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

doi:10.1259/bjr.20190558

CORC > 自动化研究所 > 中国科学院自动化研究所 > 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, Jiaming 1,2; He, Bingxi 3,4,5; Dong, Di 3,5; Liu, Ping 1,2; Duan, Hui 1,2; Li, Weili 1,2; Li, Pengfei 1,2; Wang, Lu 1,2; Fan, Huijian 1,2; Wang, Siwen 3,5
刊名	BRITISH JOURNAL OF RADIOLOGY
	2020
卷号	93 期号:1108 页码:8
ISSN号	0007-1285
DOI	10.1259/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.
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关键词	PELVIC LYMPHADENECTOMY ; ENDOMETRIAL CANCER ; COMPLICATIONS ; ADENOCARCINOMA ; ACCURACY ; NOMOGRAM
WOS研究方向	Radiology, Nuclear Medicine & Medical Imaging
语种	英语
出版者	BRITISH INST RADIOLOGY
WOS记录号	WOS:000521530600007
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
内容类型	期刊论文
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, 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
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.