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Single ventricle hearts have only one ventricle that can pump blood effectively and the treatment requires three stages of operations to reconfigure the heart and circulatory system. At the second stage, Glenn procedure is performed to connect superior vena cava (SVC) to the pulmonary arteries (PA). For the third and most complex operation, called Fontan, an extracardiac conduit is used to connect inferior vena cava (IVC) to the PL and thereafter no deoxygenated blood goes to the heart. Predicting Hemodynamic Performance of Fontan Operation using computational fluid dynamics (CFD) is hypothesized to improve outcomes and optimize this treatment planning in children with single-ventricle heart disease. An important reason for this surgical planning is to reduce the development of pulmonary arteriovenous malformations (PAVM) and the need to perform Fontan revisions. The purpose of this study was to develop amodel for Fontan surgical planning and use this model to compare blood circulation in two designed graft types of Fontan operation known as T-shape and Y-graft. The functionality of grafts was compared in terms of power loss (PL) and hepatic flow distribution (HFD), a known factor in PAVM development. To perform this study, ten single-ventricle children with Glenn physiology were included and a CFD model was developed to estimate the blood flow circulation to the left and right pulmonary arteries. The estimated blood flow by CFD was compared with that measured by cardiovascular magnetic resonance. Results showed that there was an excellent agreement between the net blood flow in the right and left pulmonary arteries computed by CFD and CMR (ICC= 0.98, P-value ≥0.21). After validating the accuracy of each CFD model, Fontan operations using T-shape and Y-graft conduits were performed in silico for each patient and the developed CFD model was used to predict the post-surgical PL and HFD. We found that the PL in the Y-graft was significantly lower than in the T-shape (P-value ≤0.001) and HFD was significantly better balanced in Y-graft compared to the T-shape (P-value=0.004)., Competing Interests: Conflict of interests: None. Authors of this study do not have any conflict of interest to declare.

Aims: A method for estimating right ventricular ejection fraction (RVEF) from RV pressure waveforms was recently validated in an experimental model. Currently, cardiac magnetic resonance imaging (MRI) is the clinical reference standard for measurement of RVEF in pulmonary arterial hypertension (PAH). The present study was designed to test the hypothesis that the pressure-based method can detect clinically significant reductions in RVEF as determined by cardiac MRI in patients with PAH., Methods and Results: RVEF estimates derived from analysis of RV pressure waveforms recorded during right heart catheterization (RHC) in 25 patients were compared with cardiac MRI measurements of RVEF obtained within 24 h. Three investigators blinded to cardiac MRI results independently performed pressure-based RVEF estimation with the mean of their results used for comparison. Linear regression was used to assess correlation, and a receiver operator characteristic (ROC) curve was derived to define ability of the pressure-based method to detect a maladaptive RV response, defined as RVEF <35% on cardiac MRI. In 23 patients, an automated adaptation of the pressure-based RVEF method was also applied as proof of concept for beat-to-beat RVEF monitoring. The study cohort was comprised of 16 female and 9 male PAH patients with an average age of 53 ± 13 years. RVEF measured by cardiac MRI ranged from 16% to 57% (mean 37.7 ± 11.6%), and estimated RVEF from 15% to 54% (mean 36.2 ± 11.2%; P = 0.6). Measured and estimated RVEF were significantly correlated (r 2  = 0.78; P < 0.0001). ROC curve analysis demonstrated an area under the curve of 0.94 ± 0.04 with a sensitivity of 81% and specificity of 85% for predicting a maladaptive RV response. As a secondary outcome, with the recognized limitation of non-coincident measures, Bland-Altman analysis was performed and indicated minimal bias for estimated RVEF (-1.5%) with limits of agreement of ± 10.9%. Adaptation of the pressure-based estimation method to provide beat-to-beat RVEF also demonstrated significant correlation between the median beat-to-beat value over 10 s with cardiac MRI (r 2  = 0.66; P < 0.001), and an area under the ROC curve of 0.94 ± 0.04 (CI = 0.86 to 1.00) with sensitivity and specificity of 78% and 86%, respectively, for predicting a maladaptive RV response., Conclusions: Pressure-based estimation of RVEF correlates with cardiac MRI and detects clinically significant reductions in RVEF. Study results support potential utility of pressure-based RVEF estimation for assessing the response to diagnostic or therapeutic interventions during RHC., (© 2022 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)