Radiomic signature as a predictive factor for lymph node metastasis in early-stage cervical cancer

doi:10.1002/jmri.26209

	Radiomic signature as a predictive factor for lymph node metastasis in early-stage cervical cancer
	Kan, Yangyang 1,2,3; Dong, Di4,5 ; Zhang, Yuchen 6; Jiang, Wenyan 2,3; Zhao, Nannan 2,3; Han, Lu 2,3; Fang, Mengjie4,5 ; Zang, Yali4,5 ; Hu, Chaoen4,5 ; Tian, Jie4,5
刊名	JOURNAL OF MAGNETIC RESONANCE IMAGING
	2019
卷号	49 期号:1 页码:304-310
ISSN号	1053-1807
DOI	10.1002/jmri.26209
通讯作者	Tian, Jie(jie.tian@ia.ac.cn) ; Li, Chunming(li_chunming@hotmail.com) ; Luo, Yahong(Luoyahong8888@hotmail.com)
英文摘要	Background Lymph node metastasis (LNM) is the principal risk factor for poor outcomes in early-stage cervical cancer. Radiomics may offer a noninvasive way for predicting the stage of LNM. Purpose To evaluate a radiomic signature of LN involvement based on sagittal T-1 contrast-enhanced (CE) and T-2 MRI sequences. Study Type Retrospective. Population In all, 143 patients were randomly divided into two primary and validation cohorts with 100 patients in the primary cohort and 43 patients in the validation cohort. Field Strength/Sequence T-1 CE and T-2 MRI sequences at 3T. Assessment The gold standard of LN status was based on histologic results. A radiologist with 10 years of experience used the ITK-SNAP software for 3D manual segmentation. A senior radiologist with 15 years of experience validated all segmentations. The area under the receiver operating characteristics curve (ROC AUC), classification accuracy, sensitivity, and specificity were used between LNM and non-LNM groups. Statistical Tests A total of 970 radiomic features and seven clinical characteristics were extracted. Minimum redundancy / maximum relevance and support vector machine algorithms were applied to select features and construct a radiomic signature. The Mann-Whitney U-test and the chi-square test were used to test the performance of clinical characteristics and potential prognostic outcomes. The results were used to assess the quantitative discrimination performance of the SVM-based radiomic signature. Results The radiomic signatures allowed good discrimination between LNM and non-LNM groups. The ROC AUC was 0.753 (95% confidence interval [CI], 0.656-0.850) in the primary cohort and 0.754 (95% CI, 0584-0.924) in the validation cohort. Data Conclusions A multiple-sequence MRI radiomic signature can be used as a noninvasive biomarker for preoperative assessment of LN status and potentially influence the therapeutic decision-making in early-stage cervical cancer patients. Level of Evidence: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:304-310.
资助项目	National Natural Science Foundation of China[81771924] ; National Natural Science Foundation of China[81501616] ; National Natural Science Foundation of China[81671851] ; National Natural Science Foundation of China[81527805] ; National Natural Science Foundation of China[81601492] ; National Key R&D Program of China[2017YFA0205200] ; National Key R&D Program of China[2017YFC1308700] ; National Key R&D Program of China[2017YFC1308701] ; National Key R&D Program of China[2017YFC1309100] ; Science and Technology Service Network Initiative of the Chinese Academy of Sciences[KFJ-SW-STS-160] ; Instrument Developing Project of the Chinese Academy of Sciences[YZ201502] ; Beijing Municipal Science and Technology Commission[Z161100002616022] ; Youth Innovation Promotion Association CAS ; Special Fund for Research in the Public Interest of China[201402020]
WOS关键词	SURVIVAL ; ENDOMETRIAL ; CARCINOMA ; NEOPLASMS ; CT
WOS研究方向	Radiology, Nuclear Medicine & Medical Imaging
语种	英语
出版者	WILEY
WOS记录号	WOS:000453908200027
资助机构	National Natural Science Foundation of China ; National Key R&D Program of China ; Science and Technology Service Network Initiative of the Chinese Academy of Sciences ; Instrument Developing Project of the Chinese Academy of Sciences ; Beijing Municipal Science and Technology Commission ; Youth Innovation Promotion Association CAS ; Special Fund for Research in the Public Interest of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/25657]
专题	中国科学院自动化研究所
通讯作者	Tian, Jie; Li, Chunming; Luo, Yahong
作者单位	1.Dalian Med Univ, Dalian, Peoples R China 2.China Med Univ, Canc Hosp, Shenyang, Liaoning, Peoples R China 3.Liaoning Canc Hosp & Inst, Shenyang, Liaoning, Peoples R China 4.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing, Peoples R China 5.Univ Chinese Acad Sci, Beijing, Peoples R China 6.Univ Elect Sci & Technol China, Chengdu, Sichuan, Peoples R China
推荐引用方式 GB/T 7714	Kan, Yangyang,Dong, Di,Zhang, Yuchen,et al. Radiomic signature as a predictive factor for lymph node metastasis in early-stage cervical cancer[J]. JOURNAL OF MAGNETIC RESONANCE IMAGING,2019,49(1):304-310.
APA	Kan, Yangyang.,Dong, Di.,Zhang, Yuchen.,Jiang, Wenyan.,Zhao, Nannan.,...&Luo, Yahong.(2019).Radiomic signature as a predictive factor for lymph node metastasis in early-stage cervical cancer.JOURNAL OF MAGNETIC RESONANCE IMAGING,49(1),304-310.
MLA	Kan, Yangyang,et al."Radiomic signature as a predictive factor for lymph node metastasis in early-stage cervical cancer".JOURNAL OF MAGNETIC RESONANCE IMAGING 49.1(2019):304-310.