Department of Gynecology, Second Hospital of Lanzhou University, Lanzhou, Gansu 730000, China.
Department of Radiology, Second Hospital of Lanzhou University, Lanzhou, Gansu 730000, China.
Clin Radiol. 2024 Oct;79(10):e1196-e1204. doi: 10.1016/j.crad.2024.05.014. Epub 2024 May 23.
Ki-67 is a marker of cell proliferation and is increasingly being used as a primary outcome measure in preoperative window studies of endometrial cancer (EC). This study explored the feasibility of using apparent diffusion coefficient (ADC) values in noninvasive prediction of Ki-67 expression levels in EC patients before surgery, and constructs a nomogram by combining clinical data.
This study retrospectively analyzed 280 EC patients who underwent preoperative magnetic resonance imaging (MRI) diffusion-weighted imaging (DWI) in our hospital from January 2017 to February 2023. Evaluate the potential nonlinear relationship between ADC values and Ki-67 expression using the nomogram. The included patients were randomized into a training set (n = 186) and a validation set (n = 84). Using a combination of logistic regression and LASSO regression results, from which the four best predictors were identified for the construction of the nomogram. The accuracy and clinical applicability of the nomogram were assessed using the receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).
The results of this study showed a nonlinear correlation between ADCmin and Ki-67 expression (nonlinear P = 0.019), and the nonlinear correlation between ADCmean and Ki-67 expression (nonlinear P = 0.019). In addition, this study constructed the nomogram by incorporating ADCmax, International Federation of Gynecology and Obstetrics (FIGO), and chemotherapy. The area under the curve (AUC) values of the ROC for nomogram, ADCmax, FIGO, chemotherapy and grade in the training set were 0.783, 0.718, 0.579, 0.636, and 0.654, respectively. In the validation set, the AUC values for nomogram, ADCmax, FIGO, chemotherapy, and grade were 0.820, 0.746, 0.558, 0.542, and 0.738, respectively. In addition, the calibration curves and the DCA curves suggested a better predictive efficacy of the model.
A nomogram prediction model constructed on the basis of ADCmax values combined with clinical data can be used as an effective method to noninvasively assess Ki-67 expression in EC patients before surgery.
Ki-67 是细胞增殖的标志物，越来越多地被用作子宫内膜癌 (EC) 术前窗口期研究的主要结局指标。本研究探讨了在术前使用表观扩散系数 (ADC) 值无创预测 EC 患者 Ki-67 表达水平的可行性，并通过结合临床数据构建了一个列线图。
本研究回顾性分析了 2017 年 1 月至 2023 年 2 月期间在我院接受术前磁共振成像 (MRI) 扩散加权成像 (DWI) 的 280 例 EC 患者。使用列线图评估 ADC 值与 Ki-67 表达之间的潜在非线性关系。将纳入的患者随机分为训练集 (n = 186) 和验证集 (n = 84)。使用逻辑回归和 LASSO 回归结果的组合，确定了构建列线图的四个最佳预测因子。使用受试者工作特征曲线 (ROC)、校准曲线和决策曲线分析 (DCA) 评估列线图的准确性和临床适用性。
本研究结果表明，ADCmin 与 Ki-67 表达之间存在非线性关系 (非线性 P = 0.019)，ADCmean 与 Ki-67 表达之间也存在非线性关系 (非线性 P = 0.019)。此外，本研究通过纳入 ADCmax、国际妇产科联合会 (FIGO) 和化疗构建了列线图。在训练集中，列线图、ADCmax、FIGO、化疗和分级的 ROC 曲线下面积 (AUC) 值分别为 0.783、0.718、0.579、0.636 和 0.654。在验证集中，列线图、ADCmax、FIGO、化疗和分级的 AUC 值分别为 0.820、0.746、0.558、0.542 和 0.738。此外，校准曲线和 DCA 曲线表明该模型具有更好的预测效果。
基于 ADCmax 值结合临床数据构建的列线图预测模型可作为一种有效的方法，无创评估 EC 患者术前 Ki-67 表达水平。
