摘要
BACKGROUND Esophageal cancer(EC)is one of the most prevalent malignant gastrointestinal tumors;accurate prediction of EC staging has high significance before treatment.AIM To explore a rational radiomic approach for predicting preoperative staging of EC based on magnetic resonance imaging(MRI).METHODS This retrospective study included 210 patients with pathologically confirmed EC,randomly divided into a primary cohort(n=147)and a validation cohort(n=63)in a ratio of 7:3.All patients underwent a preoperative MRI scan from the neck to the abdomen.High-throughput and quantitative radiomics features were extracted from T2-weighted imaging(T2WI)and gadolinium contrast-enhanced T1-weighted imaging(T1WI)-Gd images.Radiomics signatures were selected using minimal redundancy maximal relevance and the least absolute shrinkage and selection operator.Then a logistic regression model was built to predict the EC stages.The diagnostic performance of the radiomics model for discriminating between stages Ⅰ-Ⅱ and Ⅲ-Ⅳ was evaluated using the area under the curve(AUC),sensitivity(SEN),and specificity(SPE).RESULTS A total of 214 radiomics features were extracted.Following feature dimension reduction,the T1WI and T2WI sequences were retained,and 14 features from the T1WI sequence and 3 features from the T2WI sequence were selected to construct radiomics signatures.The radiomics signature combining T2WI with T1WI-Gd demonstrated superior discrimination of stages in the validation cohort(AUC:0.851;SEN:0.697;SPE:0.793),which outperformed single-sequence models(AUC:0.779,0.844;SEN:0.667,0.636;SPE:0.8,0.8).CONCLUSION MRI-based radiomics signatures could identify EC stages before treatment,which could serve as a noninvasive and quantitative approach aiding personalized treatment planning.
基金
Supported by Guangdong Medical Research Foundation,No.B2023272.
