Image-Based In Silico Modelling of Feto-Placental Vasculature

The placenta nourishes the fetus and removes its waste products in pregnancy.

Fundamental to its function is the healthy development of an extensively branched tree-like structure known as the vascular tree. In pathological pregnancies, abnormalities have been found in placental structure and function.

Impaired uteroplacental blood flow can lead to pregnancy disorders such as fetal growth restriction (FGR), a condition in which the fetus does not grow physiologically.

FGR has lifelong consequences for both fetus and mother, affecting 8-10% of pregnancies and contributing to 30% of stillbirths. The placenta is inaccessible to in vivo measurements due to technological and ethical constraints.

Ultrasound is the most routinely used clinical imaging tool for screening the placenta; however, it is limited in spatial resolution.

Placental function can be also assessed via Magnetic Resonance Imaging (MRI) which is safe during pregnancy; however, MRI models cannot measure blood flow changes in the placental vascular tree. Complementary to imaging, in silico models are increasingly used to probe complex cardiovascular problems.

Attempts to model blood flow in the placental vasculature are based on oversimplified assumptions while being limited by the data they have been informed or validated against with.

Here, an integrated hemodynamic model of the placental vasculature will be developed using novel ex vivo computed tomography data and computational fluid dynamics.

This project will innovate by delivering a computer-based framework, InSilicoPlacenta, which will offer a comprehensive understanding of the structural and functional abnormalities with FGR.

We will combine medical imaging with in silico models to infer placental tissue properties of the entire placental vasculature.

The long-term impacts of the proposed framework are expected to change clinical diagnosis and management of high-risk pregnancies by reducing stillbirths and improving neonatal outcomes.