Yan Bi-Cong, Ma Feng-Hua, Li Ying, Fan Yan-Feng, Huang Zhi-Long, Ma Xiao-Liang, Wen Xue-Ting, Qiang Jin-Wei
Department of Diagnostic and Interventional Radiology, Shanghai Jiaotong University Affiliated Sixth People's Hospital 600 Yi Shan Road, Shanghai 200233, China.
Department of Radiology, Jinshan Hospital, Fudan University 1508 Longhang Road, Shanghai 201508, China.
Am J Cancer Res. 2022 Mar 15;12(3):1056-1068. eCollection 2022.
It is difficult to identify eligible candidates for fertility-preserving treatment (FPT) among endometrioid adenocarcinoma (EAC) and atypical hyperplasia (AH) patients. Therefore, new approaches for improving the accuracy of candidate selection are warranted. From December 2014 to January 2020, 236 EAC/AH patients (age <50 and premenopausal) were retrospectively reviewed and randomly divided into the primary group (n=158) and validation group 1 (n=78). From February 2020 to December 2021, 51 EAC/AH patients were prospectively enrolled and formed the validation group 2. From the primary group, 385 features were extracted using pyradiomics from multiparameter magnetic resonance imaging (MRI) (including T2-weighted imaging, diffusion-weighted imaging, apparent diffusion coefficient, and contrast enhancement sequences) and 13 radiomics features were selected using a least absolute shrinkage and selection operator. A clinical model based on clinical information (myometrial invasion on MRI and tumor grade in curettage) and a radiomics nomogram by integrating clinical information with the radiomics features was developed to identify eligible candidates of FPT. For identifying eligible candidates of FPT, the areas under the receiver operating characteristic curve (AUCs) were 0.63 (95% confidence interval [CI]: 0.53-0.73) in the primary group, and 0.62 (95% CI: 0.45-0.78) and 0.69 (95% CI: 0.53-0.86) in validation groups 1 and 2, respectively, for the clinical model; were 0.86 (95% CI: 0.80-0.93) in the primary group, and 0.82 (95% CI: 0.71-0.93) and 0.94 (95% CI: 0.87-1.0) in validation groups 1 and 2, respectively, for the radiomics nomogram. With the help of radiomics nomogram, the treatment decision determined from the clinical model was revised in 45 EAC/AH patients. The net reclassification index (NRI) was 0.80 and integrated discrimination improvement (IDI) was 0.17, indicating that the nomogram could improve the accuracy in identifying eligible EAC/AH candidates for FPT.
在内膜样腺癌（EAC）和非典型增生（AH）患者中，很难识别出适合保留生育功能治疗（FPT）的合格候选人。因此，有必要采用新方法提高候选人选择的准确性。2014年12月至2020年1月，对236例EAC/AH患者（年龄<50岁且处于绝经前）进行回顾性分析，并随机分为初级组（n = 158）和验证组1（n = 78）。2020年2月至2021年12月，前瞻性纳入51例EAC/AH患者，组成验证组2。从初级组中，利用多参数磁共振成像（MRI）（包括T2加权成像、扩散加权成像、表观扩散系数和对比增强序列）的影像组学提取385个特征，并使用最小绝对收缩和选择算子选择13个影像组学特征。基于临床信息（MRI上的肌层浸润和刮宫术中的肿瘤分级）建立临床模型，并将临床信息与影像组学特征相结合构建影像组学列线图，以识别FPT的合格候选人。对于识别FPT的合格候选人，临床模型在初级组中的受试者操作特征曲线下面积（AUC）为0.63（95%置信区间[CI]：0.53 - 0.73），在验证组1和验证组2中分别为0.62（95% CI：0.45 - 0.78）和0.69（95% CI：0.53 - 0.86）；影像组学列线图在初级组中的AUC为0.86（95% CI：0.80 - 0.93），在验证组1和验证组2中分别为0.82（95% CI：0.71 - 0.93）和0.94（95% CI：0.87 - 1.0）。借助影像组学列线图，45例EAC/AH患者根据临床模型做出的治疗决策得到了修订。净重新分类指数（NRI）为0.80，综合判别改善（IDI）为0.17，表明该列线图可提高识别适合FPT的EAC/AH合格候选人的准确性。
