Background: Radiomics is changing clinical practice by providing quantitative information from images to improve diagnosis, prognosis, and treatment planning. This study aims to investigate a radiomics model developed from contrast-enhanced mammography (CEM) images to predict disease-free survival (DFS) and overall survival (OS) in breast cancer (BC) patients. Methods: From January 2013 to December 2015, all consecutive BC patients who underwent CEM before biopsy at a referral center were enrolled. Clinical data included histological results, receptor profiles, and follow-up (DFS and OS). A region of interest (ROI) of the enhancing lesion was selected from recombined CEM images by experienced radiologists, and radiomic features were extracted. A Cox-LASSO model assigned coefficients to the features, generating patient radiomic scores (RSs), which were dichotomized for graphical representation. Model performance was assessed using the C index. Results: The study included 126 BC patients with predominantly “mass”-type lesions (95%) and a median follow-up of 6.88 years (IQR 3.10–8.15). The median age of the patients at the time of examination was 49.2 years (IQR: [42.33–56.98]). Radiomic and clinical–radiomic models showed significant associations between RS, DFS, and OS, with patients with RS below the median showing a better prognosis (p< 0.001). Bootstrap testing confirmed a good model fit for OS prediction, with median C-index values of 0.82 for the clinical model and 0.84 for the clinical–radiomic model. Conclusions: Radiomic analysis of CEM images may predict DFS and OS in BC patients, offering additional prognostic value beyond clinical models alone.
背景：影像组学通过从图像中提取定量信息来改善诊断、预后和治疗规划，正在改变临床实践。本研究旨在探讨基于对比增强乳腺X线摄影（CEM）图像构建的影像组学模型，用于预测乳腺癌患者的无病生存期（DFS）和总生存期（OS）。方法：纳入2013年1月至2015年12月期间在某转诊中心活检前接受CEM检查的连续乳腺癌患者。临床数据包括组织学结果、受体谱及随访信息（DFS和OS）。由经验丰富的放射科医师从重组CEM图像中选取增强病灶的感兴趣区域（ROI），并提取影像组学特征。通过Cox-LASSO模型为特征分配系数，生成患者影像组学评分（RS），并将其二分类以进行图形展示。采用C指数评估模型性能。结果：研究共纳入126例乳腺癌患者，其中95%为"肿块"型病变，中位随访时间为6.88年（IQR 3.10-8.15）。患者检查时的中位年龄为49.2岁（IQR：[42.33-56.98]）。影像组学模型及临床-影像组学联合模型均显示RS与DFS、OS存在显著关联，RS低于中位值的患者预后更佳（p<0.001）。Bootstrap检验证实模型对OS预测具有良好拟合度，临床模型和临床-影像组学联合模型的中位C指数值分别为0.82和0.84。结论：CEM图像的影像组学分析可预测乳腺癌患者的DFS和OS，为单纯临床模型提供了额外的预后价值。
肿瘤(癌症)患者之家