ArticleThe British journal of radiology2020
Prediction models for clear cell renal cell carcinoma ISUP/WHO grade: comparison between CT radiomics and conventional contrast-enhanced CT.
Article in The British journal of radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Non-invasive prediction of nuclear grade in renal cell carcinoma using CT-Based radiomics: a systematic review and meta-analysis.Abdominal radiology (New York) · 2026Pooled it
- Biphasic CT clustering-based habitat radiomics predicts WHO/ISUP nuclear grade in clear cell renal cell carcinoma.Abdominal radiology (New York) · 2026Article
- Development and validation of a CT algorithm based on intratumoral necrosis and tumor morphology to predict the nuclear grade of small (2-4 cm) solid clear cell renal cell carcinoma.BMC medical imaging · 2025Article
- Predicting Renal Cell Carcinoma Subtypes and Fuhrman Grading Using Multiphasic CT-Based Texture Analysis and Machine Learning Techniques.The Indian journal of radiology & imaging · 2025Article
- Development and validation of a CT based radiomics nomogram for preoperative prediction of ISUP/WHO grading in renal clear cell carcinoma.Abdominal radiology (New York) · 2025Article
- Impact of multi-parameter images obtained from dual-energy CT on radiomics to predict pathological grading of bladder urothelial carcinoma.Abdominal radiology (New York) · 2024Article
- Multiparameter computed tomography (CT) radiomics signature fusion-based model for the preoperative prediction of clear cell renal cell carcinoma nuclear grade: a multicenter development and external validation study.Quantitative imaging in medicine and surgery · 2024Article
- Radiomics predict the WHO/ISUP nuclear grade and survival in clear cell renal cell carcinoma.Insights into imaging · 2024Article
- Associations between contrast-enhanced ultrasound features and WHO/ISUP grade of clear cell renal cell carcinoma: a retrospective study.International urology and nephrology · 2024Article
- Radiomics vs radiologist in bladder and renal cancer. Results from a systematic review.Central European journal of urology · 2023Review
- Performance of CT radiomics in predicting the overall survival of patients with stage III clear cell renal carcinoma after radical nephrectomy.La Radiologia medica · 2022Article
- Novel Imaging Methods for Renal Mass Characterization: A Collaborative Review.European urology · 2022Review
- Circ_000829 Plays an Anticancer Role in Renal Cell Carcinoma by Suppressing SRSF1-Mediated Alternative Splicing of SLC39A14.Oxidative medicine and cellular longevity · 2022Article
- Machine learning-based CT radiomics approach for predicting WHO/ISUP nuclear grade of clear cell renal cell carcinoma: an exploratory and comparative study.Insights into imaging · 2021Article
- A CT-Based Radiomics Nomogram Integrated With Clinic-Radiological Features for Preoperatively Predicting WHO/ISUP Grade of Clear Cell Renal Cell Carcinoma.Frontiers in oncology · 2021Article
- Development and Validation of a Radiomic Nomogram for Predicting the Prognosis of Kidney Renal Clear Cell Carcinoma.Frontiers in oncology · 2021Article
- Preoperative Predicting the WHO/ISUP Nuclear Grade of Clear Cell Renal Cell Carcinoma by Computed Tomography-Based Radiomics Features.Journal of personalized medicine · 2020Article
- Computed Tomography Radiomics for Predicting Pathological Grade of Renal Cell Carcinoma.Frontiers in oncology · 2020Article
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Abstract
objectiveComparing the prediction models for the ISUP/WHO grade of clear cell renal cell carcinoma (ccRCC) based on CT radiomics and conventional contrast-enhanced CT (CECT).
methodsThe corticomedullary phase images of 119 cases of low-grade (I and II) and high-grade (III and IV) ccRCC based on 2016 ISUP/WHO pathological grading criteria were analyzed retrospectively. The patients were randomly divided into training and validation set by stratified sampling according to 7:3 ratio. Prediction models of ccRCC differentiation were constructed using CT radiomics and conventional CECT findings in the training setandwere validated using validation set. The discrimination, calibration, net reclassification index (NRI) and integrated discrimination improvement index (IDI) of the two prediction models were further compared. The decision curve was used to analyze the net benefit of patients under different probability thresholds of the two models.
resultsIn the training set, the C-statistics of radiomics prediction model was statistically higher than that of CECT (
conclusionThe prediction model using CT radiomics in corticomedullary phase is more effective for ccRCC ISUP/WHO grade than conventional CECT. ADVANCES IN KNOWLEDGE: As a non-invasive analysis method, radiomics can predict the ISUP/WHO grade of ccRCC more effectively than traditional enhanced CT.
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