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Updated: Nov 28, 2025
Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
Published on: May 19, 2023
Molecular characterization of solitary pulmonary nodules in dual-energy CT nonlinear image fusion technology
Qian Li1, Huan Tan1, Furong Lv1
1Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
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.
