BMC Cancer (May 2023)
CT radiomics features of meso-esophageal fat in predicting overall survival of patients with locally advanced esophageal squamous cell carcinoma treated by definitive chemoradiotherapy
Abstract
Abstract Objective To investigate the value of CT radiomics features of meso-esophageal fat in the overall survival (OS) prediction of patients with locally advanced esophageal squamous cell carcinoma (ESCC). Methods A total of 166 patients with locally advanced ESCC in two medical centers were retrospectively analyzed. The volume of interest (VOI) of meso-esophageal fat and tumor were manually delineated on enhanced chest CT using ITK-SNAP. Radiomics features were extracted from the VOIs by Pyradiomics and then selected using the t-test, the Cox regression analysis, and the least absolute shrinkage and selection operator. The radiomics scores of meso-esophageal fat and tumors for OS were constructed by a linear combination of the selected radiomic features. The performance of both models was evaluated and compared by the C-index. Time-dependent receiver operating characteristic (ROC) analysis was employed to analyze the prognostic value of the meso-esophageal fat-based model. A combined model for risk evaluation was constructed based on multivariate analysis. Results The CT radiomic model of meso-esophageal fat showed valuable performance for survival analysis, with C-indexes of 0.688, 0.708, and 0.660 in the training, internal, and external validation cohorts, respectively. The 1-year, 2-year, and 3-year ROC curves showed AUCs of 0.640–0.793 in the cohorts. The model performed equivalently compared to the tumor-based radiomic model and performed better compared to the CT features-based model. Multivariate analysis showed that meso-rad-score was the only factor associated with OS. Conclusions A baseline CT radiomic model based on the meso-esophagus provide valuable prognostic information for ESCC patients treated with dCRT.
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