医学
无线电技术
食管鳞状细胞癌
淋巴结
放射科
基底细胞
疾病
癌
食道疾病
肿瘤科
病理
内科学
食管
作者
Yu Wu,Lun Wu,Jing Ou,Jinming Cao,Mingming Fu,Tianwu Chen,Erika Ouchi,Jiani Hu
标识
DOI:10.1016/j.ejrad.2023.111197
摘要
Abstract
Purpose
To develop CT radiomics models of resectable esophageal squamous cell carcinoma (ESCC) and lymph node (LN) to preoperatively identify LN+. Materials and Methods
299 consecutive patients with ESCC were enrolled in the study, 140 of whom were LN+ and 159 were LN-. Of the 299 patients, 249 (from the same hospital) were randomly divided into a training cohort (n = 174) and a test cohort (n = 75). The remaining 50 patients, from a second hospital, were assigned to an external validation cohort. In the training cohort, preoperative contrast-enhanced CT radiomics features of ESCC and LN were extracted, then integrated with clinical features to develop three models: ESCC, LN and combined. The performance of these models was assessed using area under receiver operating characteristic curve (AUC), and F-1 score, which were validated in both the test cohort and external validation cohort. Results
An ESCC model was developed for the training cohort utilizing the 8 tumor radiomics features, and an LN model was constructed using 9 nodal radiomics features. A combined model was constructed using both ESCC and LN extracted features, in addition to cT stage and LN+ distribution. This combined model had the highest predictive ability among the three models in the training cohort (AUC = 0.948, F1-score = 0.878). The predictive ability was validated in both the test and external validation cohorts (AUC = 0.885 and 0.867, F1-score = 0.816 and 0.773, respectively). Conclusion
To preoperatively determine LN+, the combined model is superior to models of ESCC and LN alone.
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