Utility of CT Texture Analysis in Differentiating Low-Attenuation Renal Cell Carcinoma From Cysts: A Bi-Institutional Retrospective Study.

AJR Am J Roentgenol 2019 12 6;213(6):1259-1266. Epub 2019 Aug 6.

Department of Radiology, University of Wisconsin School of Medicine and Public Health, E3/366 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252.

The purpose of this study was to evaluate the utility of CT texture analysis (CTTA) in differentiating low-attenuation renal cell carcinoma (RCC) from renal cysts on unenhanced CT. Ninety-four patients with low-attenuation RCC on unenhanced CT were compared with a cohort of 192 patients with benign renal cysts. CT characteristics (size and minimum, maximum, and mean attenuation) and CTTA features were recorded using an ROI approximately two-thirds the size of the mass. Masses were subjectively assessed by two expert genitourinary readers and two novice readers using a 5-point Likert scale (1 = definite cyst, 5 = definite renal cell carcinoma). Results of first-order CTTA and subjective evaluation were compared using ROC analysis. The group of 94 patients with low-attenuation RCC included 62 men and 32 women (mean age, 58.0 years). On unenhanced CT, the RCC were larger than 10 mm and of a median size of 50 mm with less than or equal to 20 HU (mean attenuation, 16 ± 4 HU). Of the RCC cohort, 83 were clear cell subtype. The cohort of 192 patients included 134 men and 58 women (mean age, 64.7 years) with benign renal cysts greater than 10 mm and a median size of 27 mm and less than or equal to 20 HU (mean attenuation, 9 ± 6 HU). The mean follow-up time was 6.2 years. Mean entropy in the low-attenuation RCC group (4.1 ± 0.7) was significantly higher than in the cyst group (2.8 ± 1.3, < 0.0001). Entropy showed an ROC AUC of 0.89, with sensitivity of 84% and specificity of 80% at threshold 3.9. The AUC was better than subjective evaluation by novice readers (AUC, 0.77) and comparable to subjective evaluation by two expert readers (AUC, 0.90). A model combining the three best texture features (unfiltered mean gray-level attenuation, coarse entropy, and kurtosis) showed an improved AUC of 0.92. High entropy revealed with CTTA may be used to differentiate low-attenuation RCC from cysts at unenhanced CT; this technique performs as well as expert readers.

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http://dx.doi.org/10.2214/AJR.19.21182DOI Listing
December 2019
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