Pulmonary Emphysema Diagnosis with a Preclinical Small-Animal X-ray Dark-Field Scatter-Contrast Scanner

Research output: Contribution to journalArticle

Abstract

Purpose: To test the hypothesis that the joint distribution of x-ray transmission and dark-field signals obtained with a compact cone-beam preclinical scanner with a polychromatic source can be used to diagnose pulmonary emphysema in ex vivo murine lungs. Materials and Methods: The animal care committee approved this study. Three excised murine lungs with pulmonary emphysema and three excised murine control lungs were imaged ex vivo by using a grating-based micro-computed tomographic (CT) scanner. To evaluate the diagnostic value, the natural logarithm of relative transmission and the natural logarithm of dark-field scatter signal were plotted on a per-pixel basis on a scatterplot. Probability density function was fit to the joint distribution by using principle component analysis. An emphysema map was calculated based on the fitted probability density function. Results: The two-dimensional scatterplot showed a characteristic difference between control and emphysematous lungs. Control lungs had lower average median logarithmic transmission (-0.29 vs -0.18, P = .1) and lower average dark-field signal (-0.54 vs -0.37, P = .1) than emphysematous lungs. The angle to the vertical axis of the fitted regions also varied significantly (7.8 degrees for control lungs vs 15.9 degrees for emphysematous lungs). The calculated emphysema distribution map showed good agreement with histologic findings. Conclusion: X-ray dark-field scatter images of murine lungs obtained with a preclinical scanner can be used in the diagnosis of pulmonary emphysema. (C) RSNA, 2013

Details

Authors
  • Andre Yaroshenko
  • Felix G. Meinel
  • Martin Bech
  • Arne Tapfer
  • Astrid Velroyen
  • Simone Schleede
  • Sigrid Auweter
  • Alexander Bohla
  • Ali Oe. Yildirim
  • Konstantin Nikolaou
  • Fabian Bamberg
  • Oliver Eickelberg
  • Maximilian F. Reiser
  • Franz Pfeiffer
Organisations
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Radiology, Nuclear Medicine and Medical Imaging
Original languageEnglish
Pages (from-to)426-432
JournalRadiology
Volume269
Issue number2
Publication statusPublished - 2013
Publication categoryResearch
Peer-reviewedYes