Prediction of epithelial-to-mesenchymal transition molecular subtype using CT in gastric cancer.
Dong Ik ChaJeeyun LeeWoo Kyoung JeongSeung Tae KimJae-Hun KimJung Yong HongWon Ki KangKyoung-Mee KimSeon Woo KimDongil ChoiPublished in: European radiology (2021)
• A predictive model for epithelial-to-mesenchymal transition (EMT) subtype incorporating patient's age, Lauren classification, and mural stratification on CT was built. • The predictive model had high diagnostic accuracy (area under the curve (AUC) = 0.865) and was validated (bootstrap AUC = 0.860). • Adding CT findings to clinicopathologic variables increases the accuracy of the predictive model than using only.