To explore the diagnostic value of radiomics features of preoperative computed tomography (CT) for triple negative breast cancer (TNBC) for better treatment of patients with breast cancer. A total of 890 patients with breast cancer admitted to our hospital from June 2016 to January 2018 were analyzed. They were diagnosed by surgery and pathology to have mass and invasive breast cancer and had contrast-enhanced chest CT examination before operation. 300 patients were randomly selected for the study, including 100 TNBC and 200 non-TNBC (NTNBC) patients. Among them 180 were used in discovery group and 120 were used in validation group. The molecular subtypes of breast cancer in the patients were determined immunohistochemistrially. Radiomics features were extracted from three dimensional CT-images. The LASSO logistic method was used to select image features and calculate radiomics scores. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic value of radiomics scores for TNBC. Five image features were found to be related to TNBC subtype (P < 0.001). These image features based-radiomic signatures had good predictive values for TNBC with the areas under ROC curve (AUC) of 0.881 (95% CI: 0.781–0.921) in the discovery group and 0.851 (95% CI: 0.761–0.961) in the validation group, respectively. The sensitivities and specificities were 0.767, and 0.873 in the discovery group and 0.785 and 0.915 in the validation group. Radiomic signature based on preoperative CT is capable of distinguishing patients with TNBC and NTNBC. It adds additional value for conventional chest contrast-enhanced CT and helps plan the strategy for clinical treatment of the patients.

中文翻译：

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基于从术前对比增强胸部计算机断层扫描中提取的放射学特征对三阴性乳腺癌进行诊断。

探讨术前计算机断层扫描（CT）的放射学特征对三阴性乳腺癌（TNBC）的诊断价值，以更好地治疗乳腺癌患者。分析了2016年6月至2018年1月我院收治的890例乳腺癌患者。他们通过手术和病理学诊断出患有弥漫性和浸润性乳腺癌，并在手术前进行了增强对比的胸部CT检查。随机选择300例患者进行研究，其中包括100例TNBC和200例非TNBC（NTNBC）患者。其中，发现组使用了180个，验证组使用了120个。通过免疫组织化学方法确定患者乳腺癌的分子亚型。放射学特征是从三维CT图像中提取的。LASSO logistic方法用于选择图像特征并计算放射学分数。进行受试者工作特征（ROC）曲线分析以评估TNBC的放射性组评分的诊断价值。发现五个图像特征与TNBC亚型有关（P <0.001）。这些基于图像特征的放射性标记对TNBC具有良好的预测价值，发现组的ROC曲线下面积（AUC）为0.881（95％CI：0.781–0.921），而发现组的ROC曲线下面积为0.851（95％CI：0.761–0.961）。验证组。发现组的敏感性和特异性为0.767和0.873，验证组的敏感性和特异性为0.785和0.915。基于术前CT的放射学特征能够区分TNBC和NTNBC患者。