Preoperative Contrast-enhanced CT Features Associated with Occult Lymph Node Metastasis in Early-Stage Solid...

Purpose To develop and validate a contrast-enhanced CT-based prediction model for identifying occult lymph node metastasis (OLNM) in patients with early-stage non-small cell lung cancer (NSCLC), with the goal of supporting individualized lymph node dissection (LND) strategies. Materials and Methods This retrospective study included patients with preoperative clinical stage I-IIA (cT1-T2bN0M0) solid NSCLC who underwent lobectomy with systematic LND between January 2021 and April 2024. Univariable and multivariable logistic regression analyses were used to identify independent preoperative CT predictors of OLNM and to construct a nomogram. Model performance was assessed using the area under the receiver operating characteristic curve, and specificity was evaluated at a fixed sensitivity of 95%. Results Among 329 patients with solid NSCLC (median age, 65 years; IQR, 58-70 years; 168 male patients), 22.2% (73 of 329) had OLNM, including 47.9% (35 of 73) with N1 and 52.1% (38 of 73) with N2 metastases. Independent predictors of OLNM were a decreased inner margin ratio (odds ratio [OR], 0.02; 95% CI: 0.00, 0.10; P < .001), presence of the lollipop sign (OR, 3.48; 95% CI: 1.87, 6.49; P < .001), and tumor-pleura relationship type II (OR, 6.95; 95% CI: 2.62, 18.44; P < .001) and type III (OR, 13.27; 95% CI: 5.11, 34.45; P < .001). The nomogram achieved an area under the receiver operating characteristic curve of 0.81 (95% CI: 0.76, 0.87), with a sensitivity of 78.1% and specificity of 73.4%; specificity was 39.1% at 95% sensitivity. Conclusion A contrast-enhanced CT-based nomogram incorporating inner margin ratio, lollipop sign, and tumor-pleura relationship enabled effective preoperative risk stratification for OLNM in early-stage solid NSCLC and may aid in tailoring LND strategies. Keywords: Imaging Modality, Lung, Neoplasms-Primary, Thorax Supplemental material is available for this article. © The Author(s) 2026. Published by the Radiological Society of North America under a CC BY 4.0 license.