Multiphase CT radiomics nomogram for preoperatively predicting the WHO/ISUP nuclear grade of small (< 4 cm) clear cell renal cell carcinoma
Abstract Background Small (< 4 cm) clear cell renal cell carcinoma (ccRCC) is the most common type of small renal cancer and its prognosis is poor. However, conventional radiological characteristics obtained by computed tomography (CT) are not sufficient to predict the nuclear grade of small ccRC...
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BMC
2023-10-01
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| Series: | BMC Cancer |
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| Online Access: | https://doi.org/10.1186/s12885-023-11454-5 |
| _version_ | 1827710471160987648 |
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| author | Yankun Gao Xia Wang Xiaoying Zhao Chao Zhu Cuiping Li Jianying Li Xingwang Wu |
| author_facet | Yankun Gao Xia Wang Xiaoying Zhao Chao Zhu Cuiping Li Jianying Li Xingwang Wu |
| author_sort | Yankun Gao |
| collection | DOAJ |
| description | Abstract Background Small (< 4 cm) clear cell renal cell carcinoma (ccRCC) is the most common type of small renal cancer and its prognosis is poor. However, conventional radiological characteristics obtained by computed tomography (CT) are not sufficient to predict the nuclear grade of small ccRCC before surgery. Methods A total of 113 patients with histologically confirmed ccRCC were randomly assigned to the training set (n = 67) and the testing set (n = 46). The baseline and CT imaging data of the patients were evaluated statistically to develop a clinical model. A radiomics model was created, and the radiomics score (Rad-score) was calculated by extracting radiomics features from the CT images. Then, a clinical radiomics nomogram was developed using multivariate logistic regression analysis by combining the Rad-score and critical clinical characteristics. The receiver operating characteristic (ROC) curve was used to evaluate the discrimination of small ccRCC in both the training and testing sets. Results The radiomics model was constructed using six features obtained from the CT images. The shape and relative enhancement value of the nephrographic phase (REV of the NP) were found to be independent risk factors in the clinical model. The area under the curve (AUC) values for the training and testing sets for the clinical radiomics nomogram were 0.940 and 0.902, respectively. Decision curve analysis (DCA) revealed that the radiomics nomogram model was a better predictor, with the highest degree of coincidence. Conclusion The CT-based radiomics nomogram has the potential to be a noninvasive and preoperative method for predicting the WHO/ISUP grade of small ccRCC. |
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| institution | Directory Open Access Journal |
| issn | 1471-2407 |
| language | English |
| last_indexed | 2024-03-10T17:39:35Z |
| publishDate | 2023-10-01 |
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| series | BMC Cancer |
| spelling | doaj.art-45dfe92f041b4783aef1e3fe3e25733e2023-11-20T09:43:54ZengBMCBMC Cancer1471-24072023-10-0123111210.1186/s12885-023-11454-5Multiphase CT radiomics nomogram for preoperatively predicting the WHO/ISUP nuclear grade of small (< 4 cm) clear cell renal cell carcinomaYankun Gao0Xia Wang1Xiaoying Zhao2Chao Zhu3Cuiping Li4Jianying Li5Xingwang Wu6Department of Radiology, The First Affiliated Hospital of Anhui Medical UniversityDepartment of Radiology, The First Affiliated Hospital of Anhui Medical UniversityDepartment of Radiology, The First Affiliated Hospital of Anhui Medical UniversityDepartment of Radiology, The First Affiliated Hospital of Anhui Medical UniversityDepartment of Radiology, The First Affiliated Hospital of Anhui Medical UniversityCT Research Center, GE Healthcare ChinaDepartment of Radiology, The First Affiliated Hospital of Anhui Medical UniversityAbstract Background Small (< 4 cm) clear cell renal cell carcinoma (ccRCC) is the most common type of small renal cancer and its prognosis is poor. However, conventional radiological characteristics obtained by computed tomography (CT) are not sufficient to predict the nuclear grade of small ccRCC before surgery. Methods A total of 113 patients with histologically confirmed ccRCC were randomly assigned to the training set (n = 67) and the testing set (n = 46). The baseline and CT imaging data of the patients were evaluated statistically to develop a clinical model. A radiomics model was created, and the radiomics score (Rad-score) was calculated by extracting radiomics features from the CT images. Then, a clinical radiomics nomogram was developed using multivariate logistic regression analysis by combining the Rad-score and critical clinical characteristics. The receiver operating characteristic (ROC) curve was used to evaluate the discrimination of small ccRCC in both the training and testing sets. Results The radiomics model was constructed using six features obtained from the CT images. The shape and relative enhancement value of the nephrographic phase (REV of the NP) were found to be independent risk factors in the clinical model. The area under the curve (AUC) values for the training and testing sets for the clinical radiomics nomogram were 0.940 and 0.902, respectively. Decision curve analysis (DCA) revealed that the radiomics nomogram model was a better predictor, with the highest degree of coincidence. Conclusion The CT-based radiomics nomogram has the potential to be a noninvasive and preoperative method for predicting the WHO/ISUP grade of small ccRCC.https://doi.org/10.1186/s12885-023-11454-5Clear cell renal cell carcinomaSmall renal massRadiomics nomogramComputed tomographyWHO/ISUP grade |
| spellingShingle | Yankun Gao Xia Wang Xiaoying Zhao Chao Zhu Cuiping Li Jianying Li Xingwang Wu Multiphase CT radiomics nomogram for preoperatively predicting the WHO/ISUP nuclear grade of small (< 4 cm) clear cell renal cell carcinoma BMC Cancer Clear cell renal cell carcinoma Small renal mass Radiomics nomogram Computed tomography WHO/ISUP grade |
| title | Multiphase CT radiomics nomogram for preoperatively predicting the WHO/ISUP nuclear grade of small (< 4 cm) clear cell renal cell carcinoma |
| title_full | Multiphase CT radiomics nomogram for preoperatively predicting the WHO/ISUP nuclear grade of small (< 4 cm) clear cell renal cell carcinoma |
| title_fullStr | Multiphase CT radiomics nomogram for preoperatively predicting the WHO/ISUP nuclear grade of small (< 4 cm) clear cell renal cell carcinoma |
| title_full_unstemmed | Multiphase CT radiomics nomogram for preoperatively predicting the WHO/ISUP nuclear grade of small (< 4 cm) clear cell renal cell carcinoma |
| title_short | Multiphase CT radiomics nomogram for preoperatively predicting the WHO/ISUP nuclear grade of small (< 4 cm) clear cell renal cell carcinoma |
| title_sort | multiphase ct radiomics nomogram for preoperatively predicting the who isup nuclear grade of small 4 cm clear cell renal cell carcinoma |
| topic | Clear cell renal cell carcinoma Small renal mass Radiomics nomogram Computed tomography WHO/ISUP grade |
| url | https://doi.org/10.1186/s12885-023-11454-5 |
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