Yang Mingwei, Hu Panpan, Li Minglun, Ding Rui, Wang Yichun, Pan Shuhao, Kang Mei, Kong Weihao, Du Dandan, Wang Fan
Department of Radiation Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Department of Radiotherapy, The First Affiliated Hospital of University of Science and Technology of China (USTC), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
Front Oncol. 2021 Oct 14;11:722961. doi: 10.3389/fonc.2021.722961. eCollection 2021.
Because of the superficial and infiltrative spreading patterns of esophageal squamous cell carcinoma (ESCC), an accurate assessment of tumor extent is challenging using imaging-based clinical staging. Radiomics features extracted from pretreatment computed tomography (CT) or magnetic resonance imaging have shown promise in identifying tumor characteristics. Accurate staging is essential for planning cancer treatment, especially for deciding whether to offer surgery or radiotherapy (chemotherapy) in patients with locally advanced ESCC. Thus, this study aimed to evaluate the predictive potential of contrast-enhanced CT-based radiomics as a non-invasive approach for estimating pathological tumor extent in ESCC patients.
Patients who underwent esophagectomy between October 2011 and September 2017 were retrospectively studied and included 116 patients with pathologically confirmed ESCC. Contrast-enhanced CT from the neck to the abdomen was performed in all patients during the 2 weeks before the operation. Radiomics features were extracted from segmentations, which were contoured by radiologists. Cluster analysis was performed to obtain clusters with similar radiomics characteristics, and chi-squared tests were used to assess differences in clinicopathological features and survival among clusters. Furthermore, a least absolute shrinkage and selection operator was performed to select radiomics features and construct a radiomics model. Receiver operating characteristic analysis was used to evaluate the predictive ability of the radiomics signatures.
All 116 ESCC patients were divided into two groups according to the cluster analysis. The chi-squared test showed that cluster-based radiomics features were significantly correlated with T stage ( = 0.0254) and tumor length ( = 0.0002). Furthermore, CT radiomics signatures exhibited favorable predictive performance for T stage (area under the curve [AUC] = 0.86, sensitivity = 0.77, and specificity = 0.87) and tumor length (AUC = 0.95, sensitivity = 0.92, and specificity = 0.91).
CT contrast radiomics is a simple and non-invasive method that shows promise for predicting pathological T stage and tumor length preoperatively in ESCC patients and may aid in the accurate assessments of patients in combination with the existing examinations.
由于食管鳞状细胞癌（ESCC）具有表面扩散和浸润性扩散模式，使用基于影像学的临床分期准确评估肿瘤范围具有挑战性。从治疗前计算机断层扫描（CT）或磁共振成像中提取的放射组学特征在识别肿瘤特征方面显示出前景。准确分期对于规划癌症治疗至关重要，特别是对于决定局部晚期ESCC患者是否进行手术或放疗（化疗）。因此，本研究旨在评估基于对比增强CT的放射组学作为一种非侵入性方法对ESCC患者病理肿瘤范围的预测潜力。
对2011年10月至2017年9月期间接受食管切除术的患者进行回顾性研究，纳入116例经病理证实为ESCC的患者。所有患者在手术前2周内进行了从颈部到腹部的对比增强CT检查。从放射科医生勾勒轮廓的分割图像中提取放射组学特征。进行聚类分析以获得具有相似放射组学特征的聚类，并使用卡方检验评估聚类间临床病理特征和生存率的差异。此外，进行最小绝对收缩和选择算子以选择放射组学特征并构建放射组学模型。使用受试者工作特征分析来评估放射组学特征的预测能力。
根据聚类分析，所有116例ESCC患者分为两组。卡方检验表明，基于聚类的放射组学特征与T分期（= 0.0254）和肿瘤长度（= 0.0002）显著相关。此外，CT放射组学特征对T分期（曲线下面积[AUC] = 0.86，敏感性 = 0.77，特异性 = 0.87）和肿瘤长度（AUC = 0.95，敏感性 = 0.92，特异性 = 0.91）表现出良好的预测性能。
CT对比放射组学是一种简单且非侵入性的方法，有望在术前预测ESCC患者的病理T分期和肿瘤长度，并可能有助于结合现有检查对患者进行准确评估。
