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Updated: May 22, 2026

Three-dimensional Rendering and Analysis of Immunolabeled, Clarified Human Placental Villous Vascular Networks
Published on: March 29, 2018
Tissue clearing and light-sheet fluorescence microscopy for three-dimensional mapping of placental vascularization
Matthieu Simion1, Audrey Prézelin2, Anne Couturier-Tarrade1
1Université Paris-Saclay, UVSQ, INRAE, BREED, Jouy-en-Josas, France; Ecole Nationale Vétérinaire d'Alfort, BREED, Maisons-Alfort, France.
None:
Placental function depends on a highly heterogeneous three-dimensional (3D) vascular architecture that cannot be fully captured from conventional two-dimensional sections. Recent advances in tissue clearing and whole-mount labelling now enable deep optical imaging of millimeter-scale placental samples while preserving villi and vascular organization. In this review, available approaches for 3D visualization and quantification of placental vasculature are outlined, with emphasis on light-sheet fluorescence microscopy (LSFM) as a high-throughput modality for cleared, immunolabelled tissues. Placenta-specific sample formats (i.e., for human, villous trees, perfused lobules/cotyledons, basal plate or uteroplacental vessels) are discussed, and practical pipelines for perfusion/washing, clearing (hydrogel, solvent, aqueous-based methods), staining (endothelial, trophoblast and morphology-oriented markers) and computational segmentation of image volumes to produce vascular graphs are described. These methods are discussed across humans, laboratory rodents and domestic species, highlighting how species-specific exchange structure and maternal-fetal blood space organization shape the choice and interpretation of vascular metrics. Current limitations of LSFM include blood-derived absorption, antibody penetration, deformation, segmentation validation and terabyte-scale data management. Research perspectives include the development of correlative multiscale imaging, standardized metadata and targeted 3D pathology workflows for clinically annotated human cohorts.

