy of 6.5% to 10.5% mean absolute difference between computed and measured FFR. The main aspects of modelling which affected cFFR estimation were choice of inlet and outlet boundary conditions and estimation of flow distribution in the coronary network.One of the reduced‐order models showed the lowest overall deviation from the clinical FFR measurements, indicating that reduced‐order models are capable of a similar level of accuracy to a 3D model. In addition, this reduced‐order model did not include a lumped pressure‐drop model for a stenosis, which implies that the additional effort of isolating a stenosis and inserting a pressure‐drop element in the spatial mesh may not be required for FFR estimation.The present benchmark study is the first of this kind, in which we attempt to homogenize the data required to compute FFR using mathematical models. The clinical data utilised in the cFFR workflows are made publicly available online.