ArticleAbdominal radiology (New York)2021
A CT-based radiomics nomogram for differentiation of small masses (< 4 cm) of renal oncocytoma from clear cell renal cell carcinoma.
Article in Abdominal radiology (New York), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 17 citations in OpenAlex.
- Review
- Radiomics analysis of CT imaging for predicting MIT family translocation renal cell carcinoma: a multicenter retrospective clinical study.BMC cancer · 2026Article
- CT-Based Radiomics in the Characterization of Solid Renal Tumors: A Systematic Review.Cancers · 2026Review
- Artificial intelligence-based segmentation of small renal masses: a multi-center, multi-scanner, multi-sequence study.Abdominal radiology (New York) · 2026Article
- The Loss of Complex I in Renal Oncocytoma Is Associated with Defective Mitophagy Due to Lysosomal Dysfunction.International journal of molecular sciences · 2025Article
- Intratumoral and peritumoral radiomics using multi-phase contrast-enhanced CT for diagnosis of renal oncocytoma and chromophobe renal cell carcinoma: a multicenter retrospective study.Frontiers in oncology · 2025Article
- Radiomics-based machine learning role in differential diagnosis between small renal oncocytoma and clear cells carcinoma on contrast-enhanced CT: A pilot study.European journal of radiology open · 2024Article
- Radiomics analysis based on single phase and different phase combinations of radiomics features from tri-phasic CT to distinguish renal oncocytoma from chromophobe renal cell carcinoma.Abdominal radiology (New York) · 2024Article
- Article
- Role of AI and Radiomic Markers in Early Diagnosis of Renal Cancer and Clinical Outcome Prediction: A Brief Review.Cancers · 2023Review
- Computed Tomography Urography: State of the Art and Beyond.Tomography (Ann Arbor, Mich.) · 2023Review
- Effectiveness of Radiomic ZOT Features in the Automated Discrimination of Oncocytoma from Clear Cell Renal Cancer.Journal of personalized medicine · 2023Article
- A CT-based radiomics nomogram for differentiation of benign and malignant small renal masses (≤4 cm).Translational oncology · 2023Article
- CT differentiation of the oncocytoma and renal cell carcinoma based on peripheral tumor parenchyma and central hypodense area characterisation.BMC medical imaging · 2023Article
- Radiomics vs radiologist in bladder and renal cancer. Results from a systematic review.Central European journal of urology · 2023Review
- Differential Diagnosis of Type 1 and Type 2 Papillary Renal Cell Carcinoma Based on Enhanced CT Radiomics Nomogram.Frontiers in oncology · 2022Article
Corrections and comments
- Commented on byImaging.2022
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeRenal oncocytoma (RO) is the most commonly resected benign renal tumor because of misdiagnosis as renal cell carcinoma. This misdiagnosis is generally owing to overlapping imaging features. This study describes the building of a radiomics nomogram based on clinical data and radiomics signature for the preoperative differentiation of RO from clear cell renal cell carcinoma (ccRCC) on tri-phasic contrast-enhanced CT.
methodsA total of 122 patients (85 in training set and 37 in external validation set) with ROs (n = 46) or ccRCCs (n = 76) were enrolled. Patient characteristics and tri-phasic contrast-enhanced CT imaging features were evaluated to build a clinical factors model. A radiomics signature was constructed by extracting radiomics features from tri-phasic contrast-enhanced CT images and a radiomics score (Rad-score) was calculated. A radiomics nomogram was then built by incorporating the Rad-score and significant clinical factors according to a multivariate logistic regression analysis. The diagnostic performance of the above three models was evaluated in training and validation sets.
resultsCentral stellate area and perirenal fascia thickening were selected to build the clinical factors model. Eleven radiomics features were combined to construct the radiomics signature. The AUCs of the radiomics nomogram, which was based on the selected clinical factors and Rad-score, were 0.960 and 0.898 in the training and validation sets, respectively. The decision curves of the radiomics nomogram and radiomics signature in the validation set indicated an overall net benefit over the clinical factors model.
conclusionOur radiomics nomogram can effectively predict the preoperative diagnosis of ROs and may therefore be of assistance in sparing unnecessary surgery and tailoring precise therapy. The ROC curves of the clinical model, the radiomics signature and the radiomics nomogram for the validation set. RO = Renal oncocytoma; ccRCC = Clear cell renal cell carcinoma.
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