The placenta is one of the most accessible human organs for ex vivo imaging, yet it still remains one of the least understood. Recent advances in ex vivo imaging approaches provide opportunities to capture the complex anatomy of the placenta and its vasculature across multiple scales. However, alongside this it is imperative to consider how we can optimise workflows - from tissue sampling and preparation to analysis - to obtain meaningful quantitative data from imaging, including computational handling of large and complex datasets at scale. Indeed, such tools are critical to advance our insight into how structure-function relationships change across gestation, or in pregnancy pathologies. This review first provides a quantitative overview of placental structure, then critically considers the advantages and disadvantages of current and emerging ex vivo placental imaging approaches from the subcellular level to the organ scale, with a focus on methods and considerations to enable meaningful quantification and downstream use of data. • Multiscale imaging provides vital insights into placental anatomy. • Appropriate tissue preparation is critical to enhance data quality. • Quantification of 3D placental imaging requires custom-built approaches. • 2D imaging fulfils important roles, with interpretation aided by 3D imaging. • Machine learning can enable future high-throughput analysis of complex imaging data.
Spring et al. (Sun,) studied this question.