乳腺癌腋窝淋巴结转移负荷的超声组学研究  

Ultrasound omics study of axillary lymph node metastatic burden in breast cancer

作　　者：赵高芳 陈京 王春梅 吴娟 Zhao Gaofang;Chen Jing;Wang Chunmei;Wu Juan(Department of Medical Ultrasound,Mianyang 404 Hospital,Sichuan Mianyang 621000;Department of Radiology,Chongqing Southeast Hospital,Chongqing 401366;Department of Medical Imaging,Qingbaijiang District People's Hospital,Sichuan Chengdu 610300,China)

机构地区：[1]四川绵阳四〇四医院医学超声科,四川绵阳621000 [2]重庆市东南医院放射科,重庆南岸401366 [3]成都市青白江区人民医院医学影像科,四川成都610300

出　　处：《中华介入放射学电子杂志》2025年第1期54-61,共8页Chinese Journal of Interventional Radiology:electronic edition

摘　　要：目的研究乳腺癌腋窝淋巴结转移负荷的超声组学。方法选取2019年11月至2023年1月四川绵阳四〇四医院接受手术治疗的乳腺癌患者100例。依据术后病理淋巴结转移情况分为高淋巴结转移负荷(HNB)组(n=43)和低淋巴结转移负荷(LNB)组(n=57)。分析2组患者的一般临床资料、常规超声特征及影像组学特征。提取影像组学特征,使用组内相关系数(ICC)进行一致性分析。采用mRMR和LASSO回归算法,筛选与淋巴结转移负荷相关的影像组学特征。采用单因素Logistic回归分析选取临床因素及常规超声特征。构建常规超声评分模型、影像组学评分模型和联合预测模型并对模型进行评价。结果从超声图像中最终筛选出10个非0的影像组学特征。影像组学评分(Rad-score)、常规超声评分及联合得分(Combine-score)在LNB组和HNB组间差异均有统计学意义(P<0.05)。常规超声模型分别与影像组学模型、联合预测模型的受试者工作特征曲线下面积(AUC)比较差异有统计学意义(P<0.05),而影像组学模型与联合预测模型的AUC比较差异无统计学意义(P>0.05)。Hosmer-Lemeshow检验表明各模型拟合均较好(P>0.05)。结论联合预测模型的鉴别能力优于常规超声模型和影像组学模型,提示影像组学特征联合常规超声特征用于预测乳腺癌腋窝高淋巴结转移负荷具有一定可行性。Objective To investigate the ultrasound radiomics of axillary lymph node metastasis burden in breast cancer.Methods A total of 100 patients with breast cancer who received surgical treatment in Mianyang 404 hospital,Sichuan Province from November 2019 to January 2023 were selected.According to the postoperative pathological status of lymph node metastasis,the patients were divided into high lymph node metastasis burden(HNB)group(n=43)and low lymph node metastasis burden(LNB)group(n=57).The general clinical data,conventional ultrasound features and image omics features of the 2 groups were analyzed.The image omics features were extracted and the intra-group correlation coefficient(ICC)was used for consistency analysis.The mRMR and LASSO regression algorithms were used to screen the image omics features related to lymph node metastasis burden.Univariate Logistic regression analysis was used to select clinical factors and routine ultrasound features.The conventional ultrasound scoring model,imaging omics scoring model and joint prediction model were constructed and evaluated.Results Finally,10 non-zero image omics features were screened out from ultrasonic images.There were significant differences in Radscore,conventional ultrasound score and combination-score between the LNB group and HNB group(P<0.05).There were statistically significant differences in the area under the receiver working characteristic curve(AUC)between conventional ultrasound model and imaging omics model and combined prediction model respectively(P<0.05),while there was no statistically significant difference in the AUC between imaging omics model and combined prediction model(P>0.05).The Hosmer-Lemeshow test showed that all models fit well(P>0.05).Conclusion The differential ability of the combined prediction model is better than that of conventional ultrasound model and imaging omics mode,suggesting that it is feasible for the combined imaging omics features and conventional ultrasound features to predict high axillary lymph node metastatic bu

关 键 词：乳腺癌 腋窝淋巴结 转移负荷 超声成像 影像组学 

分 类 号：R737.9[医药卫生—肿瘤]