Scientific Reports (Feb 2023)

The choice of an autocorrelation length in dark-field lung imaging

  • Simon Spindler,
  • Dominik Etter,
  • Michał Rawlik,
  • Maxim Polikarpov,
  • Lucia Romano,
  • Zhitian Shi,
  • Konstantins Jefimovs,
  • Zhentian Wang,
  • Marco Stampanoni

DOI
https://doi.org/10.1038/s41598-023-29762-y
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 11

Abstract

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Abstract Respiratory diseases are one of the most common causes of death, and their early detection is crucial for prompt treatment. X-ray dark-field radiography (XDFR) is a promising tool to image objects with unresolved micro-structures such as lungs. Using Talbot-Lau XDFR, we imaged inflated porcine lungs together with Polymethylmethacrylat (PMMA) microspheres (in air) of diameter sizes between 20 and 500 $$\upmu \hbox {m}$$ μ m over an autocorrelation range of 0.8–5.2 $$\upmu \hbox {m}$$ μ m . The results indicate that the dark-field extinction coefficient of porcine lungs is similar to that of densely-packed PMMA spheres with diameter of $${200}\,\upmu \hbox {m}$$ 200 μ m , which is approximately the mean alveolar structure size. We evaluated that, in our case, the autocorrelation length would have to be limited to $${0.57}\,\upmu \hbox {m}$$ 0.57 μ m in order to image $${20}\,\hbox {cm}$$ 20 cm -thick lung tissue without critical visibility reduction (signal saturation). We identify the autocorrelation length to be the critical parameter of an interferometer that allows to avoid signal saturation in clinical lung dark-field imaging.