Radiomics models for predicting occult nodal metastasis in stage cT1a-bN0M0 lung adenocarcinoma: a multicenter study

Background: Preoperative detection of occult nodal metastasis (ONM) is essential for treatment planning and prognostic evaluation in lung adenocarcinoma (LUAD). This study aimed to develop and validate radiomics models capable of predicting ONM in patients with stage cT1a-bN0M0 LUAD. Methods: A total of 1,672 patients from six hospitals were enrolled and stratified into training (n=687), test (n=297) and external validation (n=688) sets. Predictive models including generalized linear model (GLM), support vector machine (SVM), random forest (RF), gradient boosting machine (GBM), and the combined clinical-radiomics (Clinic-Rad) model were constructed. Diagnostic performance was quantified via the area under receiver operating characteristic curve (AUC), with the De Long test used for comparisons. The Mantel test was employed to assess the correlations between radiomics features and pathological/genetic characteristics. Results: expression, as well as histopathological markers of ONM. Conclusions: Radiomics-based models demonstrate clinical utility in predicting ONM in patients with stage cT1a-bN0M0 LUAD, with the integrated Clinic-Rad model providing superior diagnostic performance.