Institutional Repository of Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
| The MR radiomic signature can predict preoperative lymph node metastasis in patients with esophageal cancer | |
Qu, Jinrong1,2; Shen, Chen2,3; Qin, Jianjun4; Wang, Zhaoqi1; Liu, Zhenyu3 ; Guo, Jia1; Zhang, Hongkai1; Gao, Pengrui1; Bei, Tianxia1; Wang, Yingshu1; Liu, Hui1; Kamel, Ihab R.5; Tian, Jie2,3; Li, Hailiang1
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| Source Publication | EUROPEAN RADIOLOGY
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| ISSN | 0938-7994 |
| 2019-02-01 | |
| Volume | 29Issue:2Pages:906-914 |
| Corresponding Author | Tian, Jie(jie.tian@ia.ac.cn) ; Li, Hailiang(doctorhnchr@126.com) |
| Abstract | PurposeTo assess the role of the MR radiomic signature in preoperative prediction of lymph node (LN) metastasis in patients with esophageal cancer (EC).Patients and methodsA total of 181 EC patients were enrolled in this study between April 2015 and September 2017. Their LN metastases were pathologically confirmed. The first half of this cohort (90 patients) was set as the training cohort, and the second half (91 patients) was set as the validation cohort. A total of 1578 radiomic features were extracted from MR images (T2-TSE-BLADE and contrast-enhanced StarVIBE). The lasso and elastic net regression model was exploited for dimension reduction and selection of the feature space. The multivariable logistic regression analysis was adopted to identify the radiomic signature of pathologically involved LNs. The discriminating performance was assessed with the area under receiver-operating characteristic curve (AUC). The Mann-Whitney U test was adopted for testing the potential correlation of the radiomic signature and the LN status in both training and validation cohorts.ResultsNine radiomic features were selected to create the radiomic signature significantly associated with LN metastasis (p < 0.001). AUC of radiomic signature performance in the training cohort was 0.821 (95% CI: 0.7042-0.9376) and in the validation cohort was 0.762 (95% CI: 0.7127-0.812). This model showed good discrimination between metastatic and non-metastatic lymph nodes.ConclusionThe present study showed MRI radiomic features that could potentially predict metastatic LN involvement in the preoperative evaluation of EC patients.Key Points center dot The role of MRI in preoperative staging of esophageal cancer patients is increasing.center dot MRI radiomic features showed the ability to predict LN metastasis in EC patients.center dot ICCs showed excellent interreader agreement of the extracted MR features. |
| Keyword | Magnetic resonance imaging Esophageal cancer Lymph nodes Metastasis |
| DOI | 10.1007/s00330-018-5583-z |
| WOS Keyword | CT TEXTURE ; HETEROGENEITY ; SEQUENCE ; NUMBER |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | National Natural Science Foundation of China[81501549] ; National Natural Science Foundation of China[81772012] ; National Key Research and Development Plan of China[2017YFA0205200] ; National Key Research and Development Plan of China[2016YFC0103001] ; Beijing Municipal Science & Technology Commission[Z171100000117023] ; Henan Health Science and Technology Innovation Talent Project[201004057] ; National Natural Science Foundation of China[81501549] ; National Natural Science Foundation of China[81772012] ; National Key Research and Development Plan of China[2017YFA0205200] ; National Key Research and Development Plan of China[2016YFC0103001] ; Beijing Municipal Science & Technology Commission[Z171100000117023] ; Henan Health Science and Technology Innovation Talent Project[201004057] |
| Funding Organization | National Natural Science Foundation of China ; National Key Research and Development Plan of China ; Beijing Municipal Science & Technology Commission ; Henan Health Science and Technology Innovation Talent Project |
| WOS Research Area | Radiology, Nuclear Medicine & Medical Imaging |
| WOS Subject | Radiology, Nuclear Medicine & Medical Imaging |
| WOS ID | WOS:000454706500045 |
| Publisher | SPRINGER |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/25634 |
| Collection | 中国科学院分子影像重点实验室 |
| Corresponding Author | Tian, Jie; Li, Hailiang |
| Affiliation | 1.Zhengzhou Univ, Henan Canc Hosp, Dept Radiol, Affiliated Canc Hosp, Zhengzhou 450003, Henan, Peoples R China 2.Xidian Univ, Sch Life Sci & Technol, Xian 710126, Shaanxi, Peoples R China 3.Chinese Acad Sci, Inst Automat, Key Lab Mol Imaging, Beijing 100190, Peoples R China 4.Zhengzhou Univ, Henan Canc Hosp, Dept Thorac Surg, Affiliated Canc Hosp, Zhengzhou 450003, Henan, Peoples R China 5.Johns Hopkins Univ, Sch Med, Dept Radiol, Baltimore, MD 21205 USA |
| Corresponding Author Affilication | Institute of Automation, Chinese Academy of Sciences |
| Recommended Citation GB/T 7714 | Qu, Jinrong,Shen, Chen,Qin, Jianjun,et al. The MR radiomic signature can predict preoperative lymph node metastasis in patients with esophageal cancer[J]. EUROPEAN RADIOLOGY,2019,29(2):906-914. |
| APA | Qu, Jinrong.,Shen, Chen.,Qin, Jianjun.,Wang, Zhaoqi.,Liu, Zhenyu.,...&Li, Hailiang.(2019).The MR radiomic signature can predict preoperative lymph node metastasis in patients with esophageal cancer.EUROPEAN RADIOLOGY,29(2),906-914. |
| MLA | Qu, Jinrong,et al."The MR radiomic signature can predict preoperative lymph node metastasis in patients with esophageal cancer".EUROPEAN RADIOLOGY 29.2(2019):906-914. |
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