Optimizing dual energy cone beam CT protocols for preclinical imaging and radiation research

Br J Radiol. 2017 Jan;90(1069):20160480. doi: 10.1259/bjr.20160480. Epub 2016 Nov 2.

Abstract

Objective: The aim of this work was to investigate whether quantitative dual-energy CT (DECT) imaging is feasible for small animal irradiators with an integrated cone-beam CT (CBCT) system.

Methods: The optimal imaging protocols were determined by analyzing different energy combinations and dose levels. The influence of beam hardening effects and the performance of a beam hardening correction (BHC) were investigated. In addition, two systems from different manufacturers were compared in terms of errors in the extracted effective atomic numbers (Zeff) and relative electron densities (ρe) for phantom inserts with known elemental compositions and relative electron densities.

Results: The optimal energy combination was determined to be 50 and 90 kVp. For this combination, Zeff and ρe can be extracted with a mean error of 0.11 and 0.010, respectively, at a dose level of 60 cGy.

Conclusion: Quantitative DECT imaging is feasible for small animal irradiators with an integrated CBCT system. To obtain the best results, optimizing the imaging protocols is required. Well-separated X-ray spectra and a sufficient dose level should be used to minimize the error and noise for Zeff and ρe. When no BHC is applied in the image reconstruction, the size of the calibration phantom should match the size of the imaged object to limit the influence of beam hardening effects. No significant differences in Zeff and ρe errors are observed between the two systems from different manufacturers. Advances in knowledge: This is the first study that investigates quantitative DECT imaging for small animal irradiators with an integrated CBCT system.

Publication types

  • Review

MeSH terms

  • Absorptiometry, Photon*
  • Animals
  • Cone-Beam Computed Tomography / methods*
  • Diagnostic Imaging / methods
  • Evaluation Studies as Topic
  • Image Processing, Computer-Assisted
  • Models, Animal
  • Phantoms, Imaging*
  • Sensitivity and Specificity