中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 自动化研究所
  3. 中国科学院自动化研究所
  4. 中国科学院分子影像重点实验室
Radiomic analysis for preoperative prediction of cervical lymph node metastasis in patients with papillary thyroid carcinoma

文献类型：期刊论文

作者Lu, Wei2,3; Zhong, Lianzhen1,2; Dong, Di1,2; Fang, Mengjie1,2; Dai, Qi3; Leng, Shaoyi3; Zhang, Liwen1,2; Sun, Wei3; Tian, Jie1,2,4; Zheng, Jianjun3
刊名EUROPEAN JOURNAL OF RADIOLOGY
出版日期2019-09-01
卷号118页码:231-238
关键词Forecasting Thyroid neoplasms Lymphatic metastasis
ISSN号0720-048X
DOI10.1016/j.ejrad.2019.07.018
通讯作者Tian, Jie(jie.tian@ia.ac.cn) ; Zheng, Jianjun(zhengjianjun@ucas.ac.cn) ; Jin, Yinhua(jinyh@ucas.ac.cn)
英文摘要Purpose: Cervical lymph node (LN) metastasis of papillary thyroid carcinoma (PTC) is critical for treatment and prognosis. We explored the feasibility of using radiomics to preoperatively predict cervical LN metastasis in PTC patients. Method: Total 221 PTC patients (training cohort n = 154; validation cohort n = 67; divided randomly at the ratio of 7:3) were enrolled and divided into 2 groups based on LN pathologic diagnosis (NO: n = 118; N1 a and N1b: n = 88 and 15, respectively). We extracted 546 radiomic features from non-contrast and venous contrast-enhanced computed tomography (CT) images. We selected 8 groups of candidate feature sets by minimum redundancy maximum relevance (mRMR), and obtained 8 radiomic sub-signatures by support vector machine (SVM) to construct the radiomic signature. Incorporating the radiomic signature, CT-reported cervical LN status and clinical risk factors, a nomogram was constructed using multivariable logistic regression. The nomogram's calibration, discrimination, and clinical utility were assessed. Results: The radiomic signature was associated significantly with cervical LN status (p < 0.01 for both training and validation cohorts). The radiomic signature showed better predictive performance than any radiomic sub-signatures devised by SVM. Addition of radiomic signature to the nomogram improved the predictive value (area under the curve (AUC), 0.807 to 0.867) in the training cohort; this was confirmed in an independent validation cohort (AUC, 0.795 to 0.822). Good agreement was observed using calibration curves in both cohorts. Decision curve analysis demonstrated the radiomic nomogram was worthy of clinical application. Conclusions: Our radiomic nomogram improved the preoperative prediction of cervical LN metastasis in PTC patients.
WOS关键词PROGNOSTIC-FACTORS ; CANCER ; TOMOGRAPHY ; ULTRASOUND ; DIAGNOSIS ; MRI ; DISSECTION ; NODULES ; AMES ; CT
资助项目National Key R&D Program of China[2017YFC1308700] ; National Key R&D Program of China[2017YFA0205200] ; National Key R&D Program of China[2017YFC1309100] ; National Natural Science Foundation of China[81771924] ; National Natural Science Foundation of China[81501616] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[81671851] ; National Natural Science Foundation of China[81527805] ; Beijing Natural Science Foundation[L182061] ; Bureau of International Cooperation of Chinese Academy of Sciences[173211KYSB20160053] ; Instrument Developing Project of the Chinese Academy of Sciences[YZ201502] ; Youth Innovation Promotion Association CAS[2017175] ; Key R&D Project of Zhejiang Province[2017C03042] ; Major Medical and Health Program of Zhejiang Province[WKJ-ZJ-1807] ; Public Welfare Technology Application Research Project of Zhejiang Province[2017C35003] ; Natural Science Foundation of Zhejiang Province[LY18H180011] ; Public Welfare Technology Research Project of Zhejiang Province[LGF18H180017] ; Medical Science and Technology Project of Zhejiang Province[2019320334] ; Ningbo Municipal Leading and Top-notch Personnel Training Project[NBLJ201801030]
WOS研究方向Radiology, Nuclear Medicine & Medical Imaging
语种英语
WOS记录号WOS:000481609300034
出版者ELSEVIER IRELAND LTD
资助机构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 ; Instrument Developing Project of the Chinese Academy of Sciences ; Youth Innovation Promotion Association CAS ; Key R&D Project of Zhejiang Province ; Major Medical and Health Program of Zhejiang Province ; Public Welfare Technology Application Research Project of Zhejiang Province ; Natural Science Foundation of Zhejiang Province ; Public Welfare Technology Research Project of Zhejiang Province ; Medical Science and Technology Project of Zhejiang Province ; Ningbo Municipal Leading and Top-notch Personnel Training Project
源URL[http://ir.ia.ac.cn/handle/173211/27622]  
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; Zheng, Jianjun; Jin, Yinhua
作者单位1.Univ Chinese Acad Sci, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Hwa Mei Hosp, Dept Med Imaging, 41 Northwest St, Ningbo 315010, Zhejiang, Peoples R China
4.Beihang Univ, Sch Med, Beijing Adv Innovat Ctr Big Data Based Precis Med, Beijing 100191, Peoples R China
推荐引用方式
GB/T 7714		 Lu, Wei,Zhong, Lianzhen,Dong, Di,et al. Radiomic analysis for preoperative prediction of cervical lymph node metastasis in patients with papillary thyroid carcinoma[J]. EUROPEAN JOURNAL OF RADIOLOGY,2019,118:231-238.
APA Lu, Wei.,Zhong, Lianzhen.,Dong, Di.,Fang, Mengjie.,Dai, Qi.,...&Jin, Yinhua.(2019).Radiomic analysis for preoperative prediction of cervical lymph node metastasis in patients with papillary thyroid carcinoma.EUROPEAN JOURNAL OF RADIOLOGY,118,231-238.
MLA Lu, Wei,et al."Radiomic analysis for preoperative prediction of cervical lymph node metastasis in patients with papillary thyroid carcinoma".EUROPEAN JOURNAL OF RADIOLOGY 118(2019):231-238.

入库方式： OAI收割

来源：自动化研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。