Computational modeling of uteroplacental hemodynamics

Carnegie Mellon University received a $766,982 project grant awarded July 1, 2025, through June 30, 2027, from the National Institute of Child Health and Human Development under the Child Health and Human Development Extramural Research program (CFDA 93.865). The award funds the development and validation of a novel computational framework to simulate uteroplacental hemodynamics and placentation during early pregnancy. Specifically, the project will create multiphysics simulation models that investigate maternal uterine vascular remodeling, particularly spiral artery changes critical to establishing appropriate placental and fetal blood flow. The computational models will systematically analyze the effects of placental anatomy, blood rheology, vascular mechanical properties, and other physiological factors on hemodynamic outcomes to establish a robust platform for studying pregnancy vascular dynamics.

The deliverables include a validated computational modeling platform designed to advance understanding of the mechanistic links between uteroplacental hemodynamics and placentation, with application toward early detection and diagnosis of pregnancy complications such as those arising from defective spiral artery remodeling. By leveraging multiscale cardiovascular modeling expertise, the research addresses current limitations in obtaining in vivo pregnancy data and provides a foundation for identifying diagnostic metrics for severe pregnancy disorders related to abnormal placental formation.

Abstract

During early pregnancy, the maternal uterine vasculature, particularly the spiral arteries, must undergo significant remodeling to establish uteroplacental circulation and create a hemodynamic environment suitable for placental and fetal development. Defective or incomplete spiral artery remodeling has been reported as a common characteristic of severe pregnancy disorders related to abnormal placental formation. Despite their importance, the mechanistic links between uteroplacental hemodynamics and placentation and their implications in fetal development have not been fully elucidated. Given the limitations of current technology to obtain in vivo data in the early stages of pregnancy, computational models provide a promising approach to investigate mechanisms of placentation and identify metrics for early diagnosis of pregnancy complications. Although models have already been proposed to study this process, they are not without limitations. Our preliminary data have shown that uncertainties related to placental anatomy and physiology can substantially affect simulation results. In addition, the effect of blood rheology or other assumptions related to uterine vascular remodeling and mechanical properties of the placenta and its vascular structures could significantly change local hemodynamics in this organ. Therefore, a systematic analysis of the effect of these factors to establish a robust platform to study pregnancy hemodynamics and vascular remodeling is much needed. We propose a computational study that leverages our expertise in multiphysics simulations and cardiovascular multiscale modeling toward maternal-fetal health applications. This project will focus on developing and validating a novel computational framework that can simulate uteroplacental hemodynamics and critical aspects of placentation and investigate the potential for applying these models to the early detection of pregnancy complications. We will do this through the following specific aims: 1) simulate uteroplacental hemodynamics and determine the implications of spiral artery remodeling in the development of the placenta; 2) determine metrics to measure the risk of adverse placental development by combining standard-of-care technology (doppler ultrasound) and data from uteroplacental hemodynamics simulations. Successful completion of this exploratory project will establish a modeling framework for the simulation of the maternal-placental interface that would lay the groundwork for subject-specific modeling studies through an R01 award. More importantly, this model will offer a window into the early stages of pregnancy, which is currently challenging to study in humans, and will help generate data to inform future hypothesis-driven - experimental or computational - research.