Institutional Repository of Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
| 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
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| Source Publication | TRANSLATIONAL ONCOLOGY
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| 2018-06-01 | |
| Volume | 11Issue:3Pages:815-824 |
| Subtype | Article |
| Abstract | PURPOSE: 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 Headings | Science & Technology ; Life Sciences & Biomedicine |
| DOI | 10.1016/j.tranon.2018.04.005 |
| WOS Keyword | LIMITED TRANSHIATAL RESECTION ; POSITRON-EMISSION-TOMOGRAPHY ; ENDOSCOPIC ULTRASONOGRAPHY ; ESOPHAGOGASTRIC JUNCTION ; TUMOR HETEROGENEITY ; 5-YEAR SURVIVAL ; ADENOCARCINOMA ; CARCINOMA ; CHEMOTHERAPY ; TEXTURE |
| Indexed By | SCI |
| Language | 英语 |
| Funding Organization | National 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 Area | Oncology |
| WOS Subject | Oncology |
| WOS ID | WOS:000433287500030 |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/22044 |
| Collection | 中国科学院分子影像重点实验室 |
| Affiliation | 1.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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