MR texture analysis in the differentiation of renal oncocytoma with localized renal cell carcinoma subtypes

Abstract

Objectives We aimed to explore the diagnostic efficacy of MR texture analysis and imaging signs in the differentiation of renal oncocytoma from renal cell carcinoma (RCC). Methods From January 2015 to March 2019, a total of 168 localized solid renal masses (37 oncocytomas, 131 RCCs) were retrospectively included. Two radiologists reviewed complete MR images and recorded imaging presentation. Texture parameters were extracted from 3D ROIs on axial FSE-T2WI. Univariate and multivariate logistic regressions were used for feature selection and nomogram construction. The diagnostic performances were assessed by receiver operating characteristic (ROC) curves. Results Cystic change, hemorrhage, SEI and four texture parameters significantly correlated with oncocytoma in the training cohort. For differentiating oncocytoma from RCC, the nomogram yielded an AUC of 0.874 in the training cohort and 0.830 in the testing cohort. For differentiating oncocytoma from chRCC, the nomogram had an AUC of 0.889 in the training cohort and 0.861 in the testing cohort. For differentiating oncocytoma from pRCC, the nomogram had an AUC of 0.932 in the training cohort and 0.792 in the testing cohort. For differentiating oncocytoma from ccRCC, the nomogram had an AUC of 0.829 in the training cohort and 0.813 in the testing cohort. Conclusion The diagnostic nomogram combining MR texture parameters with imaging signs performed well in differentiating oncocytomas with localized RCC and its subtypes. Advances in knowledge Few articles reported using the combination of MR texture analysis with imaging signs in differentiating RCC from oncocytoma. Our study established a useful nomogram in subtype characterization.