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Three-dimensional high-content imaging of unstained soft tissue with subcellular resolution using a laboratory-based X-ray microscope.

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Title: Three-dimensional high-content imaging of unstained soft tissue with subcellular resolution using a laboratory-based X-ray microscope.
Authors: Esposito, Michela1 michela.esposito@ucl.ac.uk, Astolfo, Alberto1, Zhou, Yang2, Buchanan, Ian1, Teplov, Alexei3, Hutchinson, John Ciaran4, Endrizzi, Marco5, Vinogradova, Alexandra Egido6, Makarova, Olga7, Divan, Ralu8, Tangi, Cha-Mei9, Yagi, Yukako3, Lee, Peter D.2, Walsh, Claire L.2, Ferrara, Joseph D.6, Olivo, Alessandro1
Source: Proceedings of the National Academy of Sciences of the United States of America. 3/24/2026, Vol. 123 Issue 12, p1-8. 18p.
Subjects: X-ray microscopy, Three-dimensional imaging, X-ray imaging, High resolution imaging, Machine learning, Histopathology, Connective tissues, Histology
Abstract: With increasing interest in studying biological systems across spatial scales--from centimeters down to nanometers--histology continues to be the gold standard for tissue imaging at cellular resolution, providing an essential bridge between macroscopic and nanoscopic analysis. However, its inherently destructive and two-dimensional nature limits its ability to capture the full three-dimensional complexity of tissue architecture. Here, we show that phase-contrast X-ray microscopy can enable threedimensional virtual histology with subcellular resolution. This technique provides direct quantification of electron density without restrictive assumptions, allowing for direct characterization of cellular nuclei in a standard laboratory setting. By combining high spatial resolution and soft tissue contrast, with automated segmentation of cell nuclei, we demonstrated virtual Hematoxylin and Eosin (H&E) staining using machine learning-based style transfer, yielding volumetric datasets compatible with existing histopathological analysis tools. Furthermore, by integrating electron density and the sensitivity to nanometric features of the dark field contrast channel, we achieve stainfree, high-content imaging capable of distinguishing nuclei and extracellular matrix. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
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Abstract:With increasing interest in studying biological systems across spatial scales--from centimeters down to nanometers--histology continues to be the gold standard for tissue imaging at cellular resolution, providing an essential bridge between macroscopic and nanoscopic analysis. However, its inherently destructive and two-dimensional nature limits its ability to capture the full three-dimensional complexity of tissue architecture. Here, we show that phase-contrast X-ray microscopy can enable threedimensional virtual histology with subcellular resolution. This technique provides direct quantification of electron density without restrictive assumptions, allowing for direct characterization of cellular nuclei in a standard laboratory setting. By combining high spatial resolution and soft tissue contrast, with automated segmentation of cell nuclei, we demonstrated virtual Hematoxylin and Eosin (H&E) staining using machine learning-based style transfer, yielding volumetric datasets compatible with existing histopathological analysis tools. Furthermore, by integrating electron density and the sensitivity to nanometric features of the dark field contrast channel, we achieve stainfree, high-content imaging capable of distinguishing nuclei and extracellular matrix. [ABSTRACT FROM AUTHOR]
ISSN:00278424
DOI:10.1073/pnas.2525239123