Radiomics Analysis of Contrast-Enhanced CT Predicts Survival in Clear Cell Renal Cell Carcinoma
PurposeTo develop and validate the radiomics nomogram that combines clinical factors and radiomics features to estimate overall survival (OS) in patients with clear cell renal cell carcinoma (ccRCC), and assess the incremental value of radiomics for OS estimation.Materials and MethodsOne hundred nin...
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doaj-15571f8a556c48bc93177764d25525042021-06-25T07:38:23ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2021-06-011110.3389/fonc.2021.671420671420Radiomics Analysis of Contrast-Enhanced CT Predicts Survival in Clear Cell Renal Cell CarcinomaLei Yan0Guangjie Yang1Jingjing Cui2Wenjie Miao3Yangyang Wang4Yujun Zhao5Ning Wang6Aidi Gong7Na Guo8Pei Nie9Zhenguang Wang10Department of Positron Emission Tomography-Computed Tomography (PET-CT) Center, The Affiliated Hospital of Qingdao University, Qingdao, ChinaDepartment of Positron Emission Tomography-Computed Tomography (PET-CT) Center, The Affiliated Hospital of Qingdao University, Qingdao, ChinaScientific Research Department, Huiying Medical Technology Co., Ltd., Beijing, ChinaDepartment of Positron Emission Tomography-Computed Tomography (PET-CT) Center, The Affiliated Hospital of Qingdao University, Qingdao, ChinaDepartment of Positron Emission Tomography-Computed Tomography (PET-CT) Center, The Affiliated Hospital of Qingdao University, Qingdao, ChinaDepartment of Positron Emission Tomography-Computed Tomography (PET-CT) Center, The Affiliated Hospital of Qingdao University, Qingdao, ChinaDepartment of Radiology, Shandong Provincial Hospital, Jinan, ChinaDepartment of Positron Emission Tomography-Computed Tomography (PET-CT) Center, The Affiliated Hospital of Qingdao University, Qingdao, ChinaScientific Research Department, Huiying Medical Technology Co., Ltd., Beijing, ChinaDepartment of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, ChinaDepartment of Positron Emission Tomography-Computed Tomography (PET-CT) Center, The Affiliated Hospital of Qingdao University, Qingdao, ChinaPurposeTo develop and validate the radiomics nomogram that combines clinical factors and radiomics features to estimate overall survival (OS) in patients with clear cell renal cell carcinoma (ccRCC), and assess the incremental value of radiomics for OS estimation.Materials and MethodsOne hundred ninety-four ccRCC cases were included in the training cohort and 188 ccRCC patients from another hospital as the test cohort. Three-dimensional region-of-interest segmentation was manually segmented on multiphasic contrast-enhanced abdominal CT images. Radiomics score (Rad-score) was calculated from a formula generated via least absolute shrinkage and selection operator (LASSO) Cox regression, after which the association between the Rad-score and OS was explored. The radiomics nomogram (clinical factors + Rad-score) was developed to demonstrate the incremental value of the Rad-score to the clinical nomogram for individualized OS estimation, which was then evaluated in relation to calibration and discrimination.ResultsRad-score, calculated using a linear combination of the 11 screened features multiplied by their respective LASSO Cox coefficients, was significantly associated with OS. Calibration curves showed good agreement between the OS predicted by the nomograms and observed outcomes. The radiomics nomogram presented higher discrimination capability compared to clinical nomogram in the training (C-index: 0.884; 95% CI: 0.808–0.940 vs. 0.803; 95% CI: 0.705–0.899, P < 0.05) and test cohorts (C-index: 0.859; 95% CI: 0.800–0.921 vs. 0.846; 95% CI: 0.777–0.915, P < 0.05).ConclusionsThe radiomics nomogram may be used for predicting OS in patients with ccRCC, and radiomics is useful to assist quantitative and personalized treatment.https://www.frontiersin.org/articles/10.3389/fonc.2021.671420/fullradiomicsRad-scorenomogramclear cell renal cell carcinomaoverall survival |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lei Yan Guangjie Yang Jingjing Cui Wenjie Miao Yangyang Wang Yujun Zhao Ning Wang Aidi Gong Na Guo Pei Nie Zhenguang Wang |
spellingShingle |
Lei Yan Guangjie Yang Jingjing Cui Wenjie Miao Yangyang Wang Yujun Zhao Ning Wang Aidi Gong Na Guo Pei Nie Zhenguang Wang Radiomics Analysis of Contrast-Enhanced CT Predicts Survival in Clear Cell Renal Cell Carcinoma Frontiers in Oncology radiomics Rad-score nomogram clear cell renal cell carcinoma overall survival |
author_facet |
Lei Yan Guangjie Yang Jingjing Cui Wenjie Miao Yangyang Wang Yujun Zhao Ning Wang Aidi Gong Na Guo Pei Nie Zhenguang Wang |
author_sort |
Lei Yan |
title |
Radiomics Analysis of Contrast-Enhanced CT Predicts Survival in Clear Cell Renal Cell Carcinoma |
title_short |
Radiomics Analysis of Contrast-Enhanced CT Predicts Survival in Clear Cell Renal Cell Carcinoma |
title_full |
Radiomics Analysis of Contrast-Enhanced CT Predicts Survival in Clear Cell Renal Cell Carcinoma |
title_fullStr |
Radiomics Analysis of Contrast-Enhanced CT Predicts Survival in Clear Cell Renal Cell Carcinoma |
title_full_unstemmed |
Radiomics Analysis of Contrast-Enhanced CT Predicts Survival in Clear Cell Renal Cell Carcinoma |
title_sort |
radiomics analysis of contrast-enhanced ct predicts survival in clear cell renal cell carcinoma |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Oncology |
issn |
2234-943X |
publishDate |
2021-06-01 |
description |
PurposeTo develop and validate the radiomics nomogram that combines clinical factors and radiomics features to estimate overall survival (OS) in patients with clear cell renal cell carcinoma (ccRCC), and assess the incremental value of radiomics for OS estimation.Materials and MethodsOne hundred ninety-four ccRCC cases were included in the training cohort and 188 ccRCC patients from another hospital as the test cohort. Three-dimensional region-of-interest segmentation was manually segmented on multiphasic contrast-enhanced abdominal CT images. Radiomics score (Rad-score) was calculated from a formula generated via least absolute shrinkage and selection operator (LASSO) Cox regression, after which the association between the Rad-score and OS was explored. The radiomics nomogram (clinical factors + Rad-score) was developed to demonstrate the incremental value of the Rad-score to the clinical nomogram for individualized OS estimation, which was then evaluated in relation to calibration and discrimination.ResultsRad-score, calculated using a linear combination of the 11 screened features multiplied by their respective LASSO Cox coefficients, was significantly associated with OS. Calibration curves showed good agreement between the OS predicted by the nomograms and observed outcomes. The radiomics nomogram presented higher discrimination capability compared to clinical nomogram in the training (C-index: 0.884; 95% CI: 0.808–0.940 vs. 0.803; 95% CI: 0.705–0.899, P < 0.05) and test cohorts (C-index: 0.859; 95% CI: 0.800–0.921 vs. 0.846; 95% CI: 0.777–0.915, P < 0.05).ConclusionsThe radiomics nomogram may be used for predicting OS in patients with ccRCC, and radiomics is useful to assist quantitative and personalized treatment. |
topic |
radiomics Rad-score nomogram clear cell renal cell carcinoma overall survival |
url |
https://www.frontiersin.org/articles/10.3389/fonc.2021.671420/full |
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