CASIA OpenIR  > 中国科学院分子影像重点实验室
Building CT Radiomics Based Nomogram for Preoperative Esophageal Cancer Patients Lymph Node Metastasis Prediction
Shen, Chen1,2; Liu, Zhenyu2; Wang, Zhaoqi1,3; Guo, Jia3; Zhang, Hongkai3; Wang, Yingshu3; Qin, Jianjun4; Li, Hailiang3; Fang, Mengjie2; Tang, Zhenchao5; Li, Yin3; Qu, Jinrong3; Tian, Jie1,2
Source PublicationTRANSLATIONAL ONCOLOGY
2018-06-01
Volume11Issue:3Pages:815-824
SubtypeArticle
AbstractPURPOSE: To build and validate a radiomics-based nomogram for the prediction of pre-operation lymph node (LN) metastasis in esophageal cancer. PATIENTS AND METHODS: A total of 197 esophageal cancer patients were enrolled in this study, and their LN metastases have been pathologically confirmed. The data were collected from January 2016 to May 2016; patients in the first three months were set in the training cohort, and patients in April 2016 were set in the validation cohort. About 788 radiomics features were extracted from computed tomography (CT) images of the patients. The elastic-net approach was exploited for dimension reduction and selection of the feature space. The multivariable logistic regression analysis was adopted to build the radiomics signature and another predictive nomogram model. The predictive nomogram model was composed of three factors with the radiomics signature, where CT reported the LN number and position risk level. The performance and usefulness of the built model were assessed by the calibration and decision curve analysis. RESULTS: Thirteen radiomics features were selected to build the radiomics signature. The radiomics signature was significantly associated with the LN metastasis (P<0.001). The area under the curve (AUC) of the radiomics signature performance in the training cohort was 0.806 (95% CI: 0.732-0.881), and in the validation cohort it was 0.771 (95% CI: 0.632-0.910). The model showed good discrimination, with a Harrell's Concordance Index of 0.768 (0.672 to 0.864, 95% CI) in the training cohort and 0.754 (0.603 to 0.895, 95% CI) in the validation cohort. Decision curve analysis showed ourmodel will receive benefit when the threshold probability was larger than 0.15. CONCLUSION: The present study proposed a radiomics-based nomogram involving the radiomics signature, so the CT reported the status of the suspected LN and the dummy variable of the tumor position. It can be potentially applied in the individual preoperative prediction of the LN metastasis status in esophageal cancer patients.
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
DOI10.1016/j.tranon.2018.04.005
WOS KeywordLIMITED TRANSHIATAL RESECTION ; POSITRON-EMISSION-TOMOGRAPHY ; ENDOSCOPIC ULTRASONOGRAPHY ; ESOPHAGOGASTRIC JUNCTION ; TUMOR HETEROGENEITY ; 5-YEAR SURVIVAL ; ADENOCARCINOMA ; CARCINOMA ; CHEMOTHERAPY ; TEXTURE
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(81772012 ; National Key Research and Development Plan of China(2017YFA0205200 ; International Innovation Team of CAS(20140491524) ; Beijing Municipal Science & Technology Commission(Z161100002616022 ; 81501549) ; 2016YFC0103001) ; Z171100000117023)
WOS Research AreaOncology
WOS SubjectOncology
WOS IDWOS:000433287500030
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/22044
Collection中国科学院分子影像重点实验室
Affiliation1.Xidian Univ, Sch Life Sci & Technol, Xian 710126, Shaanxi, Peoples R China
2.Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
3.Zhengzhou Univ, Henan Canc Hosp, Affiliated Canc Hosp, Dept Radiol, Zhengzhou 450003, Henan, Peoples R China
4.Zhengzhou Univ, Henan Canc Hosp, Affiliated Canc Hosp, Dept Thorac Surg, Zhengzhou 450003, Henan, Peoples R China
5.Shandong Univ, Sch Mech Elect & Informat Engn, Weihai 264209, Shandong, Peoples R China
6.Univ Chinese Acad Sci, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Shen, Chen,Liu, Zhenyu,Wang, Zhaoqi,et al. Building CT Radiomics Based Nomogram for Preoperative Esophageal Cancer Patients Lymph Node Metastasis Prediction[J]. TRANSLATIONAL ONCOLOGY,2018,11(3):815-824.
APA Shen, Chen.,Liu, Zhenyu.,Wang, Zhaoqi.,Guo, Jia.,Zhang, Hongkai.,...&Tian, Jie.(2018).Building CT Radiomics Based Nomogram for Preoperative Esophageal Cancer Patients Lymph Node Metastasis Prediction.TRANSLATIONAL ONCOLOGY,11(3),815-824.
MLA Shen, Chen,et al."Building CT Radiomics Based Nomogram for Preoperative Esophageal Cancer Patients Lymph Node Metastasis Prediction".TRANSLATIONAL ONCOLOGY 11.3(2018):815-824.
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