Performance evaluation of dual-energy CT and differential phase contrast CT in quantitative imaging applications

Med Phys. 2022 Feb;49(2):1123-1138. doi: 10.1002/mp.15417. Epub 2022 Jan 10.

Abstract

Purpose: The purpose of this study is to evaluate and compare the quantitative material decomposition performance of the dual-energy CT (DECT) and differential phase contrast CT (DPCT) via numerical observer studies.

Methods: The electron density ( ρ e $\rho _{{\rm e}}$ ) and the effective atomic number ( Z eff $Z_{{\rm eff}}$ ) are selected as the decomposition bases. The image domain based decomposition algorithms with certain noise suppression are used to extract the ρ e $\rho _{{\rm e}}$ and Z eff $\text{Z}_{{\rm eff}}$ information under three different spatial resolutions (0.3 mm, 0.1 mm, and 0.03 mm). The contrast-to-noise-ratio (CNR) and the numerical human observer model which is sensitive to the noise textures are investigated to compare the quantitative imaging performance of DECT and DPCT under varied radiation dose levels.

Results: The model observer results show that the DECT is superior to DPCT at 0.3 mm spatial resolution (300 mm object size); the DECT and DPCT show similar quantitative imaging performance at 0.1 mm spatial resolution (100 mm object size); and the DPCT outperforms the DECT by approximately 1.5 times for the 0.3 mm sized imaging target at 0.03 mm spatial resolution (30 mm object size).

Conclusions: In conclusion, the DECT would be recommended to obtain ρ e $\rho _{{\rm e}}$ and Z eff $Z_{{\rm eff}}$ for the low spatial resolution quantitative imaging applications such as the diagnostic CT imaging. Whereas, the DPCT would be recommended for ultra high spatial resolution imaging tasks of small objects such as the micro-CT imaging. This study provides a reference to determine the most appropriate quantitative X-ray CT imaging method for a certain radiation dose level.

Keywords: different spatial resolutions; differential phase contrast CT; dual-energy CT; human observer model; material decomposition; performance evaluation.

MeSH terms

  • Algorithms*
  • Humans
  • Phantoms, Imaging
  • Radiation Dosage
  • Tomography, X-Ray Computed*