上皮性卵巢癌（EOC）是女性第二大致命的妇科肿瘤。 CA125被许多国家推荐作为卵巢癌的主要筛查测试。但也有卵巢癌患者的 CA125 正常。我们希望通过建立基于超声影像组学的精细化模型，更好地识别CA125正常的EOC类型，从而为患者提供精准的医疗治疗。我们纳入了来自两个中心的58例CA125正常的EOC患者，这些患者均经过术前确诊超声和病理学。我们根据每位患者最典型的超声图像中的肿瘤感兴趣区域提取了 1130 个放射组学特征。我们通过套索和逻辑回归选择放射组学和临床特征，分别构建 Rad 评分和临床模型。 ROC曲线判断其测试效果。在组合模型的基础上，我们开发了列线图。组合模型的训练组和测试组的 AUC 分别为 0.93 和 0.83。 Rad 评分和临床模型之间的 AUC 相似，分别为 0.82 和 0.80。通过分析校准曲线，确定列线图与训练队列中的实际观察结果相符。超声放射组学可以区分 CA125 水平正常的 I 型和 II 型 EOC。这项研究是第一个关注 CA125 水平正常的 EOC 病例的研究。占疾病人群 20% 的患者子集可能需要更精细的放射组学模型。© 作者 2024。由牛津大学出版社代表英国放射学研究所出版。版权所有。如需权限，请发送电子邮件至：journals.permissions@oup.com。

Epithelial Ovarian cancer (EOC) is the second most lethal gynecologic tumor in women. CA125 is recommended by many countries as the primary screening test for ovarian cancer. But there are patients with ovarian cancer having normal CA125. We hope to identify the types of EOC with normal CA125 levels better by building a refined model based on the ultrasound radiomics, thus providing precise medical treatment for patients.We included 58 patients with EOC with normal CA125 from two centers, who were confirmed by preoperative ultrasound and pathology. We extracted 1130 radiomics features based on the tumor's region of interest from the most typical ultrasound image of each patient. We selected radiomics and clinical features by lasso and logistic regression to construct Rad-score and clinical models, respectively. ROC curves judged their test efficacy. On the basis of the combined model, we developed a nomogram.AUCs of 0.93 and 0.83 were achieved in both the training and test groups for the combined model. There were similar AUCs between the Rad-score and clinical models of 0.82 and 0.80, respectively. By analyzing the calibration curves, it was determined that the nomogram matched actual observations in the training cohort.Ultrasound Radiomics Can Differentiate Type I and Type II EOC with Normal CA125 Levels.This study is the first to focus on EOC cases with normal level of CA125. The subset of patients constituting 20% of the disease population may require more refined radiomics models.© The Author(s) 2024. Published by Oxford University Press on behalf of the British Institute of Radiology. All rights reserved. For permissions, please email: journals.permissions@oup.com.