English

Refraction beats attenuation in breast CT

Medical Physics 2023-01-03 v1

Abstract

For a century, clinical X-ray imaging has visualised only the attenuation properties of tissue, which fundamentally limits the contrast, particularly in soft tissues like the breast. Imaging based on refraction can overcome this limitation, but so far has been constrained to high-dose ex-vivo applications or required highly coherent X-ray sources, like synchrotrons. It has been predicted that grating interferometry (GI) could eventually allow computed tomography (CT) to be more dose-efficient. However, the benefit of refraction in clinical CT has not been demonstrated so far. Here we show that GI-CT is more dose-efficient in imaging of breast tissue than conventional CT. Our system, based on a 70kVp X-ray tube source and commercially available gratings, demonstrated superior quality, in terms of adipose-to-glandular tissue contrast-to-noise ratio (CNR), of refraction-contrast compared to the attenuation images. The fusion of the two modes of contrast outperformed conventional CT for spatial resolutions better than 263{\mu}m and an average dose to the breast of 16mGy, which is in the clinical breast CT range. Our results show that grating interferometry can significantly reduce the dose, while maintaining the image quality, in diagnostic breast CT. Unlike conventional absorption-based CT, the sensitivity of refraction-based imaging is far from being fully exploited, and further progress will lead to significant improvements of clinical X-ray CT.

Keywords

Cite

@article{arxiv.2301.00455,
  title  = {Refraction beats attenuation in breast CT},
  author = {Michał Rawlik and Alexandre Pereira and Simon Spindler and Zhentian Wang and Lucia Romano and Konstantins Jefimovs and Zhitian Shi and Maxim Polikarpov and Jinqiu Xu and Marie-Christine Zdora and Stefano van Gogh and Martin Stauber and Eduardo Yukihara and Jeppe Brage Christensen and Rahel Kubik-Huch and Tilo Niemann and Cornelia Leo and Zsuzsanna Varga and Andreas Boss and Marco Stampanoni},
  journal= {arXiv preprint arXiv:2301.00455},
  year   = {2023}
}
R2 v1 2026-06-28T07:58:58.579Z