The authors of this retrospective study aimed to develop and validate a CT-based radiomics model for preoperative prediction of spread through air space (STAS) in lung adenocarcinoma. They found that a CT-based radiomics model can preoperatively predict, with good diagnosis performance, STAS in lung adenocarcinoma.
Key points
- CT-based radiomics and machine learning model can predict spread through air space (STAS) in lung adenocarcinoma with high accuracy.
- The random forest (RF) model achieved an AUC of 0.754 (a sensitivity of 0.880 and a specificity of 0.588) for predicting STAS.
Article: CT-based radiomics and machine learning to predict spread through air space in lung adenocarcinoma
Authors: Changsi Jiang, Yan Luo, Jialin Yuan, Shuyuan You, Zhiqiang Chen, Mingxiang Wu, Guangsuo Wang & Jingshan Gong
