Established the prediction model of early‐stage non‐small cell lung cancer spread through air spaces (STAS) by radiomics and genomics features

Abstract Background This study was aimed to establish a prediction model for spread through air spaces (STAS) in early‐stage non‐small cell lung cancer based on imaging and genomic features. Methods We retrospectively collected 204 patients (47 STAS+ and 157 STAS−) with non‐small cell lung cancer who underwent surgical treatment in the Jinling Hospital from January 2021 to December 2021. Their preoperative CT images, genetic testing data (including next‐generation sequencing data from other hospitals), and clinical data were collected. Patients were randomly divided into training and testing cohorts (7:3). Results The study included a total of 204 eligible patients. STAS were found in 47 (23.0%) patients, and no STAS were found in 157 (77.0%) patients. The receiver operating characteristic curve showed that radiomics model, clinical genomics model, and mixed model had good predictive performance (area under the curve [AUC] = 0.85; AUC = 0.70; AUC = 0.85). Conclusions The prediction model based on radiomics and genomics features has a good prediction performance for STAS.