瘤内和瘤周放射组学用于预测乳腺癌症对比增强乳房X光检查中的可疑HER2状态
Intra- and peritumoral radiomics for predicting equivocal HER2 status of breast cancer on contrast-enhanced mammography.
摘要(中文译文)
人表皮生长因子受体2（HER2）状态的识别对乳腺癌患者的治疗和预后具有重要意义。本研究旨在利用对比增强乳腺摄影（CEM）的瘤内和瘤周影像组学特征评估乳腺癌HER2状态不确定（IHC 2+）的情况。研究共纳入131例HER2状态不确定（IHC 2+）的乳腺癌患者，分为训练队列（n=84）、内部测试队列（n=22）和前瞻性测试队列（n=25）。从CEM图像的瘤内和瘤周区域提取影像组学特征，并采用低方差和最小绝对收缩与选择算子回归（LASSO）进行特征筛选。基于不同的瘤内和瘤周区域建立了五种影像组学标签。通过逻辑回归分析，利用筛选出的标签和临床因素构建列线图。将其预测性能与影像组学模型和临床模型进行比较。采用受试者工作特征曲线下面积（AUC）、灵敏度、特异度、准确度、校准曲线和决策曲线分析（DCA）评估模型的预测性能。瘤内标签、5mm瘤周标签和肿瘤直径被用于建立列线图。与影像组学模型和临床模型相比，列线图取得了最优的预测性能，内部测试队列的AUC为0.893，前瞻性测试队列的AUC为0.840。校准曲线和DCA显示列线图具有良好的预测性能。该列线图整合了CEM的瘤内和瘤周影像组学标签及临床风险变量，有望在术前预测乳腺癌HER2状态不确定（IHC 2+）。
Abstract
Identification of Human epidermal growth factor receptor 2 (HER2) status is significant for the treatment and prognosis of breast cancer patients. The study aimed to evaluate the equivocal HER2 (IHC 2+) status of breast cancer using intra- and peritumoral radiomics features of contrast-enhanced mammography (CEM). A total of 131 breast cancer patients with equivocal HER2 (IHC 2+) status of breast cancer were enrolled in the study and divided into training (n=84), internal test (n=22) and prospective test (n=25) cohorts. Radiomics features were extracted from intratumoral and peritumoral regions on CEM and were selected using low variance and least absolute shrinkage and selection operator regression (LASSO). Five radiomics signatures were established based on different intratumoral and peritumoral regions. The nomogram was constructed using the selected signatures and clinical factors by logistic regression analysis. Its predictive performance was compared with the radiomics model and the clinical model. The area under the receiver operator characteristic curve (AUC), sensitivity, specificity, accuracy, the calibration curve, and decision curve analysis (DCA) were used to evaluate predictive performance of the models. The intratumoral signature, 5mm-peritumoral signature, and tumor diameter were used to establish nomogram. Compared to the radiomics model and the clinical model, the nomogram achieved optimal predictive performance, with an AUC of 0.893 in the internal test cohort and an AUC of 0.840 in the prospective test cohort. The calibration curves and DCA showed favorable predictive performance of the nomogram. The nomogram incorporated the intratumoral and peritumoral radiomics signatures of CEM and clinical risk variables has the potential to predict equivocal HER2 (IHC 2+) status of breast cancer preoperatively.
如何引用
AMA
Cong Xu, Juan Qiu, Shijie Zhang, Yuqian Chen, Xiaodong Wang, Haicheng Zhang, et al. Intra- and peritumoral radiomics for predicting equivocal HER2 status of breast cancer on contrast-enhanced mammography.. Frontiers in oncology. 2026; doi:10.3389/fonc.2026.1807530.
APA
Cong Xu, Juan Qiu, Shijie Zhang, Yuqian Chen, Xiaodong Wang, Haicheng Zhang, et al (2026). Intra- and peritumoral radiomics for predicting equivocal HER2 status of breast cancer on contrast-enhanced mammography.. Frontiers in oncology. https://doi.org/10.3389/fonc.2026.1807530
GB/T 7714
Cong Xu, Juan Qiu, Shijie Zhang, Yuqian Chen, Xiaodong Wang, Haicheng Zhang, et al. Intra- and peritumoral radiomics for predicting equivocal HER2 status of breast cancer on contrast-enhanced mammography.[J]. Frontiers in oncology, 2026 doi:10.3389/fonc.2026.1807530.
在 PubMed增强版 阅读全文
翻译全文 · AI 文献问答 · PDF 原文下载 · 引用导出