Institutional Repository of Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
| Radiomic analysis for preoperative prediction of cervical lymph node metastasis in patients with papillary thyroid carcinoma | |
Lu, Wei1,2; Zhong, Lianzhen2,3; Dong, Di2,3 ; Fang, Mengjie2,3; Dai, Qi1; Leng, Shaoyi1; Zhang, Liwen2,3; Sun, Wei1; Tian, Jie2,3,4; Zheng, Jianjun1; Jin, Yinhua1
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| Source Publication | EUROPEAN JOURNAL OF RADIOLOGY
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| ISSN | 0720-048X |
| 2019-09-01 | |
| Volume | 118Pages:231-238 |
| Corresponding Author | Tian, Jie(jie.tian@ia.ac.cn) ; Zheng, Jianjun(zhengjianjun@ucas.ac.cn) ; Jin, Yinhua(jinyh@ucas.ac.cn) |
| Abstract | 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. |
| Keyword | Forecasting Thyroid neoplasms Lymphatic metastasis |
| DOI | 10.1016/j.ejrad.2019.07.018 |
| WOS Keyword | PROGNOSTIC-FACTORS ; CANCER ; TOMOGRAPHY ; ULTRASOUND ; DIAGNOSIS ; MRI ; DISSECTION ; NODULES ; AMES ; CT |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | 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] ; 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] |
| Funding Organization | 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 |
| WOS Research Area | Radiology, Nuclear Medicine & Medical Imaging |
| WOS Subject | Radiology, Nuclear Medicine & Medical Imaging |
| WOS ID | WOS:000481609300034 |
| Publisher | ELSEVIER IRELAND LTD |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/27623 |
| Collection | 中国科学院分子影像重点实验室 |
| Corresponding Author | Tian, Jie; Zheng, Jianjun; Jin, Yinhua |
| Affiliation | 1.Univ Chinese Acad Sci, Hwa Mei Hosp, Dept Med Imaging, 41 Northwest St, Ningbo 315010, Zhejiang, Peoples R China 2.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Beijing, Peoples R China 4.Beihang Univ, Sch Med, Beijing Adv Innovat Ctr Big Data Based Precis Med, Beijing 100191, Peoples R China |
| First Author Affilication | Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China |
| Corresponding Author Affilication | Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China |
| Recommended Citation 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. |
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