DCE-MRI影像特征对乳腺癌激素受体、HER-2及三阴性乳腺癌的预测价值  

Predictive value of DCE-MRI features of breast cancer on hormone receptor,HER-2 and triple negative breast cancer

作　　者：代婷 苏桐 王锐 杨鸿羽 赵青 吕发金[1] 欧阳祖彬[1] DAI Ting;SU Tong;WANG Rui;YANG Hongyu;ZHAO Qing;LÜFajin;OUYANG Zubin(Department of Radiology,the First Affiliated Hospital of Chongqing Medical University,Chongqing 400016,China;Department of Radiology,Changshou District People's Hospital,Chongqing 401220,China)

机构地区：[1]重庆医科大学附属第一医院放射科,重庆400016 [2]重庆市长寿区人民医院放射科,重庆401220

出　　处：《磁共振成像》2023年第4期57-67,共11页Chinese Journal of Magnetic Resonance Imaging

基　　金：国家重点研发计划(编号:2020YFA0714002);重庆市卫生计生委医学科研项目(编号:2015MSXM011)。

摘　　要：目的 探讨动态对比增强MRI(dynamic contrast-enhanced MRI, DCE-MRI)图像特征联合定量参数对乳腺癌激素受体、人表皮生长因子受体2 (human epidermal growth factor receptor-2, HER-2)及三阴性乳腺癌(triple-negative breast cancer, TNBC)的预测价值。材料与方法 回顾性分析316例行乳腺MRI检查的乳腺癌患者的临床资料、DCE-MRI图像及定量参数,其中242例为训练组,74例为验证组。根据激素受体表达情况分为激素受体阳性组和阴性组;按照HER-2表达情况分为HER-2阳性组和HER-2阴性组;根据激素受体及HER-2表达状态分为TNBC和非三阴性乳腺癌组(non-triple-negative breast cancer, NTNBC)。比较训练组中不同类型乳腺癌MRI图像特征及定量参数的差异,运用logistic回归联合部分影像征象及定量参数预测激素受体阳性、HER-2阳性与TNBC,构建出相应的列线图,利用验证组进行验证,采用受试者工作特征(receiver operator characteristic, ROC)曲线、校正曲线、决策曲线分析(decision curve analysis, DCA)评估预测模型效能。结果 训练组中病灶大小、形状、毛刺、内部强化特征(internal enhancement characteristics, IEC)、非肿块样强化(non-mass enhancement, NME)、子灶、周围血管增多、腋窝淋巴结肿大、乳头改变等乳腺DCE-MRI图像特征在乳腺癌不同免疫组化结果及分子亚型组间存在显著差异(P均<0.05),定量参数中血管外细胞外间隙容积比(volume fraction of extravascular extra vascular space, Ve)则是激素受体阳性组大于阴性组(P<0.001),而TNBC的Ve小于NTNBC (P<0.001)。毛刺(P<0.001)、IEC(P=0.041)、NME(P=0.006)以及腋窝淋巴结肿大(P=0.029)可以鉴别激素受体阳性和阴性乳腺癌。训练组的曲线下面积(area under the curve, AUC)为0.746(95%CI:0.681~0.811),敏感度、特异度及准确度分别为82.8%、52.9%及72.3%。验证组的AUC为0.829(95%CI:0.730~0.926),敏感度、特异度及准确度分别为78.7%、74.1%及77.0%。肿块形状(Objective:To explore the predictive value of dynamic contrast-enhanced MRI(DCE-MRI)image features combined with quantitative parameters in breast cancer hormone receptor,human epidermal growth factor receptor-2(HER-2)and triple negative breast cancer(TNBC).Materials and Methods:The clinical data,DCE-MRI images,and quantitative parameters of 316 patients with breast cancer who underwent breast MRI were collected retrospectively,242 patients in the training group and 74 patients in the validation group.According to the expression of hormone receptor,they were divided into two groups:hormone receptor positive group and negative group.HER-2 positive group and HER-2 negative group were determined by HER-2 expression.TNBC group and non-triple negative breast cancer(NTNBC)group devided according to hormone receptor and HER-2 expression status.In training group,the differences of image features and quantitative parameters among different immunohistochemical results and molecular types of breast cancer were compared.Some imaging features and quantitative parameters selected by logistic regression were used to predict hormone receptor positive,HER-2 positive and TNBC,and then the nomogram models were constructed.The verification group was used for verification.Receiver operator characteristic(ROC)curve,calibration curve and decision curve analysis(DCA)were used to evaluate the performance of the prediction model.Results:In the training group,DCE-MRI image features such as lesion size,shape,spiculated margin,internal enhancement characteristics(IEC),non-mass enhancement(NME),sub-focus,increased peripheral vascularity,axillary lymphadenopathy and nipple change were significantly different among the immunohistochemical results and molecular subtypes of breast cancer(all P<0.05).The quantitative parameter volume fraction of extravascular extra vascular space(Ve)of the hormone receptor positive group was larger than that of hormone receptor negative group(P<0.001),while Ve of the TNBC group was smaller than that of NTNBC group(

关 键 词：乳腺癌 三阴性乳腺癌 动态对比增强 磁共振成像 定量参数 激素受体 人类表皮生长因子受体2 预测模型 

分 类 号：R445.2[医药卫生—影像医学与核医学] R737.9[医药卫生—诊断学]