ArticleBioMed research international2021
Imaging Tool for Predicting Renal Clear Cell Carcinoma Fuhrman Grade: Comparing R.E.N.A.L. Nephrometry Score and CT Texture Analysis.
Article in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 11 citations in OpenAlex.
- Radiomic model versus R.E.N.A.L. nephrometry score for predicting the likelihood of undergoing partial nephrectomy in clear cell renal cell carcinoma.Frontiers in urology · 2026Article
- CT-based AI score associates with perioperative outcomes in nephron-sparing surgery for renal cell carcinoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Predictive value of a constructed artificial neural network model for microvascular invasion in hepatocellular carcinoma: A retrospective study.World journal of gastrointestinal oncology · 2025Article
- Treatment of fat-poor renal angiomyolipoma with ectopic blood supply by fluorescent laparoscopy: A case report and review of literature.World journal of clinical oncology · 2024Article
- Application of texture signatures based on multiparameter-magnetic resonance imaging for predicting microvascular invasion in hepatocellular carcinoma: Retrospective study.World journal of gastrointestinal oncology · 2024Article
- Prediction of Fuhrman nuclear grade for clear cell renal carcinoma by a multi-information fusion model that incorporates CT-based features of tumor and serum tumor associated material.Journal of cancer research and clinical oncology · 2023Article
- Pathological diagnostic nomograms for predicting malignant histology and unfavorable pathology in patients with endophytic renal tumor.Frontiers in oncology · 2022Article
- Construction of a 12-Gene Prognostic Risk Model and Tumor Immune Microenvironment Analysis Based on the Clear Cell Renal Cell Carcinoma Model.Cancer control : journal of the Moffitt Cancer CenterArticle
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundClear cell renal cell carcinoma (ccRCC) is the most common renal malignant tumor. Preoperative imaging boasts advantages in diagnosing and choosing treatment methods for ccRCC. PURPOSE: This study is aimed at building models based on R.E.N.A.L. nephrometry score (RNS) and CT texture analysis (CTTA) to estimate the Fuhrman grade of ccRCC and comparing the advantages and disadvantages of the two models. MATERIALS AND
methods143 patients with pathologically confirmed ccRCC were enrolled. All patients were stratified into Fuhrman low-grade and high-grade groups with complete CT data and R.E.N.A.L. nephrometry scores. CTTA features were extracted from the ROI delineated at the largest tumor level, and RNS and CTTA features were included in the logistic regression model, respectively.
resultsRNS model constructed based on multivariate logistic regression analysis showed that 3 pts for
conclusionsR.E.N.A.L. nephrometry score has a certain provocative effect on the Fuhrman pathological grading of ccRCC. As a potential emerging technology, CTTA is expected to replace R.E.N.A.L. nephrometry score in evaluating patients' Fuhrman classification, and this approach might become an available method for assisting clinicians in choosing appropriate operation.
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