基于DCE-MRI影像组学对乳腺癌腋窝淋巴结转移的预测价值  

Predictive value of axillary lymph node metastasis in breast cancer based on DCE-MRI radiomics

作　　者：宋亚博 李娇娇[2] 黄紫莹 焦光丽 石子馨 李晓东[2] SONG Yabo;LI Jiaojiao;HUANG Ziying;JIAO Guangli;SHI Zixin;LI Xiaodong(Department of Postgraduate,Hebei North University,Zhangjiakou 075000,China;Department of Medical Imaging,The First Affiliated Hospital of Hebei North University,Zhangjiakou 075000,China)

机构地区：[1]河北北方学院研究生院,河北张家口075000 [2]河北北方学院附属第一医院医学影像部,河北张家口075000

出　　处：《医学影像学杂志》2025年第3期60-63,73,共5页Journal of Medical Imaging

基　　金：河北省自然科学基金项目(编号:H2023405031);河北省医学科学研究课题计划项目(编号:20210136)。

摘　　要：目的 探究乳腺癌肿瘤内部和包含肿瘤周围5 mm区域的影像组学特征预测患者腋窝淋巴结(axillary lymph node,ALN)转移的价值。方法 选取术前进行磁共振检查的乳腺癌患者198例,按照7∶3的比例随机分为训练集(n=138)和验证集(n=60)。对动态对比增强磁共振成像(dynamic contrast-enhanced magnetic resonance imaging,DCE-MRI)的第二期图像勾画三维容积感兴趣区(volume of interest,VOI),并在VOI基础上外扩5 mm瘤周范围形成VOI+5 mm,采用最小绝对值收缩和选择算子(least absolute shrinkage and selection operator,LASSO)算法筛选特征,之后通过逻辑回归分类器(logistics regression,LR)方法分别建立瘤内模型、瘤内联合瘤周模型。采用受试者工作特征曲线下面积(area under the curve,AUC)评估模型的预测效能。通过临床决策曲线(decision curve analysis,DCA)评估模型的临床应用价值。结果 在训练集和验证集中,瘤内联合瘤周模型的AUC(0.861、0.802)均高于瘤内模型(0.745、0.741)。DCA显示当阈值概率分别在31.0%~72.0%、25.0%~78.0%时,瘤内模型和瘤内联合瘤周模型产生了净获益。结论 基于LR分类器,通过DCE-MRI图像影像组学特征建立的影像组学模型对评估乳腺癌ALN转移有一定的预测价值,瘤内联合瘤周影像组学特征对提升预测效能有较大潜能。Objective To investigate the value of radiomics features within breast cancer tumors and containing a 5-mm area around the tumor to predict axillary lymph node(ALN)metastasis in patients.Methods A total of 198 breast cancer patients who underwent preoperative magnetic resonance examination in the First Affiliated Hospital of Hebei North College were retro-spectively collected and randomly divided into a training set(n=138)and a validation set(n=60)according to the ratio of 7:3.The three-dimensional volume of interest(VOI)was sketched on the second-phase images of dynamic contrast-enhanced mag-netic resonance imaging(DCE-MRI),and the peri-tumor area was expanded by 5 mm to form VOI+5 mm.The VOI was ex-panded by 5 mm to form VOI+,and the features were screened by the least absolute shrinkage and selection operator(LASSO)algorithm,after which the intratumor model and the combined intratumor and peritumor model were established by the logistic re-gression(LR)method,respectively.The predictive efficacy of the models was evaluated by plotting the receiver operating char-acteristic(ROC)and calculating the area under the curve(AUC).Decision Curve Analysis(DCA)was used to assess the clinical application value of the model.Results In both the training and validation sets,the AUC values of the intra-tumor combined peri-tumor model(0.861,0.802)were higher than those of the intra-tumor model(0.745,0.741).DCA showed that the intra-tumor model and intra-tumor combined peri-tumor model yielded net when the threshold probabilities were in the ranges of 31.0%to 72.0%and 25.0%to 78.0%,respectively.Conclusion The MRI radiomics model based on the LR classifier and established by DCE-MRI image radiomics features has a certain predictive value for assessing axillary lymph node metastasis in breast cancer,and the intra-tumor combined peri-tumor radiomics features have a greater potential to enhance the predictive efficacy.

关 键 词：影像组学 乳腺癌 磁共振成像 腋窝淋巴结 瘤周微环境 

分 类 号：R737.9[医药卫生—肿瘤] R445.2[医药卫生—临床医学]