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

doi:10.1259/bjr.20191019

CORC > 自动化研究所 > 中国科学院自动化研究所 > 中国科学院分子影像重点实验室

	Mammography-based radiomics nomogram: a potential biomarker to predict axillary lymph node metastasis in breast cancer
	Tan, Hongna 3,4,5; Wu, Yaping 3,4,5; Bao, Fengchang 1,5; Zhou, Jing 3,4,5; Wan, Jianzhong 6,7; Tian, Jie 2; Lin, Yusong 6,7; Wang, Meiyun 3,4,5
刊名	BRITISH JOURNAL OF RADIOLOGY
	2020
卷号	93 期号:1111 页码:11
ISSN号	0007-1285
DOI	10.1259/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.
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关键词	QUALITY-OF-LIFE ; PREOPERATIVE PREDICTION ; MRI ; ULTRASONOGRAPHY ; DISSECTION ; BIOPSY
WOS研究方向	Radiology, Nuclear Medicine & Medical Imaging
语种	英语
出版者	BRITISH INST RADIOLOGY
WOS记录号	WOS:000542990000012
资助机构	China Postdoctoral Science Foundation ; National Natural Scientific Foundation of China ; Henan Provincial Department of Science and Technology Research Project
内容类型	期刊论文
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, Dept Hematol, Henan Prov Peoples Hosp, Zhengzhou 450003, Henan, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 3.Zhengzhou Univ, Dept Radiol, Henan Prov Peoples Hosp, Zhengzhou 450003, Henan, Peoples R China 4.Zhengzhou Univ, Imaging Diag Neurol Dis & Res Lab Henan Prov, Zhengzhou 450003, Henan, Peoples R China 5.Zhengzhou Univ, Peoples Hosp, Zhengzhou 450003, Henan, Peoples R China 6.Zhengzhou Univ, Sch Software, Zhengzhou 450052, Henan, Peoples R China 7.Zhengzhou Univ, Collaborat Innovat Ctr Internet Healthcare, Zhengzhou 450052, 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.