The value of radiomics based on 2-[18 F]FDG PET/CT in predicting WHO/ISUP grade of clear cell renal cell carcinoma

The aim is to develop and validate radiomics based on 2-[18F]fluoro-D-glucose positron emission tomography/computed tomography (2-[18F]FDG PET/CT) parameters for predicting the World Health Organization/International Society of Urological Pathology (WHO/ISUP) grade of clear cell renal cell carcinoma (ccRCC). A total of 209 patients with 214 lesions, who underwent 2-[18F]FDG PET/CT scans between December 2016 to December 2023, were included in our study. All ccRCC lesions were categorized into low grade (WHO/ISUP grade I-II) and high grade (WHO/ISUP grade III-IV). The lesions were allocated into a training group and a testing group in a ratio of 7:3. The radiomics features were extracted by a serious of maximum standardized uptake value (SUVmax) thresholds (0,2.5%,25%,40%) with the utilization of the minimum redundancy and maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) regression algorithm. The clinical, radiomics and combined models were constructed. The receiver operating characteristic (ROC) curve, decision curve and calibration curves were plotted to assess the predicting performance. The area under curve (AUC) of PET-0, PET-2.5%, PET-25%, PET-40% model in the training group were 0.881(95% CI: 0.822–0.940),0.883(95% CI: 0.825–0.942),0.889(95% CI: 0.831–0.946),0.887(95% CI: 0.826–0.948); and 0.878(95% CI: 0.777–0.978),0.876(95% CI: 0.776–0.977),0.871(95% CI: 0.769–0.972),0.882(95% CI: 0.786–0.979) in the testing group. Due to perfect prediction and verification performance, the volume of interest (VOI) from PET images with SUVmax threshold of 40% were selected to construct the radiomics model and combined model. The AUC of the clinical model and radiomics model was 0.859 (sensitivity = 0.846, specificity = 0.747) and 0.909 (sensitivity = 0.808, specificity = 0.751) in the training group, respectively; 0.882 (sensitivity = 0.857, specificity = 0.857) and 0.901 (sensitivity = 0.905, specificity = 0.833) in the testing group, respectively. In combined models, the AUC was 0.916, the sensitivity was 0.923 and the specificity was 0.808 in the training group; the AUC was 0.916, the sensitivity was 0.881 and the specificity was 0.792 in the training group. Radiomics based on 2-[18F]FDG PET/CT can be helpful to predict WHO/ISUP grade of ccRCC.

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Journal
EJNMMI Research
Published
2024-11-21
DOI
https://doi.org/10.1186/s13550-024-01182-7
Citations
5
Primary Topic
Renal cell carcinoma treatment
Type
article
Field-Weighted Citation Impact
2.09
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article

The value of radiomics based on 2-[18 F]FDG PET/CT in predicting WHO/ISUP grade of clear cell renal cell carcinoma

Jianzhong Cui, Yue Pan, Baixuan Xu, Xiaodan Xu et al.
5 citations
EJNMMI Research
Renal cell carcinoma treatment
2.09
article

The value of radiomics based on 2-[18 F]FDG PET/CT in predicting WHO/ISUP grade of clear cell renal cell carcinoma

Jianzhong Cui, Yue Pan, Baixuan Xu, Xiaodan Xu, Yun Han, Can Li, Jingfeng Zhang, Yanmei Wang, Guanyun Wang
article en
5 citations

Abstract

The aim is to develop and validate radiomics based on 2-[18F]fluoro-D-glucose positron emission tomography/computed tomography (2-[18F]FDG PET/CT) parameters for predicting the World Health Organization/International Society of Urological Pathology (WHO/ISUP) grade of clear cell renal cell carcinoma (ccRCC). A total of 209 patients with 214 lesions, who underwent 2-[18F]FDG PET/CT scans between December 2016 to December 2023, were included in our study. All ccRCC lesions were categorized into low grade (WHO/ISUP grade I-II) and high grade (WHO/ISUP grade III-IV). The lesions were allocated into a training group and a testing group in a ratio of 7:3. The radiomics features were extracted by a serious of maximum standardized uptake value (SUVmax) thresholds (0,2.5%,25%,40%) with the utilization of the minimum redundancy and maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) regression algorithm. The clinical, radiomics and combined models were constructed. The receiver operating characteristic (ROC) curve, decision curve and calibration curves were plotted to assess the predicting performance. The area under curve (AUC) of PET-0, PET-2.5%, PET-25%, PET-40% model in the training group were 0.881(95% CI: 0.822–0.940),0.883(95% CI: 0.825–0.942),0.889(95% CI: 0.831–0.946),0.887(95% CI: 0.826–0.948); and 0.878(95% CI: 0.777–0.978),0.876(95% CI: 0.776–0.977),0.871(95% CI: 0.769–0.972),0.882(95% CI: 0.786–0.979) in the testing group. Due to perfect prediction and verification performance, the volume of interest (VOI) from PET images with SUVmax threshold of 40% were selected to construct the radiomics model and combined model. The AUC of the clinical model and radiomics model was 0.859 (sensitivity = 0.846, specificity = 0.747) and 0.909 (sensitivity = 0.808, specificity = 0.751) in the training group, respectively; 0.882 (sensitivity = 0.857, specificity = 0.857) and 0.901 (sensitivity = 0.905, specificity = 0.833) in the testing group, respectively. In combined models, the AUC was 0.916, the sensitivity was 0.923 and the specificity was 0.808 in the training group; the AUC was 0.916, the sensitivity was 0.881 and the specificity was 0.792 in the training group. Radiomics based on 2-[18F]FDG PET/CT can be helpful to predict WHO/ISUP grade of ccRCC.

EJNMMI ResearchVol. 14(1)
Capital Medical University (CN), Chinese PLA General Hospital (CN), Beijing Friendship Hospital (CN)
Good health and well-being
Openalex Percentile: Top 12%
Renal cell carcinoma treatment
2.09
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