PURPOSE: To determine if renal cell carcinomas can be distinguished from high-attenuation renal cysts on portal venous phase contrast material-enhanced computed tomographic (CT) scans. MATERIALS AND METHODS: Fifty-seven renal cell carcinomas and 37 high-attenuation (>20 HU) renal cysts that were at least 1 cm in diameter were retrospectively identified in 90 patients who underwent portal venous phase contrast-enhanced CT. Two independent readers recorded the CT number and degree of internal heterogeneity (uniform or mildly, moderately, or markedly heterogeneous) of all lesions. Logistic regression analysis with adjustment for the two readers was used to examine the association between clinical and CT parameters and the final diagnosis. Stepwise logistic regression analysis was used to identify independent distinguishing variables, which were then incorporated in a classification and regression tree analysis to construct the most efficient classification algorithm. RESULTS: Renal cell carcinomas were of significantly greater size (5.10 cm vs 2.84 cm, P < .001), mean attenuation (101.2 HU vs 55.3 HU, P < .001), and internal heterogeneity (P < .001) than high-attenuation renal cysts. Stepwise logistic regression showed attenuation and internal heterogeneity were both independent variables associated with final diagnosis, but lesion size was not an independent distinguishing variable after adjustment for internal heterogeneity. Classification and regression tree analysis demonstrated that an attenuation greater than 70 HU or the presence of moderate or marked internal heterogeneity was an accurate sign of renal cell carcinoma, with a sensitivity of 91% (52 of 57) for both readers and a specificity of 92% (34 of 37) for reader 1 and 84% (31 of 37) for reader 2. CONCLUSION: On portal venous phase contrast-enhanced CT scans, attenuation greater than 70 HU or moderate or marked internal heterogeneity favor a diagnosis of renal cell carcinoma over a diagnosis of high-attenuation renal cyst.
- Kidney neoplasms
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging