RESUMO
Objective:To evaluate the value of dual-layer spectral detector CT (DLSDCT) in precise radiotherapy for central lung cancer (CLC) complicated with atelectasis.Methods:Clinical and imaging data (including DLSDCT, PET-CT, and radiotherapy simulation CT images) of 26 patients with pathologically confirmed CLC accompanied by atelectasis from the Third Affiliated Hospital of Shandong First Medical University and Shandong Cancer Hospital were analyzed retrospectively. There were 21 males and 5 females, aged 36-82 years. Two physicians assessed CLC identifiability on DLSDCT, PET-CT, and simulation localization CT images, respectively, and outlined the gross tumor volume (GTV) and measured GTV values (GTV DLSDCT, GTV PET-CT, GTV CT). Paired-sample Friedman test was used to compare the differences in GTV of the three images, and the SNK test with Bonferroni correction was used for a two-way comparison. The intra-class correlation coefficient (ICC) was used to compare the agreement of measured GTV between 2 physicians. Results:The differentiation rates on PET-CT, DLSDCT, and simulation CT images were 100% (26/26), 80.77% (21/26), and 11.54% (3/26), respectively. The differentiation rate of CLC on DLSDCT images was significantly higher than that on simulation CT images (χ 2=16.06, P<0.001). GTV CT, GTV PET-CT, and GTV DLSDCT measured on simulation localization CT images, PET-CT images, and DLSDCT images were 58.75 (22.57, 86.17) cm 3, 47.34 (18.13, 69.25) cm 3, and 51.40 (18.87, 71.31) cm 3, respectively, with statistically significant differences (χ 2=44.99, P<0.001). Both GTV DLSDCT and GTV PET-CT were significantly smaller than GTV CT (χ 2=4.23, 6.59, Bonferroni corrected P<0.001), and there was no significant difference between GTV DLSDCT and GTV PET-CT (χ 2=2.36, Bonferroni corrected P=0.055). The agreement between the two physicians was good for GTV values measured on both DLSDCT and PET-CT (ICC=0.86, 0.89). Conclusions:On DLSDCT images, most CLC and atelectasis can be identified. Compared to simulation localization CT, the tumor target areas outlined on DLSDCT are closer to PET-CT, and the tumor volumes outlined by different physicians are more consistent.
RESUMO
Objective:To evaluate the application value of double-layer spectral detector CT (DLSDCT) in differentiating central lung cancer from atelectasis.Methods:Fifty-one patients with central lung cancer accompanied by atelectasis confirmed by pathology in Shandong Cancer Hospital from January to December 2020 were enrolled. The differentiating rates of tumor from atelectasis of the conventional CT, 40 keV virtual monoenergetic imaging (MonoE), iodine density map (ID), and 40 keV MonoE-ID fusion images of unenhanced scan, arterial and venous phase were retrospectively analyzed. Cochran′s Q test was used to compare the differentiating rate (Bonferroni correction afterwards), and Friedman test was used to compare the maximum diameter of the tumor of each imaging method.Results:Of the 51 patients, none of the conventional CT images, 40 keV MonoE, ID and 40 keV MonoE-ID fusion images in the unenhanced scan could distinguish lung tumors from atelectasis; the number of cases in which the conventional CT images, 40 keV MonoE, ID and 40 keV MonoE-ID fusion images in the arterial phase could distinguish lung tumors from atelectasis regions was 4, 5, 5 and 6, respectively; the number of cases in which the conventional CT, 40 keV MonoE, ID and 40 keV MonoE-ID fusion images in the venous phase could distinguish lung tumors from atelectasis regions was 17, 35, 39 and 38, respectively, and the difference was statistically significant (χ 2=52.40, P<0.001). The differentiating rates of the 40 keV MonoE, ID, and 40 keV MonoE-ID fusion image were significantly higher than that of conventional CT image (χ2=-0.35, -0.43, -0.41, P<0.001, Bonferroni correction afterwards); There was no significant difference in the differentiating rate among 40 keV MonoE, ID and MonoE-ID fusion image ( P=1.00). Seventeen tumors could be differentiated in conventional CT images, 40 keV MonoE, ID and 40 keV MonoE-ID fusion images of venous phase, and the maximum diameters of lung tumors were (50±21) mm, (50±23) mm, (50±23) mm, and (50±23) mm, respectively, and the difference was not statistically significant (χ2=3.61, P=0.31). Conclusions:The venous phase spectral images of DLSDCT can differentiate most central lung cancer from atelectasis. Therefore, it has great clinical application value in tumor staging, efficacy evaluation, and radiotherapy.