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

M Michela Esposito (Department of Medical Physics and Biomedical Engineering) A Alberto Astolfo (Department of Medical Physics and Biomedical Engineering) Y Yang Zhou I Ian Buchanan (Department of Medical Physics and Biomedical Engineering) A Alexei Teplov (Department of Pathology and Lab Medicine) J John Ciaran Hutchinson (Department of Histopathology) M Marco Endrizzi (Department of Medical Physics and Biomedical Engineering) A Alexandra Egido Vinogradova (Rigaku Americas) O Olga Makarova (Creatv MicroTech Inc.) R Ralu Divan (Center for Nanoscale Materials) C Cha-Mei Tang (Creatv MicroTech Inc.) Y Yukako Yagi (Department of Pathology and Lab Medicine) P Peter D. Lee (Department of Mechanical Engineering) C Claire L. Walsh (Department of Mechanical Engineering) J Joseph D. Ferrara (Rigaku Americas) A Alessandro Olivo (Department of Medical Physics and Biomedical Engineering)

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 three-dimensional 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 stain-free, high-content imaging capable of distinguishing nuclei and extracellular matrix.

Article Details

Volume / Issue Vol. 123, Issue 12
Published March 24, 2026
ISSN 0027-8424
Publisher National Academy of Sciences

Authors (16)

M

Michela Esposito

Department of Medical Physics and Biomedical Engineering

A

Alberto Astolfo

Department of Medical Physics and Biomedical Engineering

Y

Yang Zhou

I

Ian Buchanan

Department of Medical Physics and Biomedical Engineering

A

Alexei Teplov

Department of Pathology and Lab Medicine

J

John Ciaran Hutchinson

Department of Histopathology

M

Marco Endrizzi

Department of Medical Physics and Biomedical Engineering

A

Alexandra Egido Vinogradova

Rigaku Americas

O

Olga Makarova

Creatv MicroTech Inc.

R

Ralu Divan

Center for Nanoscale Materials

C

Cha-Mei Tang

Creatv MicroTech Inc.

Y

Yukako Yagi

Department of Pathology and Lab Medicine

P

Peter D. Lee

Department of Mechanical Engineering

C

Claire L. Walsh

Department of Mechanical Engineering

J

Joseph D. Ferrara

Rigaku Americas

A

Alessandro Olivo

Department of Medical Physics and Biomedical Engineering