Development and validation of a nomogram for predicting visceral pleural invasion in solid pulmonary adenocarcinoma nodules with pleural contact

Background Visceral pleural invasion (VPI) is an adverse prognostic factor in lung adenocarcinoma. Accurate preoperative prediction of VPI in solid tumors with pleural contact is crucial for surgical planning and individualized treatment. Methods This was a retrospective study of 162 patients. All patients had surgically resected, pathologically confirmed solid lung adenocarcinoma in pleural contact between November 2018 and August 2025. Patients were classified into VPI-positive and VPI-negative groups based on postoperative pathology. The patients were randomly divided into a training cohort and a testing cohort at a ratio of 7:3. Multivariable logistic regression was performed to identify independent risk factors for VPI. A nomogram prediction model was developed based on the multivariable analysis. Its predictive performance was then evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results Of the 162 patients with solid lung adenocarcinoma nodules, 58 had VPI confirmed by pathology. Multivariate logistic regression analysis identified spiculation, pleural indentation, and pleural contact length as independent risk factors for predicting VPI. A nomogram based on these three CT features showed good discriminative performance in both the training and testing cohorts, with AUCs of 0.901 (95% CI: 0.846–0.956) and 0.864 (95% CI: 0.737–0.937), respectively. Calibration curves showed the predictions matched observations well. Decision curve analysis suggested the nomogram could be clinically useful. Conclusion Among patients with solid lung adenocarcinoma nodules with pleural contact, we developed a nomogram based on routinely assessed CT semantic features to estimate the preoperative probability of VPI. The model is intended as a practical decision-support tool to assist clinical decision-making.