The role of radiomics analysis in the assessment of renal nodules on CT

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Abstract
Purpose: To develop a radiomics model for the characterization of renal nodules on CT. Methods: Patients who underwent surgical resection of renal nodules, with preoperative CT (LightSpeed VCT, GE) with contrast agent (Iopamidol 370; 1.5 ml/kg) and availability of a histopathological report, were retrospectively included. Renal lesions were segmented by two radiologists in consensus, in the arterial phase on the axial section with greater diameter. The radiomics analysis was performed with validated software (PyRadiomics on Syngo.via Frontier, Siemens) by applying normalization, resampling (1,1,1), setting bin width (15), and applying padding (2). The extracted features were used for training and testing machine learning models (random forest and support vector machine (end point: clear cell carcinoma, ccRCC). Results: 45 patients were included (mean age 56 years; 34/45 ccRCC). SVM e RF models obtained an AUC of 0.84 and accuracy of 0.87 and 0.80, respectively, in the testing phase. Conclusion: Radiomics analysis is feasible and effective in the characterization of renal lesions on CT.

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