Abstract
Artificial placenta (AP) is a promising approach to improve survival in extremely premature fetuses, removing them from the uterus and replacing the placenta by an external oxygenator. In in vivo experiments with lambs, haemodynamic changes were observed in the umbilical artery (UA) post-connection to the AP: decrease in flow pulsatility index (PI), increase in mean pressure and heart rate, and flatter diastolic flow with a secondary peak.
Computational models can help to understand the causes of observed phenomena. Therefore, the clinical objective of this work was to investigate the causes of the aforementioned changes in UA velocity, while the methodological objective was to implement a computational model capable of reproducing the behaviour of an AP.
We used a closed lumped model of the whole fetal circulation, modified to include the AP, and tested the haemodynamic changes in the UA after altering heart rate and AP’s resistance and compliance. We also added a simple wave reflection model and studied its effect on pressure and flow traces. We found that reducing AP’s resistance increased mean flow, and reducing compliance decreased velocity PI. When adding the reflection model, the flatter diastolic flow observed in the UA was reproduced.
This study suggests that the observed haemodynamics changes in the UA post-connection to the AP are due to a combination of decreased compliance and resistance, as well as wave reflections from components within the AP circuit.
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Acknowledgements
The research leading to these results has received funding from "la Caixa" Banking Foundation. This work has been performed under FI 2022 grant number 00237, awarded by the Agency for Management of University and Research Grants (AGAUR), Generalitat de Catalunya.
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Villanueva, M.I. et al. (2022). Haemodynamic Changes in the Fetal Circulation Post-connection to an Artificial Placenta: A Computational Modelling Study. In: Camara, O., et al. Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers. STACOM 2022. Lecture Notes in Computer Science, vol 13593. Springer, Cham. https://doi.org/10.1007/978-3-031-23443-9_5
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