Scientific Reports (Mar 2024)

Integrating X-ray phase-contrast imaging and histology for comparative evaluation of breast tissue malignancies in virtual histology analysis

  • Sandro Donato,
  • Lucia Mariel Arana Peña,
  • Fulvia Arfelli,
  • Luca Brombal,
  • Luisella Colmo,
  • Renata Longo,
  • Fulvia Martellani,
  • Giuliana Tromba,
  • Fabrizio Zanconati,
  • Deborah Bonazza

DOI
https://doi.org/10.1038/s41598-024-56341-6
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 13

Abstract

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Abstract Detecting breast tissue alterations is essential for cancer diagnosis. However, inherent bidimensionality limits histological procedures’ effectiveness in identifying these changes. Our study applies a 3D virtual histology method based on X-ray phase-contrast microtomography (PhC $$\mu$$ μ CT), performed at a synchrotron facility, to investigate breast tissue samples including different types of lesions, namely intraductal papilloma, micropapillary intracystic carcinoma, and invasive lobular carcinoma. One-to-one comparisons of X-ray and histological images explore the clinical potential of 3D X-ray virtual histology. Results show that PhC $$\mu$$ μ CT technique provides high spatial resolution and soft tissue sensitivity, while being non-destructive, not requiring a dedicated sample processing and being compatible with conventional histology. PhC $$\mu$$ μ CT can enhance the visualization of morphological characteristics such as stromal tissue, fibrovascular core, terminal duct lobular unit, stromal/epithelium interface, basement membrane, and adipocytes. Despite not reaching the (sub) cellular level, the three-dimensionality of PhC $$\mu$$ μ CT images allows to depict in-depth alterations of the breast tissues, potentially revealing pathologically relevant details missed by a single histological section. Compared to serial sectioning, PhC $$\mu$$ μ CT allows the virtual investigation of the sample volume along any orientation, possibly guiding the pathologist in the choice of the most suitable cutting plane. Overall, PhC $$\mu$$ μ CT virtual histology holds great promise as a tool adding to conventional histology for improving efficiency, accessibility, and diagnostic accuracy of pathological evaluation.