乳腺X线影像组学标签在预测乳腺癌HER2表达中的价值

目的:探讨乳腺X线摄影影像组学标签在预测乳腺癌HER2表达中的价值.方法:回顾性分析2018年1月-2020年10月在苏州大学附属第一医院及苏州市立医院经病理证实为乳腺癌患者的临床及X线资料.共入组222例女性患者,平均年龄(53.70±14.46)岁,其中HER2阳性患者59例,阴性患者163例,苏州大学附属第一医院...

The value of mammography based radiomics signature for preoperative prediction of HER2 expression in breast carcinoma

Objective:To explore the value of mammography-based radiomics signature for preoperative prediction of HER2 expression in breast carcinoma.Methods:The clinical and X-ray data of patients with breast cancer confirmed by pathology in the first affiliated hospital of soochow university and Suzhou municipal hospital from January 2018 to October 2020 were retrospectively analyzed.A total of 222 female patients with an average age of 52.62±13.15 years old were enrolled,including 59 HER2 positive patients and 163 HER2 negative patients.Patients from the first affiliated hospital of soochow university were set as the training set(n=154),and patients from Suzhou municipal hospital were set as the validation set(n=68).Comparing the mediolateral oblique(MLO)and cranial cauda(CC)X-ray images,the mammography images with larger lesion areas were selected,and the image segmentation and icomic feature extraction were performed by Mazda software.Fisher coefficients(Fisher),classification error probability combined average correlation coefficients(POE+ACC)and mutual information(MI)were used to select 3 sets of feature subsets.Z-score standardization was carried out for the feature subset with the highest accuracy,and then binary logistics regression was used for further screening.The linear fusion of selected features was used to construct the Radiomics Signature.The score of each patient’s Radiomics Signature was calculated,and the receiver operating characteristic curve(ROC)was analyzed to calculate the AUC,accuracy,sensitivity,specificity,positive predictive value,and negative predictive value of HER2 expression in breast cancer.Results:The(POE+ACC)-NDA method had the highest accuracy of 88.31%.In the training set,radiomics signature was obtained by logistic regression:radscore=-2.149-0.548×WavEnLH_s-4+0.475×Kurtosis-0.765×Perc.01%-0.703×WavEnHH_s-5-0.513×Teta4+1.069×135 dr_ShrtREmp-3.831×WavEnHH_s-1.In the training set,the radiomics scores of breast cancer in HER2 positive group and HER2 negative group were 0.159(-0.357,0.928)and-2.987(-3.997,-1.184)respectively,the difference was statistically significant(Z=-8.088,P <0.001).In the validation set,the radiomics scores of breast cancer in HER2 positive group and HER2 negative group were 0.475(-0.412,1.541)and-3.093(-4.126,-1.157)respectively.The difference was statistically significant(Z=-4.865,P<0.001).In the training set,the AUC,accuracy,sensitivity,specificity,positive predictive value,and negative predictive value of HER2 expression in breast cancer were 0.927(95%confidence interval 0.881~0.973),85.4%、87.6%、71.4%、94.3%and 87.0%;in the validation set,the AUC,accuracy,sensitivity,specificity,positive predictive value,and negative predictive value of HER2 expression in breast cancer were 0.889(95%confidence interval 0.813~0.964)、94.4%、74.0%、56.7%、97.3% and 79.4%.Conclusion:Mammography-based radiomics signature can be used to predict the expression of HER2 in patients with breast cancer,which has a high application value.