Abstract： Objective:To explore the predictive value of qualitative and quantitative parameters of dual-layer spectral detector CT plain scan on the invasiveness of pure ground-glass pulmonary nodules (pGGNs).Methods:Clinical and imaging data of 113 patients (119 pGGNs) with pathology-proven lung adenocarcinoma who underwent preoperative dual-layer spectral detector CT plain scan in Tianjin Medical University Cancer Institute and Hospital from November 2019 to December 2020 were retrospectively analyzed. According to invasiveness, pGGNs were divided into non-invasive adenocarcinoma (non-IA) group ( n=66) and IA group ( n=53). The non-IA group included atypical adenomatous hyperplasia ( n=10), adenocarcinoma in situ ( n=26) and minimally invasive adenocarcinoma ( n=30). The qualitative parameters were nodule shape, lung-tumor interface, lobulation, spiculation, pleural retraction, bubblelike lucency, air bronchogram and vascular abnormality. The quantitative parameters included nodule size, effective atomic number (Z eff), CT value on 120 kVp images (CT 120 kVp) and virtual monoenergetic images from 40 keV to 200 keV (CT 40 keV-CT 200 keV), and slope of energy spectrum curve (λHU). The χ 2 test, Mann-Whitney U test and independent sample t test were used to analyze the parameter differences between non-IA group and IA group. Multivariate logistic regression analysis was performed to screen out independent predictors. Receiver operating characteristic (ROC) curve was used to assess the diagnostic efficacy of single predictor and combined independent factors for the invasiveness of pGGN. Results:Significant differences were found in nodule shape, lobulation, air bronchogram, vascular abnormality, nodules size, Z eff, CT 120 kVp and CT 40 keV-CT 200 keV between non-IA and IA groups ( P<0.05). The maltivariate logistic regression analysis showed that nodule size [odds ratio 9.269, 95% confidence interval (CI) 1.640-52.395, P=0.012] CT 200 keV (odds ratio 1.012, 95%CI 1.006-1.019, P<0.001) as well as vascular abnormality sign (odds ratio 4.940, 95%CI 1.358-17.969, P=0.015) were independent predictors of pGGN invasiveness. ROC curve analysis of a single independent predictor and a combination of the three factors showed that the area under the curve (AUC) of the combination of three factors predicting the invasiveness of pGGN was significantly higher than the AUC of vascular abnormality sign ( Z=4.01, P<0.001) and CT 200 keV ( Z=3.25, P=0.001), while there was no significant difference in AUC between the combination of the three factors and nodule size ( Z=1.94, P=0.052). The AUC of the combination of the three independent predictors was 0.909, and the sensitivity and specificity for predicting pGGN invasion were 81.1% and 86.4%, respectively, using a threshold of 0.505. Conclusion:The combination of qualitative and quantitative parameters of dual-layer spectral detector CT plain scan shows a high predictive value for the invasiveness of pGGNs.