Background: Reliability of computational models for cardiovascular investigations strongly depends on their validation against physical data. This study aims to experimentally validate a computational model of complex congenital heart disease (i.e., surgically palliated hypoplastic left heart syndrome with aortic coarctation) thus demonstrating that hemodynamic information can be reliably extrapolated from the model for clinically meaningful investigations.
Materials and methods: A patient-specific aortic arch model was tested in a mock circulatory system and the same flow conditions were re-created in silico, by setting an appropriate lumped parameter network (LPN) attached to the same three-dimensional (3D) aortic model (i.e., multi-scale approach). The model included a modified Blalock-Taussig shunt and coarctation of the aorta. Different flow regimes were tested as well as the impact of uncertainty in viscosity.
Results: Computational flow and pressure results were in good agreement with the experimental signals, both qualitatively, in terms of the shape of the waveforms, and quantitatively (mean aortic pressure 62.3 vs. 65.1 mmHg, 4.8% difference; mean aortic flow 28.0 vs. 28.4% inlet flow, 1.4% difference; coarctation pressure drop 30.0 vs. 33.5 mmHg, 10.4% difference), proving the reliability of the numerical approach. It was observed that substantial changes in fluid viscosity or using a turbulent model in the numerical simulations did not significantly affect flows and pressures of the investigated physiology. Results highlighted how the non-linear fluid dynamic phenomena occurring in vitro must be properly described to ensure satisfactory agreement.
Conclusions: This study presents methodological considerations for using experimental data to preliminarily set up a computational model, and then simulate a complex congenital physiology using a multi-scale approach.