Mammography-based radiomic analysis for predicting benign BI-RADS category 4 calcifications

doi:10.1016/j.ejrad.2019.108711

	Mammography-based radiomic analysis for predicting benign BI-RADS category 4 calcifications
	Lei, Chuqian 1,2,3; Wei, Wei4,5,6 ; Liu, Zhenyu6 ; Xiong, Qianqian 1,2,3; Yang, Ciqiu 1; Yang, Mei 1; Zhang, Liulu 1; Zhu, Teng 1; Zhuang, Xiaosheng 1,7; Liu, Chunling 8; Liu, Zaiyi 8; Tian, Jie 5,6,9; Wang, Kun 1,2,3
发表期刊	EUROPEAN JOURNAL OF RADIOLOGY
ISSN	0720-048X
	2019-12-01
卷号	121 页码:8
通讯作者	Tian, Jie(jie.tian@ia.ac.cn) ; Wang, Kun(gzwangkun@126.com)
摘要	Purpose: We developed and validated a radiomic model based on mammography and assessed its value for predicting the pathological diagnosis of Breast Imaging Reporting and Data System (BI-RADS) category 4 calcifications. Materials and methods: Patients with a total of 212 eligible calcifications were recruited (159 cases in the primary cohort and 53 cases in the validation cohort). In total, 8286 radiomic features were extracted from the craniocaudal (CC) and mediolateral oblique (MLO) images. Machine learning was used to select features and build a radiomic signature. The clinical risk factors were selected from the independent clinical factors through logistic regression analyses. The radiomic nomogram incorporated the radiomic signature and an independent clinical risk factor. The diagnostic performance of the radiomic model and the radiologists' empirical prediction model was evaluated by the area under the receiver operating characteristic curve (AUC). The differences between the various AUCs were compared with DeLong's test. Results: Six radiomic features and the menopausal state were included in the radiomic nomogram, which discriminated benign calcifications from malignant calcifications with an AUC of 0.80 in the validation cohort. The difference between the classification results of the radiomic nomogram and that of radiologists was significant (p < 0.05). Particularly for patients with calcifications that are negative on ultrasounds but can be detected by mammography (MG+/US-calcifications), the identification ability of the radiomic nomogram was very strong. Conclusions: The mammography-based radiomic nomogram is a potential tool to distinguish benign calcifications from malignant calcifications.
关键词	Radiomics Breast Calcification Predictive value of test Unnecessary procedures
DOI	10.1016/j.ejrad.2019.108711
关键词[WOS]	BREAST-CANCER ; MICROCALCIFICATION DESCRIPTORS ; SCREENING MAMMOGRAPHY ; REGULARIZATION PATHS ; RISK ; CHEMORADIOTHERAPY ; PERFORMANCE ; WOMEN ; MODEL
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2017YFC1309100] ; National Key Research and Development Program of China[2017YFA0205200] ; Natural Science Foundation of Guangdong Province, China[2017A030313882] ; National Natural Science Foundation of China[81871513] ; National Natural Science Foundation of China[81772012] ; National Natural Science Foundation of China[81922040] ; Beijing Natural Science Foundation[7182109] ; Youth Innovation Promotion Association CAS[2019136] ; CSC0-constant Rui Tumor Research Fund, China[Y-HR2016-067] ; National Key Research and Development Program of China[2017YFC1309100] ; National Key Research and Development Program of China[2017YFA0205200] ; Natural Science Foundation of Guangdong Province, China[2017A030313882] ; National Natural Science Foundation of China[81871513] ; National Natural Science Foundation of China[81772012] ; National Natural Science Foundation of China[81922040] ; Beijing Natural Science Foundation[7182109] ; Youth Innovation Promotion Association CAS[2019136] ; CSC0-constant Rui Tumor Research Fund, China[Y-HR2016-067]
项目资助者	National Key Research and Development Program of China ; Natural Science Foundation of Guangdong Province, China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation ; Youth Innovation Promotion Association CAS ; CSC0-constant Rui Tumor Research Fund, China
WOS研究方向	Radiology, Nuclear Medicine & Medical Imaging
WOS类目	Radiology, Nuclear Medicine & Medical Imaging
WOS记录号	WOS:000500465900028
出版者	ELSEVIER IRELAND LTD
七大方向——子方向分类	医学影像处理与分析
引用统计	被引频次：30[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/29368
专题	中国科学院分子影像重点实验室
通讯作者	Tian, Jie; Wang, Kun
作者单位	1.Southern Med Univ, Sch Clin Med 2, Guangzhou 510515, Guangdong, Peoples R China 2.Guangdong Prov Peoples Hosp, Canc Ctr, Dept Breast Canc, Guangzhou 510080, Guangdong, Peoples R China 3.Guangdong Acad Med Sci, Guangzhou 510080, Guangdong, Peoples R China 4.Xian Polytech Univ, Sch Elect & Informat, Xian 710000, Shaanxi, Peoples R China 5.Xidian Univ, Engn Res Ctr Mol & Neuro Imaging, Sch Life Sci & Technol, Minist Educ, Xian 710126, Shaanxi, Peoples R China 6.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China 7.Shantou Univ, Med Coll, Shantou 515041, Guangdong, Peoples R China 8.Guangdong Prov Peoples Hosp, Dept Radiol, Guangzhou 510080, Guangdong, Peoples R China 9.Univ Chinese Acad Sci, Beijing 100190, Peoples R China
通讯作者单位	中国科学院分子影像重点实验室
推荐引用方式 GB/T 7714	Lei, Chuqian,Wei, Wei,Liu, Zhenyu,et al. Mammography-based radiomic analysis for predicting benign BI-RADS category 4 calcifications[J]. EUROPEAN JOURNAL OF RADIOLOGY,2019,121:8.
APA	Lei, Chuqian.,Wei, Wei.,Liu, Zhenyu.,Xiong, Qianqian.,Yang, Ciqiu.,...&Wang, Kun.(2019).Mammography-based radiomic analysis for predicting benign BI-RADS category 4 calcifications.EUROPEAN JOURNAL OF RADIOLOGY,121,8.
MLA	Lei, Chuqian,et al."Mammography-based radiomic analysis for predicting benign BI-RADS category 4 calcifications".EUROPEAN JOURNAL OF RADIOLOGY 121(2019):8.