CT Radiomics Nomogram Prediction for Tumor Deposits and Prognosis in Colorectal Cancer
Objective: To establish computed tomography (CT) radiomics nomogram for preoperative prediction of tumor deposits (TD) and recurrence-free survival (RFS) in patients with colorectal cancer (CRC). Methods: A retrospective study was conducted on 321 CRC patients confirmed by surgical pathology. The pa...
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Editorial Office of Computerized Tomography Theory and Application
2025-07-01
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| Series: | CT Lilun yu yingyong yanjiu |
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| Online Access: | https://www.cttacn.org.cn/cn/article/doi/10.15953/j.ctta.2024.055 |
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| author | Manman LI Yigang FU Yong XIAO Wang CHEN Feng FENG Guodong XU |
| author_facet | Manman LI Yigang FU Yong XIAO Wang CHEN Feng FENG Guodong XU |
| author_sort | Manman LI |
| collection | DOAJ |
| description | Objective: To establish computed tomography (CT) radiomics nomogram for preoperative prediction of tumor deposits (TD) and recurrence-free survival (RFS) in patients with colorectal cancer (CRC). Methods: A retrospective study was conducted on 321 CRC patients confirmed by surgical pathology. The patients’ data were divided were divided into a training set and a validation set at a ratio of 6:4, respectively. Radiomics features based on the primary tumor site were extracted from portal venous phase CT images, and the least absolute shrinkage and selection operator (LASSO) algorithm was employed to select radiomics features associated with tumor deposits (TD). The LASSO regression algorithm was applied to choose radiomics features related to TD. A clinical-radiomics nomogram was developed based on the selected radiomics features and the most predictive clinical factors. Univariate and multivariate Cox regression analyses identified independent risk factors for a 3-year relapse free survive (RFS). Results: The radiomics model achieved an area under the curve (AUC) of 0.80 in the training set and 0.79 in the validation set. By integrating radiomics features with clinical predictors (CEA, CA199, and CT-reported lymph node status), a nomogram was developed for the preoperative prediction of TD. The nomogram achieved an AUC of 0.85 in the training and validation sets. Furthermore, TD predicted by the nomogram was an independent risk factor for RFS, with poorer RFS observed in the TD-positive group compared to the TD-negative group. Conclusion: CT radiomics nomogram can effectively preoperatively predict TD and prognosis in CRC patients. |
| format | Article |
| id | doaj-art-0de45ca0887d4c7c9e3816dd1d31943a |
| institution | Kabale University |
| issn | 1004-4140 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Editorial Office of Computerized Tomography Theory and Application |
| record_format | Article |
| series | CT Lilun yu yingyong yanjiu |
| spelling | doaj-art-0de45ca0887d4c7c9e3816dd1d31943a2025-08-20T03:49:46ZengEditorial Office of Computerized Tomography Theory and ApplicationCT Lilun yu yingyong yanjiu1004-41402025-07-0134469470210.15953/j.ctta.2024.0552024.055CT Radiomics Nomogram Prediction for Tumor Deposits and Prognosis in Colorectal CancerManman LI0Yigang FU1Yong XIAO2Wang CHEN3Feng FENG4Guodong XU5Department of Radiology, the Yancheng Clinical College of Xuzhou Medical University (the First People’s Hospital of Yancheng), Yancheng 224000, ChinaDepartment of Radiology, the Yancheng Clinical College of Xuzhou Medical University (the First People’s Hospital of Yancheng), Yancheng 224000, ChinaDepartment of Radiology, the Yancheng Clinical College of Xuzhou Medical University (the First People’s Hospital of Yancheng), Yancheng 224000, ChinaDepartment of Radiology, the Yancheng Clinical College of Xuzhou Medical University (the First People’s Hospital of Yancheng), Yancheng 224000, ChinaDepartment of Radiology, Affiliated Tumor Hospital of Nantong University, Nantong 226001, ChinaDepartment of Radiology, the Yancheng Clinical College of Xuzhou Medical University (the First People’s Hospital of Yancheng), Yancheng 224000, ChinaObjective: To establish computed tomography (CT) radiomics nomogram for preoperative prediction of tumor deposits (TD) and recurrence-free survival (RFS) in patients with colorectal cancer (CRC). Methods: A retrospective study was conducted on 321 CRC patients confirmed by surgical pathology. The patients’ data were divided were divided into a training set and a validation set at a ratio of 6:4, respectively. Radiomics features based on the primary tumor site were extracted from portal venous phase CT images, and the least absolute shrinkage and selection operator (LASSO) algorithm was employed to select radiomics features associated with tumor deposits (TD). The LASSO regression algorithm was applied to choose radiomics features related to TD. A clinical-radiomics nomogram was developed based on the selected radiomics features and the most predictive clinical factors. Univariate and multivariate Cox regression analyses identified independent risk factors for a 3-year relapse free survive (RFS). Results: The radiomics model achieved an area under the curve (AUC) of 0.80 in the training set and 0.79 in the validation set. By integrating radiomics features with clinical predictors (CEA, CA199, and CT-reported lymph node status), a nomogram was developed for the preoperative prediction of TD. The nomogram achieved an AUC of 0.85 in the training and validation sets. Furthermore, TD predicted by the nomogram was an independent risk factor for RFS, with poorer RFS observed in the TD-positive group compared to the TD-negative group. Conclusion: CT radiomics nomogram can effectively preoperatively predict TD and prognosis in CRC patients.https://www.cttacn.org.cn/cn/article/doi/10.15953/j.ctta.2024.055tomographyx-ray computedradiomicscolorectal neoplasmstumor deposits |
| spellingShingle | Manman LI Yigang FU Yong XIAO Wang CHEN Feng FENG Guodong XU CT Radiomics Nomogram Prediction for Tumor Deposits and Prognosis in Colorectal Cancer CT Lilun yu yingyong yanjiu tomography x-ray computed radiomics colorectal neoplasms tumor deposits |
| title | CT Radiomics Nomogram Prediction for Tumor Deposits and Prognosis in Colorectal Cancer |
| title_full | CT Radiomics Nomogram Prediction for Tumor Deposits and Prognosis in Colorectal Cancer |
| title_fullStr | CT Radiomics Nomogram Prediction for Tumor Deposits and Prognosis in Colorectal Cancer |
| title_full_unstemmed | CT Radiomics Nomogram Prediction for Tumor Deposits and Prognosis in Colorectal Cancer |
| title_short | CT Radiomics Nomogram Prediction for Tumor Deposits and Prognosis in Colorectal Cancer |
| title_sort | ct radiomics nomogram prediction for tumor deposits and prognosis in colorectal cancer |
| topic | tomography x-ray computed radiomics colorectal neoplasms tumor deposits |
| url | https://www.cttacn.org.cn/cn/article/doi/10.15953/j.ctta.2024.055 |
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