本研究利用计算机断层扫描 (CT) 探讨了食管鳞状细胞癌 (ESCC) 的瘤内异质性 (ITH)，并研究了基于 CT 的 ITH 在预测食管鳞状细胞癌患者对免疫检查点抑制剂 (ICI) 联合化疗反应中的价值。这项回顾性研究纳入了 2019 年 1 月至 2022 年 7 月期间在两家独立医院接受 ICI 加化疗的 416 名 ESCC 患者。从 ESCC 病灶中提取多参数 CT 特征，并使用层次聚类和降维算法进行筛选。开发了基于选定特征的逻辑回归和机器学习模型来预测治疗反应并在单独的数据集中进行验证。 ITH 使用性能最佳模型计算的分数进行量化，并通过特征聚类和特征贡献热图进行可视化。进行基因集富集分析（GSEA）来识别基于 CT 的 ITH 的生物学途径。基于 CT 衍生的 ITH 的极端梯度增强模型具有更高的判别力，受试者工作特征曲线下面积为 0.864（95内部和外部验证集中的%置信区间 [CI]：0.774-0.954）和 0.796（95% CI：0.698-0.893）。基于 CT 的 ITH 模式在有反应和无反应患者之间存在显着差异。 GSEA 表明，基于 CT 的 ITH 与免疫、角化和表皮细胞分化相关途径相关。基于 CT 的 ITH 是一种有效的生物标志物，可用于识别 ESCC 患者是否可以从 ICI 加化疗中受益。免疫、角化和表皮细胞分化相关途径可能会影响患者对 ICI 加化疗的反应。版权所有 © 2024 大学放射科医生协会。由爱思唯尔公司出版。保留所有权利。

This study explored the intratumor heterogeneity (ITH) of esophageal squamous cell carcinoma (ESCC) using computed tomography (CT) and investigated the value of CT-based ITH in predicting the response to immune checkpoint inhibitor (ICI) plus chemotherapy in patients with ESCC.This retrospective study included 416 patients with ESCC who received ICI plus chemotherapy at two independent hospitals between January 2019 and July 2022. Multiparametric CT features were extracted from ESCC lesions and screened using hierarchical clustering and dimensionality reduction algorithms. Logistic regression and machine learning models based on selected features were developed to predict treatment response and validated in separate datasets. ITH was quantified using the score calculated by the best-performing model and visualized through feature clustering and feature contribution heatmaps. A gene set enrichment analysis (GSEA) was performed to identify the biological pathways underlying the CT-based ITH.The extreme gradient boosting model based on CT-derived ITH had higher discriminative power, with areas under the receiver operating characteristic curve of 0.864 (95% confidence interval [CI]: 0.774-0.954) and 0.796 (95% CI: 0.698-0.893) in the internal and external validation sets. The CT-based ITH pattern differed significantly between responding and non-responding patients. The GSEA indicated that CT-based ITH was associated with immunity-, keratinization-, and epidermal cell differentiation-related pathways.CT-based ITH is an effective biomarker for identifying patients with ESCC who could benefit from ICI plus chemotherapy. Immunity-, keratinization-, and epidermal cell differentiation-related pathways may influence the patient's response to ICI plus chemotherapy.Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.