Objective: This study aims to observe the value of the dual-energy computed tomography (DECT) technique in the assessment of primary lung cancer. Compare the difference in density of lung tumors on the true non-contrast (TNC) and virtual non-contrast (VNC) images. Investigate the iodine concentration value of lung tumors in differentiating malignant and benign lesions as well as adenocarcinoma and squamous carcinoma in lung cancer.
Methods: We conducted a cross-sectional descriptive study in 42 patients with solitary pulmonary nodules proved by pathology underwent doublephase enhanced CT scan at the Diagnostic Imaging Center of K Hospital, Hanoi. Process dual-energy CT data into virtual monoenergetic and virtual non-contrast images, comparing with true non-contrast images. Compare the iodine concentration of malignant and benign lesions, adenocarcinoma, and squamous cell carcinoma lung cancer. The slope rate was calculated from the spectral curve. Patients were divided into an inflammatory group, a malignant group, and a tuberculosis group. The Kruskal–Wallis test and Nemenyi test were performed to compare quantitative parameters among the three groups. Results: The study comprised 42 patients (34 males). The mean age of patients was 56 ±11. 23/42 right lung tumors (accounted for about 55%), 13/33 left lung tumors (about 40%). Pathological results showed that 73.8% (31/42) of the lesions were malignant, and 26.2% were benign. The density of lung tumors on the true non-contrast (TNC) and virtual noncontrast (VNC) images is 43,81 ± 10,90 and 43,32 ± 11,15 HU (p=0,147). The contrast-noise ratio of lung tumors has the highest value in the virtual monochrome image at 65 keV. The iodine concentration of malignant tumors was 0,37±0,15mg/ml, higher than benign lesions. The normalized iodine concentration (nIC) of lung tumors can differentiate malignant from benign lesions with an area under the curve of 0,748, with a best cut-off point of 0,27 mg/ml having a sensitivity is 74,2%, specificity of 81,8%. The normalized iodine concentration (nIC) of lung tumors can also differentiate adenocarcinoma from squamous cell carcinoma with an area under the curve of 0,835, with a best cut-off point of 0,36 mg/ml having a sensitivity is 76,5%, specificity of 100%. The mean slope rate for the inflammatory group was 2,51 ± 0,25, significantly higher than these parameters for the malignant group (p < 0.05), and the parameters for the malignant group were significantly higher than the tuberculosis group (p < 0.05). Conclusion: Virtual non-contrast images can replace the role of true non-contrast images. In virtual monoenergetic, the 65 keV sequence has the best Contrast to Noise Ratio (CNR). Quantitative analysis of iodine concentration in lung tumors can help differentiate malignant and benign lung lesions, adenocarcinoma, and squamous cell carcinoma. HU slope rate showed statistically significant differences, which is helpful in the differential diagnosis among inflammatory, malignant, and tuberculosis lesions.