Institutional Repository of Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
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 |
ISSN | 0938-7994 |
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 |
DOI | 10.1007/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 | |
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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