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

文献类型：期刊论文

作者Lei, Chuqian1,7,8; Wei, Wei5,6,9; Liu, Zhenyu5; Xiong, Qianqian1,7,8; Yang, Ciqiu7; Yang, Mei7; Zhang, Liulu7; Zhu, Teng7; Zhuang, Xiaosheng4,7; Liu, Chunling3
刊名EUROPEAN JOURNAL OF RADIOLOGY
出版日期2019-12-01
卷号121页码:8
ISSN号0720-048X
关键词Radiomics Breast Calcification Predictive value of test Unnecessary procedures
DOI10.1016/j.ejrad.2019.108711
通讯作者Tian, Jie(jie.tian@ia.ac.cn) ; Wang, Kun(gzwangkun@126.com)
英文摘要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.
WOS关键词BREAST-CANCER ; MICROCALCIFICATION DESCRIPTORS ; SCREENING MAMMOGRAPHY ; REGULARIZATION PATHS ; RISK ; CHEMORADIOTHERAPY ; PERFORMANCE ; WOMEN ; MODEL
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]
WOS研究方向Radiology, Nuclear Medicine & Medical Imaging
语种英语
出版者ELSEVIER IRELAND LTD
WOS记录号WOS:000500465900028
资助机构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
源URL[http://ir.ia.ac.cn/handle/173211/29367]  
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Tian, Jie; Wang, Kun
作者单位1.Guangdong Acad Med Sci, Guangzhou 510080, Guangdong, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100190, Peoples R China
3.Guangdong Prov Peoples Hosp, Dept Radiol, Guangzhou 510080, Guangdong, Peoples R China
4.Shantou Univ, Med Coll, Shantou 515041, Guangdong, Peoples R China
5.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
6.Xidian Univ, Engn Res Ctr Mol & Neuro Imaging, Sch Life Sci & Technol, Minist Educ, Xian 710126, Shaanxi, Peoples R China
7.Southern Med Univ, Sch Clin Med 2, Guangzhou 510515, Guangdong, Peoples R China
8.Guangdong Prov Peoples Hosp, Canc Ctr, Dept Breast Canc, Guangzhou 510080, Guangdong, Peoples R China
9.Xian Polytech Univ, Sch Elect & Informat, Xian 710000, Shaanxi, Peoples R China
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.

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来源：自动化研究所

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