Bo Juan, Jia Haodong, Zhang Yu, Fu Baoyue, Jiang Xueyan, Chen Yulan, Shi Bin, Fang Xin, Dong Jiangning
Department of Radiology, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230001, China.
Department of Radiation Oncology, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230001, China.
J Oncol. 2022 Jun 30;2022:3335048. doi: 10.1155/2022/3335048. eCollection 2022.
To investigate the value of apparent diffusion coefficient (ADC) value of endometrial cancer (EC) primary lesion and magnetic resonance imaging (MRI) three-dimensional (3D) radiomics features combined with clinical parameters for preoperative prediction of pelvic lymph node metastasis (PLNM).
A total of 136 patients with EC confirmed by postoperative pathology were retrospectively reviewed and analyzed. Patients were randomly divided into training set ( = 95) and test set ( = 41) at a ratio of 7 : 3. Radiomics features based on TWI, DWI, and contrast-enhanced TWI (CE-TWI) sequence were extracted and screened, and then radiomics score (Rads-score) was calculated. Clinical parameters and ADC value of EC primary lesion were measured and collected, and their correlation with PLNM was analyzed. Receiver operating characteristic (ROC) curve was plotted to assess the diagnostic efficacy of the model. A nomogram for PLNM was created based on the multivariate logistic regression model.
The ADC value of the EC primary lesion showed inverse correlation with PLNM, while CA125 and Rads-score were positively associated with PLNM. A predictive model was proposed based on ADC value, Rads-score, CA125, and MR-reported pelvic lymph node status (PLNS) for PLNM in EC. The area under the curve (AUC) of the model is 0.940; the sensitivity and specificity (87.1% and 90.6%) of the model were significantly higher than that of the MRI morphological signs.
A combination of ADC value, MRI 3D radiomics features of the EC primary lesion, and clinical parameters generated a prediction model for PLNM in EC and had a good diagnostic performance; it was a useful supplement to MR-reported PLNS based on MRI morphological signs.
探讨子宫内膜癌（EC）原发灶的表观扩散系数（ADC）值及磁共振成像（MRI）三维（3D）影像组学特征联合临床参数对盆腔淋巴结转移（PLNM）术前预测的价值。
回顾性分析136例经术后病理确诊的EC患者。患者按7∶3的比例随机分为训练集（n = 95）和测试集（n = 41）。提取并筛选基于TWI、DWI及对比增强TWI（CE-TWI）序列的影像组学特征，然后计算影像组学评分（Rads评分）。测量并收集EC原发灶的临床参数及ADC值，分析其与PLNM的相关性。绘制受试者操作特征（ROC）曲线评估模型的诊断效能。基于多因素逻辑回归模型创建PLNM的列线图。
EC原发灶的ADC值与PLNM呈负相关，而CA125和Rads评分与PLNM呈正相关。提出基于ADC值、Rads评分、CA125及MR报告的盆腔淋巴结状态（PLNS）的EC中PLNM预测模型。该模型的曲线下面积（AUC）为0.940；模型的灵敏度和特异度（87.1%和90.6%）显著高于MRI形态学征象。
EC原发灶的ADC值、MRI 3D影像组学特征及临床参数相结合生成了EC中PLNM的预测模型，且具有良好的诊断性能；它是以MRI形态学征象为基础的MR报告PLNS的有益补充。
