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The value of CT features and demographic data in the differential diagnosis of type 2 papillary renal cell carcinoma from fat-poor angiomyolipoma and oncocytoma

  • Kidneys, Ureters, Bladder, Retroperitoneum
  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

Purposes

To determine the CT features and demographic data predictive of type 2 papillary renal cell carcinoma (PRCC) that can help distinguish this neoplasm from fat-poor angiomyolipoma (fpAML) and oncocytoma.

Methods

Fifty-four patients with type 2 PRCC, 48 with fpAML, and 47 with oncocytoma in the kidney from multiple centers were retrospectively reviewed. The demographic data and CT features of type 2 PRCC were analyzed and compared with those of fpAML and oncocytoma by univariate analysis and multiple logistic regression analysis to determine the predictive factors for differential diagnosis. Then, receiver operating characteristic (ROC) curve analysis was performed to further assess the logistic regression model and set the threshold level values of the numerical parameters.

Results

Older age (≥ 46.5 years), unenhanced lesion-to-renal cortex attenuation (RLRCA) < 1.21, corticomedullary ratio of lesion to renal cortex net enhancement (RLRCNE) < 0.32, and size ≥ 30.1 mm were independent predictors for distinguishing type 2 PRCC from fpAML (OR 14.155, 8.332, and 57.745, respectively, P < 0.05 for all). The area under the curve (AUC) of the multiple logistic regression model in the ROC curve analysis was 0.970. In the combined evaluation, the four independent predictors had a sensitivity and specificity of 0.896 and 0.889, respectively. A corticomedullary RLRCNE < 0.61, irregular shape, and male sex were independent predictors for the differential diagnosis of type 2 PRCC from oncocytoma (OR 15.714, 12.158, and 6.175, respectively, P < 0.05 for all). In the combined evaluation, the three independent predictors had a sensitivity and specificity of 0.889 and 0.979, respectively. The AUC of the multiple logistic regression model in the ROC curve analysis was 0.964.

Conclusion

The combined application of CT features and demographic data had good ability in distinguishing type 2 PRCC from fpAML and oncocytoma, respectively.

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Authors and Affiliations

  1. Medical Imaging Center, The First Affiliated Hospital, Jinan University, Guangzhou, China

    Cuiping Zhou & Changzheng Shi

  2. Department of Radiology, The University of Hong Kong-Shenzhen Hospital, No.1 Haiyuan Road Futian District, Shenzhen, 518000, Guangdong, China

    Cuiping Zhou & Lin Luo

  3. Department of Medical Imaging Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, No. 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China

    Xiaohua Ban

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Zhou, C., Ban, X., Luo, L. et al. The value of CT features and demographic data in the differential diagnosis of type 2 papillary renal cell carcinoma from fat-poor angiomyolipoma and oncocytoma. Abdom Radiol 47, 3838–3846 (2022). https://doi.org/10.1007/s00261-022-03644-9

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