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07.01.2025 | Original Article

Development of a personalized fluid-structure interaction model for the aorta in human fetuses

verfasst von: Zhenglun Alan Wei, Guihong Chen, Biao Si, Liqun Sun, Mike Seed, Shuping Ge

Erschienen in: Engineering with Computers

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Abstract

Fluid-structure interaction (FSI) modeling, a technique widely used to enhance imaging modalities for adult and pediatric heart diseases, has been underutilized in the context of fetal circulation because of limited data on flow conditions and material properties. Recognizing the significant impact of congenital heart diseases on the fetal aorta, our research aims to address this gap by developing and validating a personalized FSI model for the fetal aorta. Our approach involved reconstructing the anatomy and flow of the fetal aorta using fetal echocardiography and ultrasound. We developed an innovative iterative method that includes: (i) an automated process for incorporating Windkessel models at outflow boundaries when clinical data is limited because of the resolution constraints of fetal imaging, (ii) an inverse approach to estimate bulk material properties, and (iii) an FSI model for high-fidelity hemodynamic evaluation. This method is efficient, typically converging in fewer than three iterations. We analyzed four normal fetal aortas with gestational ages ranging from 23.5 to 35.5 weeks to validate our workflow. We compared results with in vivo velocity waveforms across a cardiac cycle at the aortic isthmus. Strong correlations (R > 0.95) were observed. Furthermore, our findings suggest that the stiffness of the fetal aorta increases until 30 weeks of gestation and then decreases. This study marks a first-of-its-kind effort in developing a rigorously validated, personalized flow model for fetal circulation, offering novel insights into fetal aortic development and growth.

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Metadaten
Titel
Development of a personalized fluid-structure interaction model for the aorta in human fetuses
verfasst von
Zhenglun Alan Wei
Guihong Chen
Biao Si
Liqun Sun
Mike Seed
Shuping Ge
Publikationsdatum
07.01.2025
Verlag
Springer London
Erschienen in
Engineering with Computers
Print ISSN: 0177-0667
Elektronische ISSN: 1435-5663
DOI
https://doi.org/10.1007/s00366-024-02100-0