Computational fluid dynamics (CFD) modeling may aid in planning of invasive interventions in Fontan patients. Clinical application of current CFD techniques is however limited by complexity and long computation times. Therefore, we validated a “lean” CFD method to magnetic resonance imaging (MRI) and an “established” CFD method, ultimately aiming to reduce complexity to enable predictive CFD during ongoing interventions. Fifteen Fontan patients underwent MRI for CFD modeling. The differences between lean and established approach, in hepatic and total flow percentage to the left pulmonary artery (%LPA), power loss and relative wall shear stress area were 1.5 ± 4.0%, -0.17 ± 1.1%, -0.055 ± 0.092 mW and 1.1 ± 1.4%. Compared with MRI, the lean and established method showed a bias in %LPA of -1.9 ± 3.4% and -1.8 ± 3.1%. Computation time was for the lean and established approach 3.0 ± 2.0 min and 7.0 ± 3.4 h, respectively. We conclude that the proposed lean method provides fast and reliable results for future CFD support during interventions.
Graphical abstract
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4D-flow; cardiac magnetic resonance; patientspecific simulation; prediction of invasive interventions; total cavopulmonary connection Purpose Patients with complex congenital heart disease may need to be converted to a Fontan circulation with systemic venous return surgically connected to the pulmonary circulation. These patients frequently form aortopulmonary collaterals (APC), that is arterial inflows to the pulmonary artery vascular tree. The aim of this study was to develop a method to calculate the effect of APC on the pulmonary flow distribution based on magnetic resonance imaging (MRI) measurements and computational fluid dynamics simulations in order to enable prediction of interventional outcomes in Fontan patients. Methods Patient-specific models of 11 patients were constructed in a 3D-design software based on MRI segmentations. APC flow was quantified as the difference between pulmonary venous flow and pulmonary artery flow, measured by MRI. A method was developed to include the modulating effect of the APC flow by calculating the patient-specific relative pulmonary vascular resistance. Simulations, including interventions with a Y-graft replacement and a stent dilatation, were validated against MRI results. Results The bias between simulated and MRI-measured fraction of blood to the left lung was 2Á9 AE 5Á3%. Including the effects of the APC flow in the simulation (n = 6) reduced simulation error from 9Á8 AE 7Á0% to 5Á2 AE 6Á3%. Preliminary findings in two patients show that the effect of surgical and catheter interventions could be predicted using the demonstrated methods. Conclusions The work demonstrates a novel method to include APC flow in predictive simulations of Fontan hemodynamics. APC flow was found to have a significant contribution to the pulmonary flow distribution in Fontan patients.
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