CT Feature-Based Nomogram for Predicting Tumor Spread Through Air Spaces in Stage IA Lung Adenocarcinoma

Objectives This research aimed to examine the relationships between clinicopathological characteristics and the occurrence of Spread Through Air Spaces (STAS) in patients with stage IA lung adenocarcinoma (LUAD) and to develop a preoperative prediction model. Methods Data from 1,375 patients with stage IA LUAD at Sun Yat-sen University Cancer Center were analyzed. Propensity score matching (PSM) was employed to match 141 STAS-positive patients with 282 STAS-negative patients. Both univariate and multivariate logistic regression analyses were performed to determine independent variables among 16 clinicopathological and 13 CT imaging characteristics. A nomogram prediction model was developed and evaluated via receiver operating characteristic (ROC) and decision curve analyses (DCAs). Results Multivariate analysis identified several independent risk factors. Irregular nodule shape (OR = 1.817, 95% CI: 1.106–2.986, p  = 0.018), irregular margin (OR = 2.050, 95% CI: 1.218–3.449, p  = 0.007), lobulation (OR = 2.235, 95% CI: 1.336–3.739, p  = 0.002), and vascular convergence (OR = 5.032, 95% CI: 2.050–12.349, p  < 0.001) were significantly associated with an increased risk of STAS. Compared with a consolidation tumor ratio (CTR) = 0% (reference), a CTR of 75–100% (OR = 7.086, 95% CI: 2.542–19.750, p  < 0.001) and a CTR = 100% (OR = 11.502, 95% CI: 4.752–27.840, p  < 0.001) were significantly associated with an increased risk of STAS. The nomogram was developed and internally validated, demonstrating good predictive accuracy (AUC = 0.812, 95% CI: 0.761–0.863) and clinical utility. Conclusion The nomogram reliably predicts STAS preoperatively and may assist in guiding surgical decision-making.