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Updated: May 27, 2025

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Published on: January 22, 2018
Delta/pre-radiomics based on enhanced CT predicts complete response in locally advanced esophageal squamous cell
Yan Zhu1,2, Zhenzhong Zhang3, Genji Bai2
1Department of Radiology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University Suzhou, Jiangsu, China.
Objectives:
This study aimed to evaluate the effectiveness of neoadjuvant immunochemotherapy (NIC) in patients diagnosed with locally advanced esophageal squamous cell carcinoma (LAESCC), by assessing the performance of models that utilize enhanced computed tomography (CT) images at the pre, post, and delta/pre group stages.
Methods:
A total of 225 patients were included in our study and randomly divided into a training set (n = 157) and test set I (n = 68). In addition, we conducted a test set II involving 60 patients from another center. We obtained omics features from CT images before and after NIC. Then, the delta radiomics features were obtained by calculating the differences between the post and pre group features, which was then divided by the pre group features to obtain the delta/pre group. Imaging and clinicopathological data were collected in the two centers according to the same inclusion and exclusion criteria. The tumor regression grading (TRG) system was used according to the Japanese Esophageal Cancer (11th edition). Three sets of models were built and their performance was assessed using receiver operating characteristic (ROC) curve, confusion matrix, and calibration curve. The clinical utility of the model was evaluated through decision curve analysis and nomogram.
Results:
The area under the curve value of the delta/pre-radiomics (Rad) score model was 0.876 in the training set and 0.827 and 0.749 in the two test sets, which was significantly higher than that in the pre and post Rad score models. The radiomics nomogram was constructed using Rad scores derived from the post model, delta/pre model, Ki67, P53, and the pathological stage of lymph node after neoadjuvant therapy (ypN), demonstrating robust performance. The internal correction curve (apparent) and the external correction curve (bias-corrected) exhibited negligible deviations from the ideal curve, thereby demonstrating a high level of similarity.
Conclusion:
Nomogram, based on delta/pre-enhanced CT features and clinical risk indicators, is a non-invasive tool to predict therapeutic effects in patients with LAESCC after NIC.
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