A combined model based on dual-energy CT for predicting high-risk lung adenocarcinoma in nodules with solid component

Background High-risk factors of lung adenocarcinoma (LUAD), including poorly differentiated pattern, lymphovascular invasion, visceral pleural invasion, lymph node metastasis, and spread through air spaces, are associated with poor prognosis. Purpose To construct and validate a combined model based on dual-energy computed tomography (DECT) for predicting high-risk LUAD in nodules with solid components. Material and Methods A total of 539 pathologically confirmed LUADs were retrospectively enrolled and were randomly divided into training (n = 377) and testing cohorts (n = 162) (ratio = 7:3). DECT quantitative parameters, conventional quantitative-semantic features, and clinical characteristics were collected. Univariable and multivariable logistic regression was used to construct the conventional CT model, DECT model, and combined model. Area under the curve (AUC) was used to evaluate diagnostic performance of models. Results The combined model (features: sex, diameter, pleural indentation, electron density in venous phase [Rho_V], and NIC_A [normalized iodine concentration in arterial phase]) showed significantly higher AUC than the DECT model (features: Rho_V and NIC_A) (0.899 vs. 0.870; P = 0.005) and the conventional CT model (features: diameter and pleural indentation) (0.899 vs. 0.742; P <0.001) in the training cohort. In the testing cohort, the combined model showed significantly higher AUC than the conventional CT model (0.852 vs. 0.704; P <0.001), but no significant difference in AUC was found between the combined model and the DECT model (0.852 vs. 0.838; P = 0.354). Conclusion The combined model based on DECT has good diagnostic performance in predicting high-risk LUAD in nodules with solid components.