Preoperative nomogram for predicting spread through air spaces in clinical-stage IA non-small cell lung cancer using 18F-fluorodeoxyglucose positron emission tomography/computed tomography

作者：Yun Wang, Deng Lyu, Chao Cheng, Taohu Zhou, Wenting Tu, Yi Xiao, Changjing Zuo, Li Fan, Shiyuan Liu · 发表于：Journal of Cancer Research and Clinical Oncology · 年份：2024 · DOI：10.1007/s00432-024-05674-w · 被引用次数：10 · 研究领域：Lung Cancer Diagnosis and Treatment、Chronic Obstructive Pulmonary Disease (COPD) Research、Inhalation and Respiratory Drug Delivery

Abstract Purpose This study aims to assess the predictive value of 18 F-fluorodeoxyglucose positron emission tomography/computed tomography ( 18 F-FDG PET/CT) radiological features and the maximum standardized uptake value (SUV max ) in determining the presence of spread through air spaces (STAS) in clinical-stage IA non-small cell lung cancer (NSCLC). Methods A retrospective analysis was conducted on 180 cases of NSCLC with postoperative pathological assessment of STAS status, spanning from September 2019 to September 2023. Of these, 116 cases from hospital one comprised the training set, while 64 cases from hospital two formed the testing set. The clinical information, tumor SUV max , and 13 related CT features were analyzed. Subgroup analysis was carried out based on tumor density type. In the training set, univariable and multivariable logistic regression analyses were employed to identify the most significant variables. A multivariable logistic regression model was constructed and the corresponding nomogram was developed to predict STAS in NSCLC, and its diagnostic efficacy was evaluated in the testing set. Results SUV max , consolidation-to-tumor ratio (CTR), and lobulation sign emerged as the best combination of variables for predicting STAS in NSCLC. Among these, SUV max and CTR were identified as independent predictors for STAS prediction. The constructed prediction model demonstrated area under the curve (AUC) values of 0.796 and 0.821 in the training and testing se...