Computational Fontan Analysis: Preserving accuracy while expediting workflow

Liu, X.; Aslan, S.; Kim, B.; Warburton, L.; Jackson, D.; Muhuri, A.; Subramanian, A.; Mass, P.; Cleveland, V.; Loke, Y.-H.; Hibino, N.; Olivieri, L.; Krieger, A.

doi:10.1101/2021.10.28.466272

bioRxiv · 10.1101/2021.10.28.466272

Computational Fontan Analysis: Preserving accuracy while expediting workflow

Liu, X.·Aslan, S.·Kim, B.·Warburton, L.·Jackson, D.·Muhuri, A.·Subramanian, A.·Mass, P.·Cleveland, V.·Loke, Y.-H.·Hibino, N.·Olivieri, L.·Krieger, A.

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Abstract

BackgroundPost-operative outcomes of the Fontan operation have been linked to graft shape after implantation. Computational fluid dynamics (CFD) simulations are used to explore different surgical options. The objective of this study is to perform a systematic in vitro validation for investigating the accuracy and efficiency of CFD simulation to predict Fontan hemodynamics. MethodsCFD simulations were performed to measure indexed power loss (iPL) and hepatic flow distribution (HFD) in 10 patient-specific Fontan models, with varying mesh and numerical solvers. The results were compared with a novel in vitro flow loop setup with 3D printed Fontan models. A high-resolution differential pressure sensor was used to measure the pressure drop for validating iPL predictions. Microparticles with particle filtering system were used to measure HFD. The computational time was measured for a representative Fontan model with different mesh sizes and numerical solvers. ResultsWhen compared to in vitro setup, variations in CFD mesh sizes had significant effect on HFD (p = 0.0002) but no significant impact on iPL (p = 0.069). Numerical solvers had no significant impact in both iPL (p = 0.50) and HFD (P = 0.55). A transient solver with 0.5 mm mesh size requires computational time 100 times more than a steady solver with 2.5 mm mesh size to generate similar results. ConclusionsThe predictive value of CFD for Fontan planning can be validated against an in vitro flow loop. The prediction accuracy can be affected by the mesh size, model shape complexity and flow competition.

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Liu, X., Aslan, S., Kim, B., Warburton, L., Jackson, D., Muhuri, A., Subramanian, A., Mass, P., Cleveland, V., Loke, Y.-H., Hibino, N., Olivieri, L., Krieger, A.. 2021-10-29. Computational Fontan Analysis: Preserving accuracy while expediting workflow. https://doi.org/10.1101/2021.10.28.466272

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