XRH was utilised to investigate the structural diversity of placental villi in humans and equids (horses and related species), which despite their common evolutionary origins exhibit markedly different placental structures that may influence nutrient transfer efficiency. By combining XRH with electron microscopy (EM), the study aimed to elucidate these structural differences and their functional implications.

Bone is a dynamic tissue which is actively remodelled throughout life. It relies upon a constant blood supply for the provision of oxygen and nutrients. The cortex or outer shell of most of our bones is perforated by an interconnected network of vascular canals and bone cell survival depends on the proximity to this vascular network. Recent evidence has emerged that low bone mass, deterioration of bone tissue and disruption of bone microarchitecture in osteoporosis may be driven by reduced angiogenic signals and vascular supply. A thorough investigation of this hypothesis is currently limited by challenges related to imaging of the bone vascular network, which is deeply enclosed in mineralised bone tissue.

Lung lymphatics maintain fluid homoeostasis by providing a drainage system that returns fluid, cells and metabolites to the circulatory system. The 3D structure of the human pulmonary lymphatic network is essential to the lung function, but it is poorly characterised.  Image-based 3D mathematical modelling of pulmonary lymphatic microfluidics has been limited by the lack of the accurate and representative image geometries. This is due to the microstructural similarity of the lymphatics to the blood vessel network, the lack of lymphatic-specific biomarkers, and the technical limitations associated with image resolution in 3D techniques and sectioning artefacts present in 2D techniques.

Micro-computed tomography (µCT) is a non-destructive imaging technique that can reveal the 3D lung microstructure. 3D networks in µCT images are generally identified and segmented by manually tracing their outline, which is very time consuming and requires specialist knowledge of the tissue. We devised a new method to segment 3D networks semi-automatically and specific cell types by correlating µCT imaging with immunofluorescence microscopy.