CT feature-based nomogram for predicting tumor spread through air spaces in stage IA lung adenocarcinoma.

Abstract

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 favorable clinical utility, with a sensitivity of 69.5% and a specificity of 80.2%.

Conclusion: The nomogram reliably predicts STAS preoperatively and may assist in guiding surgical decision-making.