目的 本研究旨在评估磁共振成像 (MRI) 结果和纹理特征 (TF) 区分子宫内膜癌和子宫癌肉瘤的诊断可行性。方法 这项回顾性研究纳入了 2008 年 1 月至 2021 年 12 月期间手术后经组织病理学诊断为子宫内膜癌 (n = 68) 或子宫癌肉瘤 (n = 34) 的 102 名患者。我们评估了常规 MRI 结果和测量 (cMRFM) 以及 TF T2 加权图像 (T2WI) 和表观扩散系数 (ADC) 图及其组合用于区分子宫内膜癌和子宫癌肉瘤。使用最小绝对收缩和选择算子（LASSO）为每个模型选择LASSO回归系数绝对值最高的三个特征，构建判别模型。采用二元logistic回归分析对疾病模型进行分析，并对cMRFM、T2WI-TF、ADC-TF及其组合模型进行受试者操作特征分析，以比较两种疾病。结果 根据三个选定特征中的每一个特征构建了总共四个模型。对于 cMRFM、T2WI-TF、ADC-TF 以及 cMRFM 和 TF 的组合模型，使用这些特征的判别模型的曲线下面积 (AUC) 分别为 0.772、0.878、0.748 和 0.915。组合模型显示出比其他模型更高的AUC，具有较高的诊断性能（AUC=0.915）。结论 使用 cMRFM 和 TF 的联合模型可能有助于子宫内膜癌和子宫癌肉瘤的鉴别诊断。版权所有 © 2024，Tschihashi 等人。

Aim  This study aimed to evaluate the diagnostic feasibility of magnetic resonance imaging (MRI) findings and texture features (TFs) for differentiating uterine endometrial carcinoma from uterine carcinosarcoma. Methods This retrospective study included 102 patients who were histopathologically diagnosed after surgery with uterine endometrial carcinoma (n=68) or uterine carcinosarcoma (n=34) between January 2008 and December 2021. We assessed conventional MRI findings and measurements (cMRFMs) and TFs on T2-weighted images (T2WI) and apparent diffusion coefficient (ADC) map, as well as their combinations, in differentiating between uterine endometrial carcinoma and uterine carcinosarcoma. The least absolute shrinkage and selection operator (LASSO) was used to select three features with the highest absolute value of the LASSO regression coefficient for each model and construct a discriminative model. Binary logistic regression analysis was used to analyze the disease models and conduct receiver operating characteristic analyses on the cMRFMs, T2WI-TFs, ADC-TFs, and their combined model to compare the two diseases. Results A total of four models were constructed from each of the three selected features. The area under the curve (AUC) of the discriminative model using these features was 0.772, 0.878, 0.748, and 0.915 for the cMRFMs, T2WI-TFs, ADC-TFs, and a combined model of cMRFMs and TFs, respectively. The combined model showed a higher AUC than the other models, with a high diagnostic performance (AUC=0.915). Conclusion A combined model using cMRFMs and TFs might be helpful for the differential diagnosis of uterine endometrial carcinoma and uterine carcinosarcoma.Copyright © 2024, Tsuchihashi et al.