Whole-liver enhanced CT radiomics analysis to predict metachronous liver metastases after rectal cancer surgery
Abstract Background To develop a radiomics model based on pretreatment whole-liver portal venous phase (PVP) contrast-enhanced CT (CE-CT) images for predicting metachronous liver metastases (MLM) within 24 months after rectal cancer (RC) surgery. Methods This study retrospectively analyzed 112 RC pa...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-09-01
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| Series: | Cancer Imaging |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40644-022-00485-z |
| _version_ | 1798036466682560512 |
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| author | Meng Liang Xiaohong Ma Leyao Wang Dengfeng Li Sicong Wang Hongmei Zhang Xinming Zhao |
| author_facet | Meng Liang Xiaohong Ma Leyao Wang Dengfeng Li Sicong Wang Hongmei Zhang Xinming Zhao |
| author_sort | Meng Liang |
| collection | DOAJ |
| description | Abstract Background To develop a radiomics model based on pretreatment whole-liver portal venous phase (PVP) contrast-enhanced CT (CE-CT) images for predicting metachronous liver metastases (MLM) within 24 months after rectal cancer (RC) surgery. Methods This study retrospectively analyzed 112 RC patients without preoperative liver metastases who underwent rectal surgery between January 2015 and December 2017 at our institution. Volume of interest (VOI) segmentation of the whole-liver was performed on the PVP CE-CT images. All 1316 radiomics features were extracted automatically. The maximum-relevance and minimum-redundancy and least absolute shrinkage and selection operator methods were used for features selection and radiomics signature constructing. Three models based on radiomics features (radiomics model), clinical features (clinical model), and radiomics combined with clinical features (combined model) were built by multivariable logistic regression analysis. Receiver operating characteristic (ROC) curves were used to assess the diagnostic performance of models, and calibration curve and the decision curve analysis were performed to evaluate the clinical application value. Results In total, 52 patients in the MLM group and 60 patients in the non-MLM group were enrolled in this study. The radscore was built using 16 selected features and the corresponding coefficients. Both the radiomics model and the combined model showed higher diagnostic performance than clinical model (AUCs of training set: radiomics model 0.84 (95% CI, 0.76–0.93), clinical model 0.65 (95% CI, 0.55–0.75), combined model 0.85 (95% CI, 0.77–0.94); AUCs of validation set: radiomics model 0.84 (95% CI, 0.70–0.98), clinical model 0.58 (95% CI, 0.40–0.76), combined model 0.85 (95% CI, 0.71–0.99)). The calibration curves showed great consistency between the predicted value and actual event probability. The DCA showed that both the radiomics and combined models could add a net benefit on a large scale. Conclusions The radiomics model based on preoperative whole-liver PVP CE-CT could predict MLM within 24 months after RC surgery. Clinical features could not significantly improve the prediction efficiency of the radiomics model. |
| first_indexed | 2024-04-11T21:13:19Z |
| format | Article |
| id | doaj.art-d07bd5bece074161bf0b3c6303ea0bdc |
| institution | Directory Open Access Journal |
| issn | 1470-7330 |
| language | English |
| last_indexed | 2024-04-11T21:13:19Z |
| publishDate | 2022-09-01 |
| publisher | BMC |
| record_format | Article |
| series | Cancer Imaging |
| spelling | doaj.art-d07bd5bece074161bf0b3c6303ea0bdc2022-12-22T04:02:57ZengBMCCancer Imaging1470-73302022-09-0122111210.1186/s40644-022-00485-zWhole-liver enhanced CT radiomics analysis to predict metachronous liver metastases after rectal cancer surgeryMeng Liang0Xiaohong Ma1Leyao Wang2Dengfeng Li3Sicong Wang4Hongmei Zhang5Xinming Zhao6Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeGE Healthcare (China)Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeAbstract Background To develop a radiomics model based on pretreatment whole-liver portal venous phase (PVP) contrast-enhanced CT (CE-CT) images for predicting metachronous liver metastases (MLM) within 24 months after rectal cancer (RC) surgery. Methods This study retrospectively analyzed 112 RC patients without preoperative liver metastases who underwent rectal surgery between January 2015 and December 2017 at our institution. Volume of interest (VOI) segmentation of the whole-liver was performed on the PVP CE-CT images. All 1316 radiomics features were extracted automatically. The maximum-relevance and minimum-redundancy and least absolute shrinkage and selection operator methods were used for features selection and radiomics signature constructing. Three models based on radiomics features (radiomics model), clinical features (clinical model), and radiomics combined with clinical features (combined model) were built by multivariable logistic regression analysis. Receiver operating characteristic (ROC) curves were used to assess the diagnostic performance of models, and calibration curve and the decision curve analysis were performed to evaluate the clinical application value. Results In total, 52 patients in the MLM group and 60 patients in the non-MLM group were enrolled in this study. The radscore was built using 16 selected features and the corresponding coefficients. Both the radiomics model and the combined model showed higher diagnostic performance than clinical model (AUCs of training set: radiomics model 0.84 (95% CI, 0.76–0.93), clinical model 0.65 (95% CI, 0.55–0.75), combined model 0.85 (95% CI, 0.77–0.94); AUCs of validation set: radiomics model 0.84 (95% CI, 0.70–0.98), clinical model 0.58 (95% CI, 0.40–0.76), combined model 0.85 (95% CI, 0.71–0.99)). The calibration curves showed great consistency between the predicted value and actual event probability. The DCA showed that both the radiomics and combined models could add a net benefit on a large scale. Conclusions The radiomics model based on preoperative whole-liver PVP CE-CT could predict MLM within 24 months after RC surgery. Clinical features could not significantly improve the prediction efficiency of the radiomics model.https://doi.org/10.1186/s40644-022-00485-zRectal cancerRadiomicsLiver metastasesComputed tomography |
| spellingShingle | Meng Liang Xiaohong Ma Leyao Wang Dengfeng Li Sicong Wang Hongmei Zhang Xinming Zhao Whole-liver enhanced CT radiomics analysis to predict metachronous liver metastases after rectal cancer surgery Cancer Imaging Rectal cancer Radiomics Liver metastases Computed tomography |
| title | Whole-liver enhanced CT radiomics analysis to predict metachronous liver metastases after rectal cancer surgery |
| title_full | Whole-liver enhanced CT radiomics analysis to predict metachronous liver metastases after rectal cancer surgery |
| title_fullStr | Whole-liver enhanced CT radiomics analysis to predict metachronous liver metastases after rectal cancer surgery |
| title_full_unstemmed | Whole-liver enhanced CT radiomics analysis to predict metachronous liver metastases after rectal cancer surgery |
| title_short | Whole-liver enhanced CT radiomics analysis to predict metachronous liver metastases after rectal cancer surgery |
| title_sort | whole liver enhanced ct radiomics analysis to predict metachronous liver metastases after rectal cancer surgery |
| topic | Rectal cancer Radiomics Liver metastases Computed tomography |
| url | https://doi.org/10.1186/s40644-022-00485-z |
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