Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
GE Healthcare, Beijing, China.
Eur Radiol. 2021 Aug;31(8):5967-5979. doi: 10.1007/s00330-021-07690-7. Epub 2021 Feb 2.
To explore the role of radiomics in integrating primary tumor and peritumoral areas based on PET-CT scans for predicting E-cadherin (E-cad) expression in early-stage cervical cancer (ESCC) and its correlation with pelvic lymph node metastasis (PLNM).
Ninety-seven ESCC patients who had undergone PET-CT scans were retrospectively analyzed. The ROI of primary tumors, peritumoral areas, and plus tumors were semi-automatically segmented on PET-CT images. A total of 1188 radiomics features were extracted, selected, and eventually integrated into radiomics score (rad-score). The rad-score difference between patients with E-cad expression of high and low was analyzed using Mann-Whitney tests. Characteristic correlation was tested using a Spearman analysis. Four models were established using logistic regression algorithms and evaluated using ROC and calibration curves. A DeLong test was used to perform pairwise comparisons of AUCs.
The rad-score of patients with low E-cad expression was higher than that of patients with high E-cad expression in both training and testing cohorts (p < 0.001 and p = 0.027, respectively). A significant correlation was observed between the rad-score and E-cad (p < 0.001). PLNM correlated slightly with rad-score and E-cad values (p = 0.01 and p < 0.001, respectively). The ROC curve and calibration curve of the rad-score model performed best in both training and testing cohorts (AUC = 0.915, 0.844, p < 0.001, respectively).
The radiomics of integrating primary tumor and peritumoral areas based on PET-CT showed correlations with PLNM. It was also able to predict E-cad expression in ESCC patients, allowing for evaluation of those patients' prognosis and more individualized medical treatment.
• By integrating the primary tumor and peritumoral area based on PET-CT, radiomics was feasible. • The rad-score was associated with E-cad expression and PLNM in patients with ESCC. • Radiomics that integrated the primary tumor and peritumoral areas based on PET-CT could predict E-cad expression in patients with ESCC.
探讨基于 PET-CT 扫描的原发肿瘤和瘤周区的影像组学在预测早期宫颈癌（ESCC）E-钙黏蛋白（E-cad）表达中的作用及其与盆腔淋巴结转移（PLNM）的相关性。
回顾性分析 97 例接受 PET-CT 扫描的 ESCC 患者。在 PET-CT 图像上对原发肿瘤、瘤周区和加瘤区的 ROI 进行半自动分割。共提取、选择了 1188 个影像组学特征，并最终整合为影像组学评分（rad-score）。采用 Mann-Whitney 检验分析 E-cad 高、低表达患者之间的 rad-score 差异。采用 Spearman 分析进行特征相关性检验。采用逻辑回归算法建立 4 个模型，并通过 ROC 和校准曲线进行评估。采用 DeLong 检验对 AUC 进行两两比较。
在训练组和测试组中，E-cad 低表达患者的 rad-score 均高于 E-cad 高表达患者（p<0.001 和 p=0.027）。rad-score 与 E-cad 之间存在显著相关性（p<0.001）。PLNM 与 rad-score 和 E-cad 值略有相关（p=0.01 和 p<0.001）。在训练组和测试组中，rad-score 模型的 ROC 曲线和校准曲线表现最佳（AUC=0.915、0.844，p<0.001）。
基于 PET-CT 的原发肿瘤和瘤周区的影像组学与 PLNM 相关，也能预测 ESCC 患者的 E-cad 表达，有助于评估患者的预后，并进行更个体化的治疗。
基于 PET-CT，原发肿瘤和瘤周区的整合影像组学是可行的。
rad-score 与 ESCC 患者的 E-cad 表达和 PLNM 相关。
基于 PET-CT 的原发肿瘤和瘤周区的影像组学可预测 ESCC 患者的 E-cad 表达。
