AI Article Synopsis

  • X-ray chest radiography is commonly used for lung assessments but is not very sensitive for early pulmonary disease detection.
  • Recent studies of X-ray dark-field (XDF) imaging on mice show it significantly improves early diagnosis of conditions like chronic obstructive pulmonary disease (COPD) compared to standard radiography.
  • This study presents the first successful in-vivo XDF imaging of a pig's chest, paving the way for potential use in humans and indicating a shift in how lung conditions might be diagnosed in high-risk patients.

Article Abstract

X-ray chest radiography is an inexpensive and broadly available tool for initial assessment of the lung in clinical routine, but typically lacks diagnostic sensitivity for detection of pulmonary diseases in their early stages. Recent X-ray dark-field (XDF) imaging studies on mice have shown significant improvements in imaging-based lung diagnostics. Especially in the case of early diagnosis of chronic obstructive pulmonary disease (COPD), XDF imaging clearly outperforms conventional radiography. However, a translation of this technique towards the investigation of larger mammals and finally humans has not yet been achieved. In this letter, we present the first in-vivo XDF full-field chest radiographs (32 × 35 cm) of a living pig, acquired with clinically compatible parameters (40 s scan time, approx. 80 µSv dose). For imaging, we developed a novel high-energy XDF system that overcomes the limitations of currently established setups. Our XDF radiographs yield sufficiently high image quality to enable radiographic evaluation of the lungs. We consider this a milestone in the bench-to-bedside translation of XDF imaging and expect XDF imaging to become an invaluable tool in clinical practice, both as a general chest X-ray modality and as a dedicated tool for high-risk patients affected by smoking, industrial work and indoor cooking.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5500502PMC
http://dx.doi.org/10.1038/s41598-017-05101-wDOI Listing

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