Fetal life plays a pivotal role in shaping long-term health, with cardiovascular development exerting particular influence. Defects that arise during this critical window, such as congenital heart abnormalities or maladaptive remodeling related to placental dysfunction, increase vulnerability to cardiovascular disease, hypertension, and metabolic disorders later in life. Yet, despite the importance of early cardiovascular development, current diagnostic tools remain limited in their ability to detect or manage fetal cardiac dysfunction. Computational modelling offers a powerful means to address this gap, providing a framework to integrate physiological knowledge, capture developmental adaptations, and generate new insights into how the fetal heart and circulation evolve over gestation. However, existing models are often adapted from adult cardiovascular frameworks, which, while well established, do not fully account for fetal-specific features such as circulatory shunts, placental resistance, and shifting pressure-loading conditions. This creates a critical need to examine how current modelling approaches relate to and diverge from adult systems, in order to identify where fetal-specific refinements are required and where shared principles can be leveraged. This review aims to synthesize computational models of the fetal heart in relation to cardiovascular system function, with a focus on the biomechanical interaction between the heart and key fetal organs such as the placenta. We highlight how current approaches represent fetal physiology, the unique challenges that remain, and how advancing such models could improve early detection and intervention, ultimately supporting better lifelong health outcomes. • Fetal cardiovascular health shapes lifelong disease risk. • This review synthesizes models of fetal heart and circulation. • Highlights where fetal physiology diverges from adult-based models. • Defines modelling challenges critical for accurate fetal function simulation. • Highlights improved models could guide early intervention and better outcomes.
Nagahawatte et al. (Mon,) studied this question.