CASIA OpenIR  > 中国科学院分子影像重点实验室
Noninvasive CT radiomic model for preoperative prediction of lymph node metastasis in early cervical carcinoma
Chen, Jiaming1,2; He, Bingxi3,4,5; Dong, Di3,5; Liu, Ping1,2; Duan, Hui1,2; Li, Weili1,2; Li, Pengfei1,2; Wang, Lu1,2; Fan, Huijian1,2; Wang, Siwen3,5; Zhang, Liwen3,5; Tian, Jie3,5,6; Huang, Zhipei4,5; Chen, Chunlin1,2
发表期刊BRITISH JOURNAL OF RADIOLOGY
ISSN0007-1285
2020
卷号93期号:1108页码:8
通讯作者Tian, Jie(jie.tian@ia.ac.cn) ; Huang, Zhipei(zhphuang@ucas.ac.cn) ; Chen, Chunlin(ccl1@smu.edu.cn)
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.
DOI10.1259/bjr.20190558
关键词[WOS]PELVIC LYMPHADENECTOMY ; ENDOMETRIAL CANCER ; COMPLICATIONS ; ADENOCARCINOMA ; ACCURACY ; NOMOGRAM
收录类别SCI
语种英语
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]
项目资助者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
WOS研究方向Radiology, Nuclear Medicine & Medical Imaging
WOS类目Radiology, Nuclear Medicine & Medical Imaging
WOS记录号WOS:000521530600007
出版者BRITISH INST RADIOLOGY
七大方向——子方向分类医学影像处理与分析
引用统计
被引频次:15[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/38701
专题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, Dept Obstet & Gynecol, Guangzhou, Peoples R China
2.Southern Med Univ, Nanfang Hosp, Digital Med Lab, Dept Obstet & Gynecol, Guangzhou, Peoples R China
3.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing, Peoples R China
4.Univ Chinese Acad Sci, Sch Elect Elect & Commun Engn, Beijing, Peoples R China
5.Univ Chinese Acad Sci, Beijing, Peoples R China
6.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Beijing, Peoples R China
通讯作者单位中国科学院自动化研究所
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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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