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Noninvasive CT radiomic model for preoperative prediction of lymph node metastasis in early cervical carcinoma

文献类型：期刊论文

作者Chen, Jiaming1,6; He, Bingxi2,3,5; Dong, Di2,5; Liu, Ping1,6; Duan, Hui1,6; Li, Weili1,6; Li, Pengfei1,6; Wang, Lu1,6; Fan, Huijian1,6; Wang, Siwen2,5
刊名BRITISH JOURNAL OF RADIOLOGY
出版日期2020
卷号93期号:1108页码:8
ISSN号0007-1285
DOI10.1259/bjr.20190558
通讯作者Tian, Jie(jie.tian@ia.ac.cn) ; Huang, Zhipei(zhphuang@ucas.ac.cn) ; Chen, Chunlin(ccl1@smu.edu.cn)
英文摘要Objective: To build and validate a CT radiomic model for pre-operatively predicting lymph node metastasis in early cervical carcinoma. Methods and materials: A data set of 150 patients with Stage IB1 to IIA2 cervical carcinoma was retrospectively collected from the Nanfang hospital and separated into a training cohort (n = 104) and test cohort (n = 46). A total of 348 radiomic features were extracted from the delay phase of CT images. Mann-Whitney U test, recursive feature elimination, and backward elimination were used to select key radiomic features. Ridge logistics regression was used to build a radiomic model for prediction of lymph node metastasis (LNM) status by combining radiomic and clinical features. The area under the receiver operating characteristic curve (AUC) and kappa test were applied to verify the model. Results: Two radiomic features from delay phase CT images and one clinical feature were associated with LNM status: log-sigma-2-Omm-3D_glcm_Idn (p 0.01937), wavelet-HL_firstorder_Median (p = 0.03592), and Stage IB (p = 0.03608). Radiomic model was built consisting of the three features, and the AUCs were 0.80 (95% confidence interval: 0.70 - 0.90) and 0.75 (95% confidence intervall: 0.53 - 0.93) in training and test cohorts, respectively. The kappa coefficient was 0.84, showing excellent consistency. Conclusion: A non-invasive radiomic model, combining two radiomic features and a International Federation of Gynecology and Obstetrics stage, was built for prediction of LNM status in early cervical carcinoma. This model could serve as a pre-operative tool. Advances in knowledge: A noninvasive CT radiomic model, combining two radiomic features and the International Federation of Gynecology and Obstetrics stage, was built for prediction of LNM status in early cervical carcinoma.
WOS关键词PELVIC LYMPHADENECTOMY ; ENDOMETRIAL CANCER ; COMPLICATIONS ; ADENOCARCINOMA ; ACCURACY ; NOMOGRAM
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 Key R&D Program of China[2017YFC1308701] ; National Key R&D Program of China[2016YFC0103803] ; National Key R&D Program of China[2017YFA0700401] ; National Natural Science Foundation of China[81571422] ; National Natural Science Foundation of China[81370736] ; 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] ; National Natural Science Foundation of China[61671449] ; National Natural Science Foundation of China[61622117] ; National Science and Technology Support Program of China[2014BAI05B03] ; National Natural Science Fund of Guangdong[2015A030311024] ; Science and Technology Plan of Guangzhou[158100075] ; 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]
WOS研究方向Radiology, Nuclear Medicine & Medical Imaging
语种英语
WOS记录号WOS:000521530600007
出版者BRITISH INST RADIOLOGY
资助机构National Key R&D Program of China ; National Natural Science Foundation of China ; National Science and Technology Support Program of China ; National Natural Science Fund of Guangdong ; Science and Technology Plan of Guangzhou ; Beijing Municipal Science and Technology Commission ; Instrument Developing Project of the Chinese Academy of Sciences ; Youth Innovation Promotion Association CAS
源URL[http://ir.ia.ac.cn/handle/173211/38700]  
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; Huang, Zhipei; Chen, Chunlin
作者单位1.Southern Med Univ, Nanfang Hosp, Digital Med Lab, Dept Obstet & Gynecol, Guangzhou, Peoples R China
2.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing, Peoples R China
3.Univ Chinese Acad Sci, Sch Elect Elect & Commun Engn, Beijing, Peoples R China
4.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Beijing, Peoples R China
5.Univ Chinese Acad Sci, Beijing, Peoples R China
6.Southern Med Univ, Nanfang Hosp, Dept Obstet & Gynecol, Guangzhou, Peoples R China
推荐引用方式
GB/T 7714		 Chen, Jiaming,He, Bingxi,Dong, Di,et al. Noninvasive CT radiomic model for preoperative prediction of lymph node metastasis in early cervical carcinoma[J]. BRITISH JOURNAL OF RADIOLOGY,2020,93(1108):8.
APA Chen, Jiaming.,He, Bingxi.,Dong, Di.,Liu, Ping.,Duan, Hui.,...&Chen, Chunlin.(2020).Noninvasive CT radiomic model for preoperative prediction of lymph node metastasis in early cervical carcinoma.BRITISH JOURNAL OF RADIOLOGY,93(1108),8.
MLA Chen, Jiaming,et al."Noninvasive CT radiomic model for preoperative prediction of lymph node metastasis in early cervical carcinoma".BRITISH JOURNAL OF RADIOLOGY 93.1108(2020):8.

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