Joca, H.; Silva, P. A.; Santos, J.; Dias, E.; Barbosa, T. P.; Degaki, K.; Morales, R.; Terra, M.; Rabelo, R. S.; Cardoso, M. B.; Saito, A.; Avelino, T. M.

Conventional two-dimensional (2D) histology relies upon destructive sample preparation and stereological estimation, frequently leading to sampling bias and loss of critical spatial context required for understanding renal structure relationships. Here, we detail a novel pipeline for high-resolution 3D histology of ex vivo murine kidneys using X-ray micro-computed tomography (micro-CT) at the high flux of a synchrotron light source, the architecture of the nephron and associated microvasculature necessitates three-dimensional (3D) analysis to accurately characterize its complexity. Soft-tissue contrast was optimized through an established phosphotungstic acid (PTA) staining protocol, enabling robust mapping of macro and microstructures via absorption contrast. Multi-scale imaging was performed, providing whole-organ context at resolutions around 3 m and achieving sub-micron detail (down to 400 nm) in targeted regions of interest (ROI) of the renal cortex. Utilizing machine learning segmentation pipelines optimized for large volumetric datasets, we extracted crucial 3D quantitative morphometric data. The results presented herein demonstrate accuracy and morphological insight achievable through synchrotron-based 3D imaging, establishing a robust method for quantitative preclinical research.