Department of Radiology, Linyi Central Hospital, Linyi, China.
Department of Healthcare, Linyi Central Hospital, Linyi, China.
BMC Cancer. 2020 Jun 22;20(1):579. doi: 10.1186/s12885-020-07053-3.
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.
探索术前计算机断层扫描（CT）的放射组学特征对三阴性乳腺癌（TNBC）的诊断价值，以便更好地治疗乳腺癌患者。
回顾性分析 2016 年 6 月至 2018 年 1 月我院收治的 890 例乳腺癌患者，均经手术及病理检查确诊为肿块型及浸润性乳腺癌，术前均行胸部增强 CT 检查。随机抽取其中 300 例患者进行研究，包括 100 例 TNBC 患者和 200 例非 TNBC（NTNBC）患者。其中 180 例用于发现组，120 例用于验证组。采用免疫组织化学法确定乳腺癌患者的分子亚型。从三维 CT 图像中提取放射组学特征。采用 LASSO 逻辑回归方法筛选图像特征并计算放射组学评分。绘制受试者工作特征（ROC）曲线分析放射组学评分对 TNBC 的诊断价值。
发现 5 个与 TNBC 亚型相关的图像特征（P<0.001）。基于这些图像特征的放射组学特征对 TNBC 有较好的预测价值，发现组的 ROC 曲线下面积（AUC）为 0.881（95%CI：0.781-0.921），验证组为 0.851（95%CI：0.761-0.961）。发现组的敏感度和特异度分别为 0.767 和 0.873，验证组分别为 0.785 和 0.915。
基于术前 CT 的放射组学特征能够区分 TNBC 和 NTBG 患者，为常规胸部增强 CT 增加了附加价值，有助于制定患者的临床治疗策略。
