Molecular characterization of solitary pulmonary nodules in dual-energy CT nonlinear image fusion technology

J Recept Signal Transduct Res. 2022 Feb;42(1):95-99. doi: 10.1080/10799893.2020.1853158. Epub 2020 Nov 30.

Abstract

Objective: To investigate the feasibility and to optimize the parameters of nonlinear blending technique in dual-energy CT on solitary pulmonary nodules (SPN).

Methods: The simulated enhanced SPN were used the mixture of nonionic iodinated contrast agent (Iopromide 370mgI/100 ml) and normal saline and then randomly placed inside an anthropomorphic chest phantom. The phantom was examined on SOMATOM definition flash with dual mode (80/140 kV) and single energy mode (120 kV) (the same CTDIvol). Nonlinear blending images and linear blending images with a weighting factor of 0.3 were generated and the image qualities were analyzed.

Results: For different simulated density SPN, when 0 HU was chosen as the Blending Center (BC) and 0 to 30 HU were chosen as the Blending width (BW), the nonlinear blending images yielded a higher contrast-to-noise (CNR). There were significant differences in the image noise and signal-to-noise (SNR) of different simulated density SPN at non-linear blending images, linear blending images and 120 kV images (p < .05); But the differences of CNR between the three groups were not statistically significant (p > .05). The SNR of different simulated density SPN at non-linear blending images was significantly increased compared with it at linear blending images and 120 kV images (p < .05); And the image noise at non-linear blending was lower than it at linear blending images (p < .05).

Conclusion: Nonlinear blending technique in dual-energy CT can increase the SNR of enhanced SPN, and it is helpful in diagnosis of SPN.

Keywords: Dual-energy CT; non-linear blending; solitary pulmonary nodule.

MeSH terms

  • Humans
  • Phantoms, Imaging
  • Radiographic Image Interpretation, Computer-Assisted*
  • Solitary Pulmonary Nodule* / diagnostic imaging
  • Technology
  • Tomography, X-Ray Computed