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Mammography-based radiomics nomogram: a potential biomarker to predict axillary lymph node metastasis in breast cancer

文献类型：期刊论文

作者Tan, Hongna1,2,7; Wu, Yaping1,2,7; Bao, Fengchang2,3; Zhou, Jing1,2,7; Wan, Jianzhong4,5; Tian, Jie6; Lin, Yusong4,5; Wang, Meiyun1,2,7
刊名BRITISH JOURNAL OF RADIOLOGY
出版日期2020
卷号93期号:1111页码:11
ISSN号0007-1285
DOI10.1259/bjr.20191019
通讯作者Wang, Meiyun(mywang@ha.edu.cn)
英文摘要Objective: To establish a radiomics nomogram by integrating clinical risk factors and radiomics features extracted from digital mammography (MG) images for pre-operative prediction of axillary lymph node (ALN) metastasis in breast cancer. Methods: 216 patients with breast cancer lesions confirmed by surgical excision pathology were divided into the primary cohort (n = 144) and validation cohort (n = 72). Radiomics features were extracted from craniocaudal (CC) view of mammograms, and radiomics features selection were performed using the methods of ANOVA F-value and least absolute shrinkage and selection operator; then a radiomics signature was constructed with the method of support vector machine. Multivariate logistic regression analysis was used to establish a radiomics nomogram based on the combination of radiomics signature and clinical factors. The C-index and calibration curves were derived based on the regression analysis both in the primary and validation cohorts. Results: 95 of 216 patients were confirmed with ALN metastasis by pathology, and 52 cases were diagnosed as ALN metastasis based on MG-reported criteria. The sensitivity, specificity, accuracy and AUC (area under the receiver operating characteristic curve of MG-reported criteria were 42.7%, 90.8%, 24.1% and 0.666 (95% confidence interval: 0.591-0.741]. The radiomics nomogram, comprising progesterone receptor status, molecular subtype and radiomics signature, showed good calibration and better favorite performance for the metastatic ALN detection (AUC 0.883 and 0.863 in the primary and validation cohorts) than each independent clinical features (AUC 0.707 and 0.657 in the primary and validation cohorts) and radiomics signature (AUC 0.876 and 0.862 in the primary and validation cohorts). Conclusion: The MG-based radiomics nomogram could be used as a non-invasive and reliable tool in predicting ALN metastasis and may facilitate to assist clinicians for pre-operative decision-making. Advances in knowledge: ALN status remains among the most important breast cancer prognostic factors and is essential for making treatment decisions. However, the value of detecting metastatic ALN by MG is very limited. The studies on pre-operative ALN metastasis prediction using the method of MG-based radiomics in breast cancer are very few. Therefore, we studied whether MG-based radiomics nomogram could be used as a predictive biomarker for the detection of metastatic ALN.
WOS关键词QUALITY-OF-LIFE ; PREOPERATIVE PREDICTION ; MRI ; ULTRASONOGRAPHY ; DISSECTION ; BIOPSY
资助项目China Postdoctoral Science Foundation[2018M632779] ; National Natural Scientific Foundation of China[81401378] ; National Natural Scientific Foundation of China[81772009] ; Henan Provincial Department of Science and Technology Research Project[201602221] ; Henan Provincial Department of Science and Technology Research Project[182102310162]
WOS研究方向Radiology, Nuclear Medicine & Medical Imaging
语种英语
WOS记录号WOS:000542990000012
出版者BRITISH INST RADIOLOGY
资助机构China Postdoctoral Science Foundation ; National Natural Scientific Foundation of China ; Henan Provincial Department of Science and Technology Research Project
源URL[http://ir.ia.ac.cn/handle/173211/39939]  
专题自动化研究所_中国科学院分子影像重点实验室
通讯作者Wang, Meiyun
作者单位1.Zhengzhou Univ, Imaging Diag Neurol Dis & Res Lab Henan Prov, Zhengzhou 450003, Henan, Peoples R China
2.Zhengzhou Univ, Peoples Hosp, Zhengzhou 450003, Henan, Peoples R China
3.Zhengzhou Univ, Dept Hematol, Henan Prov Peoples Hosp, Zhengzhou 450003, Henan, Peoples R China
4.Zhengzhou Univ, Collaborat Innovat Ctr Internet Healthcare, Zhengzhou 450052, Henan, Peoples R China
5.Zhengzhou Univ, Sch Software, Zhengzhou 450052, Henan, Peoples R China
6.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
7.Zhengzhou Univ, Dept Radiol, Henan Prov Peoples Hosp, Zhengzhou 450003, Henan, Peoples R China
推荐引用方式
GB/T 7714		 Tan, Hongna,Wu, Yaping,Bao, Fengchang,et al. Mammography-based radiomics nomogram: a potential biomarker to predict axillary lymph node metastasis in breast cancer[J]. BRITISH JOURNAL OF RADIOLOGY,2020,93(1111):11.
APA Tan, Hongna.,Wu, Yaping.,Bao, Fengchang.,Zhou, Jing.,Wan, Jianzhong.,...&Wang, Meiyun.(2020).Mammography-based radiomics nomogram: a potential biomarker to predict axillary lymph node metastasis in breast cancer.BRITISH JOURNAL OF RADIOLOGY,93(1111),11.
MLA Tan, Hongna,et al."Mammography-based radiomics nomogram: a potential biomarker to predict axillary lymph node metastasis in breast cancer".BRITISH JOURNAL OF RADIOLOGY 93.1111(2020):11.

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