摘要
目的:探讨基于钼靶、MRI的多模态影像组学预测肿块型乳腺癌术前淋巴结转移的价值。方法:收集采用钼靶及MRI检查的111例(114个病灶)肿块型乳腺癌病人的资料。按照8∶2的比例随机将所有病例分为训练组与验证组。对所有图像进行勾画并提取组学特征,利用最小最大值归一化、Select K Best及最小绝对收缩与选择算子回归筛选出有效特征并建立钼靶、MRI、钼靶联合MRI的影像组学预测模型。利用受试者工作特征曲线下面积(AUC)评估模型的效能。结果:钼靶、MRI、钼靶联合MRI的影像组学模型在训练组及验证组的AUC值分别为0.76、0.82、0.89及0.74、0.81、0.88。钼靶联合MRI影像组学模型AUC值最大,效能最高。腋窝淋巴结阳性组病灶大小明显大于腋窝淋巴结阴性组(P<0.01)。结论:钼靶联合MRI的多模态影像组学模型可以较好地预测肿块型乳腺癌术前淋巴结转移。
Objective:To explore the value of multi-modality radiomics based on mammography and MRI in predicting the preoperative lymph node metastasis in mass type breast cancer.Methods:The clinical data of 111 mass type breast cancer patients(114 lesions)detected by mammography and MRI were collected.All patients were randomly divided into the training group and validation group according to the ratio of 8∶2.The radiomics features were segmented and extracted from all images.The minimum and maximum normalization,Select K Best and least absolute shrinkage and selection operator were used to obtain the optimal features to establish the mammography,MRI and mammography combined with MRI prediction model.The efficiency of model was evaluated using the area under receiver operating characteristic(ROC)curve(AUC).Results:The AUC values of the mammography,MRI and mammography combined with MRI model in the training group and validation group were(0.76,0.82 and 0.89,respectively)and(0.74,0.81 and 0.88,respectively).The AUC value and efficiency of mammography combined with MRI model were the highest.The lesion size in positive axillary lymph node group was greater than that in negative axillary lymph node group(P<0.01).Conclusions:The multi-modality radiomics model based on mammography combined with MRI can better predict the preoperative lymph node metastasis of mass type breast cancer.
作者
王祥芝
张书海
徐敏
汤晓敏
刘浩
谢宗玉
WANG Xiang-zhi;ZHANG Shu-hai;XU Min;TANG Xiao-min;LIU Hao;XIE Zong-yu(School of Graduate,Bengbu Medical College,Bengbu Anhui 233030;Department of Radiology,The First Affiliated Hospital of Bengbu Medical College,Bengbu Anhui 233004;Beijing Yizhun Intelligent Technology Co.Ltd,Beijing 100089,China)
出处
《蚌埠医学院学报》
CAS
2021年第5期652-656,共5页
Journal of Bengbu Medical College
基金
蚌埠医学院转化医学重点专项(BYTM2019043)
安徽省高校自然科学研究重点项目(KJ2019A0402)。
关键词
乳腺肿瘤
多模态
影像组学
淋巴结转移
breast neoplasms
multi-modality
radiomics
lymph node metastasis