Wang Xianhong, Deng Cheng, Kong Ruize, Gong Zhimei, Dai Hongying, Song Yang, Wu Yunzhu, Bi Guoli, Ai Conghui, Bi Qiu
The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan 650500, China (X.W., R.K., Z.G., H.D., G.B., Q.B.); Department of MRI, the First People's Hospital of Yunnan Province, Kunming, Yunnan 650032, China (X.W., Z.G., H.D., G.B., Q.B).
Department of Radiology, the Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650101, China (C.D.).
Acad Radiol. 2025 Mar;32(3):1476-1487. doi: 10.1016/j.acra.2024.09.039. Epub 2024 Oct 5.
To evaluate the validity of multiparametric MRI-based intratumoral and peritumoral habitat imaging for predicting cervical stromal invasion (CSI) in patients with early-stage endometrial carcinoma (EC) and to compare the performance of structural and functional habitats.
The preoperative MRI and clinical data of 680 patients with early-stage EC from three centers were retrospectively analyzed. Based on cohort-level, gaussian mixture model (GMM) algorithm was used for habitat clustering of MRI images. Structural habitats were clustered using T2-weighted imaging (T2WI) and contrast-enhanced T1-weighted imaging (CE-T1WI), and functional habitats were clustered using apparent diffusion coefficient (ADC) mapping and CE-T1WI. Habitat parameters were extracted from four volumes of interest (VOIs): intratumoral regions (ROI), peritumoral loops of 3 mm dilation (L3), intratumoral regions + peritumoral loops of 3 mm dilation (R3), and peritumoral loops of 3 mm dilation + peritumoral loops of 3 mm erosion (DE3). Clinical-habitat models were constructed by combining clinical independent predictors and optimal habitat models. The model performance was evaluated by the area under the curve (AUC).
Deep myometrial invasion (DMI) was an independent predictor. L3 models showed the best performance for both structural and functional habitats, and the L3 functional habitat model had the highest average AUC (0.807) in external test groups, and the average AUC increased to 0.815 when combing with the clinical independent predictor.
Multiparametric MRI-based intratumoral and peritumoral habitat imaging provides a noninvasive approach to predict CSI in EC patients. The combination of the clinical predictor with the L3 functional habitat model improved predictive performance.
评估基于多参数磁共振成像（MRI）的肿瘤内及瘤周特征成像预测早期子宫内膜癌（EC）患者宫颈间质浸润（CSI）的有效性，并比较结构和功能特征的表现。
回顾性分析来自三个中心的680例早期EC患者的术前MRI和临床资料。基于队列水平，采用高斯混合模型（GMM）算法对MRI图像进行特征聚类。使用T2加权成像（T2WI）和对比增强T1加权成像（CE-T1WI）进行结构特征聚类，使用表观扩散系数（ADC）图和CE-T1WI进行功能特征聚类。从四个感兴趣体积（VOI）中提取特征参数：肿瘤内区域（ROI）、3mm扩张的瘤周环（L3）、肿瘤内区域+3mm扩张的瘤周环（R3）以及3mm扩张的瘤周环+3mm侵蚀的瘤周环（DE3）。通过结合临床独立预测因素和最佳特征模型构建临床-特征模型。通过曲线下面积（AUC）评估模型性能。
肌层深部浸润（DMI）是独立预测因素。L3模型在结构和功能特征方面均表现最佳，L3功能特征模型在外部测试组中的平均AUC最高（0.807），与临床独立预测因素结合时平均AUC增至0.815。
基于多参数MRI的肿瘤内及瘤周特征成像为预测EC患者的CSI提供了一种非侵入性方法。临床预测因素与L3功能特征模型的结合提高了预测性能。
