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Radiomic nomogram for prediction of axillary lymph node metastasis in breast cancer
Han, Lu1,2; Zhu, Yongbei3; Liu, Zhenyu3,4; Yu, Tao1,2; He, Cuiju1,2; Jiang, Wenyan1,2; Kan, Yangyang1,2; Dong, Di3,4; Tian, Jie3,4,5; Luo, Yahong1,2
发表期刊EUROPEAN RADIOLOGY
ISSN0938-7994
2019-07-01
卷号29期号:7页码:3820-3829
通讯作者Dong, Di(di.dong@ia.ac.cn) ; Luo, Yahong(Luoyahong8888@hotmail.com)
摘要ObjectiveTo develop a radiomic nomogram for preoperative prediction of axillary lymph node (LN) metastasis in breast cancer patients.MethodsPreoperative magnetic resonance imaging data from 411 breast cancer patients was studied. Patients were assigned to either a training cohort (n=279) or a validation cohort (n=132). Eight hundred eight radiomic features were extracted from the first phase of T1-DCE images. A support vector machine was used to develop a radiomic signature, and logistic regression was used to develop a nomogram.ResultsThe radiomic signature based on 12 LN status-related features was constructed to predict LN metastasis, its prediction ability was moderate, with an area under the curve (AUC) of 0.76 and 0.78 in training and validation cohorts, respectively. Based on a radiomic signature and clinical features, a nomogram was developed and showed excellent predictive ability for LN metastasis (AUC 0.84 and 0.87 in training and validation sets, respectively). Another radiomic signature was constructed to distinguish the number of metastatic LNs (less than 2 positive nodes/more than 2 positive nodes), which also showed moderate performance (AUC 0.79).ConclusionsWe developed a nomogram and a radiomic signature that can be used to identify LN metastasis and distinguish the number of metastatic LNs (less than 2 positive nodes/more than 2 positive nodes). Both nomogram and radiomic signature can be used as tools to assist clinicians in assessing LN metastasis in breast cancer patients.Key Points center dot ALNM is an important factor affecting breast cancer patients' treatment and prognosis.center dot Traditional imaging examinations have limited value for evaluating axillary LNs status.center dot We developed a radiomic nomogram based on MR imagings to predict LN metastasis.
关键词Breast cancer Axillary lymph node metastasis Radiomics Preoperative prediction MRI
DOI10.1007/s00330-018-5981-2
关键词[WOS]F-18-FDG PET/CT ; SENTINEL NODE ; MRI ; DISSECTION ; ULTRASONOGRAPHY ; BIOPSY ; INFORMATION ; ULTRASOUND ; ACCURACY ; IMAGES
收录类别SCI
语种英语
资助项目Special Fund for Research in the Public Interest of China[201402020] ; National Key R&D Program of China[2017YFA0205200] ; National Key R&D Program of China[2017YFC1308700] ; National Key R&D Program of China[2017YFC1308701] ; National Key R&D Program of China[2017YFC1309100] ; National Key R&D Program of China[2016YFC0103803] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[81771924] ; National Natural Science Foundation of China[81501616] ; National Natural Science Foundation of China[81671851] ; National Natural Science Foundation of China[81671854] ; National Natural Science Foundation of China[81527805] ; Beijing Natural Science Foundation[L182061] ; Bureau of International Cooperation of Chinese Academy of Sciences[173211KYSB20160053] ; Science and Technology Service Network Initiative of the Chinese Academy of Sciences[KFJ-SW-STS-160] ; Beijing Municipal Science and Technology Commission[Z171100000117023] ; Beijing Municipal Science and Technology Commission[Z161100002616022] ; Instrument Developing Project of the Chinese Academy of Sciences[YZ201502] ; Youth Innovation Promotion Association CAS[2017175] ; Youth Innovation Promotion Association CAS[2017175] ; Instrument Developing Project of the Chinese Academy of Sciences[YZ201502] ; Beijing Municipal Science and Technology Commission[Z161100002616022] ; Beijing Municipal Science and Technology Commission[Z171100000117023] ; Science and Technology Service Network Initiative of the Chinese Academy of Sciences[KFJ-SW-STS-160] ; Bureau of International Cooperation of Chinese Academy of Sciences[173211KYSB20160053] ; Beijing Natural Science Foundation[L182061] ; National Natural Science Foundation of China[81527805] ; National Natural Science Foundation of China[81671854] ; National Natural Science Foundation of China[81671851] ; National Natural Science Foundation of China[81501616] ; National Natural Science Foundation of China[81771924] ; National Natural Science Foundation of China[81227901] ; National Key R&D Program of China[2016YFC0103803] ; National Key R&D Program of China[2017YFC1309100] ; National Key R&D Program of China[2017YFC1308701] ; National Key R&D Program of China[2017YFC1308700] ; National Key R&D Program of China[2017YFA0205200] ; Special Fund for Research in the Public Interest of China[201402020] ; Special Fund for Research in the Public Interest of China[201402020] ; National Key R&D Program of China[2017YFA0205200] ; National Key R&D Program of China[2017YFC1308700] ; National Key R&D Program of China[2017YFC1308701] ; National Key R&D Program of China[2017YFC1309100] ; National Key R&D Program of China[2016YFC0103803] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[81771924] ; National Natural Science Foundation of China[81501616] ; National Natural Science Foundation of China[81671851] ; National Natural Science Foundation of China[81671854] ; National Natural Science Foundation of China[81527805] ; Beijing Natural Science Foundation[L182061] ; Bureau of International Cooperation of Chinese Academy of Sciences[173211KYSB20160053] ; Science and Technology Service Network Initiative of the Chinese Academy of Sciences[KFJ-SW-STS-160] ; Beijing Municipal Science and Technology Commission[Z171100000117023] ; Beijing Municipal Science and Technology Commission[Z161100002616022] ; Instrument Developing Project of the Chinese Academy of Sciences[YZ201502] ; Youth Innovation Promotion Association CAS[2017175]
项目资助者Special Fund for Research in the Public Interest of China ; National Key R&D Program of China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation ; Bureau of International Cooperation of Chinese Academy of Sciences ; Science and Technology Service Network Initiative of the Chinese Academy of Sciences ; Beijing Municipal Science and Technology Commission ; Instrument Developing Project of the Chinese Academy of Sciences ; Youth Innovation Promotion Association CAS
WOS研究方向Radiology, Nuclear Medicine & Medical Imaging
WOS类目Radiology, Nuclear Medicine & Medical Imaging
WOS记录号WOS:000470679400053
出版者SPRINGER
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:117[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/173211/24393
专题中国科学院分子影像重点实验室
通讯作者Dong, Di; Luo, Yahong
作者单位1.China Med Univ, Canc Hosp, Shenyang 110042, Liaoning, Peoples R China
2.Liaoning Canc Hosp & Inst, Shenyang 110042, Liaoning, Peoples R China
3.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
5.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Beijing 100191, 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
Han, Lu,Zhu, Yongbei,Liu, Zhenyu,et al. Radiomic nomogram for prediction of axillary lymph node metastasis in breast cancer[J]. EUROPEAN RADIOLOGY,2019,29(7):3820-3829.
APA Han, Lu.,Zhu, Yongbei.,Liu, Zhenyu.,Yu, Tao.,He, Cuiju.,...&Luo, Yahong.(2019).Radiomic nomogram for prediction of axillary lymph node metastasis in breast cancer.EUROPEAN RADIOLOGY,29(7),3820-3829.
MLA Han, Lu,et al."Radiomic nomogram for prediction of axillary lymph node metastasis in breast cancer".EUROPEAN RADIOLOGY 29.7(2019):3820-3829.
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