Qiu Hui, Xu Muchen, Wang Yan, Wen Xin, Chen Xueting, Liu Wanming, Zhang Nie, Ding Xin, Zhang Longzhen
Cancer Institute, Xuzhou Medical University Xuzhou 221000, Jiangsu, China.
Department of Radiation Oncology, Affiliated Hospital of Xuzhou Medical University Xuzhou 221000, Jiangsu, China.
Am J Cancer Res. 2022 May 15;12(5):2032-2049. eCollection 2022.
To develop an efficient prognostic model based on preoperative magnetic resonance imaging (MRI) radiomics for patients with pancreatic ductal adenocarcinoma (PDAC), the preoperative MRI data of PDAC patients in two independent centers (defined as development cohort and validation cohort, respectively) were collected retrospectively, and the radiomics features of tumors were then extracted. Based on the optimal radiomics features which were significantly related to overall survival (OS) and progression-free survival (PFS), the score of radiomics signature (Rad-score) was calculated, and its predictive efficiency was evaluated according to the area under receiver operator characteristic curve (AUC). Subsequently, the clinical-radiomics nomogram which incorporated the Rad-score and clinical parameters was developed, and its discrimination, consistency and application value were tested by calibration curve, concordance index (C-index) and decision curve analysis (DCA). Moreover, the predictive value of the clinical-radiomics nomogram was compared with traditional prognostic models. A total of 196 eligible PDAC patients were enrolled in this study. The AUC value of Rad-score for OS and PFS in development cohort was 0.724 and 0.781, respectively, and the value of Rad-score was negatively correlated with PDAC's prognosis. Moreover, the developed clinical-radiomics nomogram showed great consistency with the C-index for OS and PFS in development cohort was 0.814 and 0.767, respectively. In addition, the DCA demonstrated that the developed nomogram displayed better clinical predictive usefulness than traditional prognostic models. We concluded that the preoperative MRI-based radiomics signature was significantly related to the poor prognosis of PDAC patients, and the developed clinical-radiomics nomogram showed better predictive ability, it might be used for individualized prognostic assessment of preoperative patients with PDAC.
为基于术前磁共振成像（MRI）影像组学开发一种针对胰腺导管腺癌（PDAC）患者的高效预后模型，我们回顾性收集了两个独立中心（分别定义为开发队列和验证队列）的PDAC患者术前MRI数据，然后提取肿瘤的影像组学特征。基于与总生存期（OS）和无进展生存期（PFS）显著相关的最佳影像组学特征，计算影像组学特征评分（Rad评分），并根据受试者操作特征曲线下面积（AUC）评估其预测效率。随后，构建了纳入Rad评分和临床参数的临床影像组学列线图，并通过校准曲线、一致性指数（C指数）和决策曲线分析（DCA）测试其区分度、一致性和应用价值。此外，将临床影像组学列线图的预测价值与传统预后模型进行了比较。本研究共纳入196例符合条件的PDAC患者。开发队列中Rad评分对OS和PFS的AUC值分别为0.724和0.781，且Rad评分值与PDAC的预后呈负相关。此外，构建的临床影像组学列线图显示出良好的一致性，开发队列中OS和PFS的C指数分别为0.814和0.767。此外，DCA表明，所构建的列线图比传统预后模型具有更好的临床预测效用。我们得出结论，基于术前MRI的影像组学特征与PDAC患者的不良预后显著相关，所构建的临床影像组学列线图显示出更好的预测能力，可用于术前PDAC患者的个体化预后评估。
