Abstract

The purpose of this study was to retrospectively investigate the utility of multiparametric MRI in differentiating minimal-fat angiomyolipoma (AML) from renal cell carcinoma (RCC) in small renal tumors with predominantly low signal intensity on T2-weighted MR images. Fifty-six patients with pathologically identified renal tumors (1-4 cm) with predominantly low signal intensity on T2-weighted images without visible fat on unenhanced CT images were enrolled. Clinical and MRI variables (tumor-to-renal cortex signal intensity [SI] ratio on T2-weighted images [T2 ratio], apparent diffusion coefficient [ADC], and SI index) on chemical-shift images were evaluated. The ADC was significantly lower in RCC than in minimal-fat AML (p = 0.001). The T2 ratio and signal intensity index were not significantly different between RCC (p = 0.31) and minimal-fat AML (p = 0.74). Multivariate analysis showed that ADC (odds ratio [OR], 0.01; p = 0.02) and male sex (OR, 46.7; p < 0.001) were the independent predictors of RCC. For differentiating minimal-fat AML from RCC, the ROC AUC of ADC was 0.781. When ADC and sex were combined, the AUC significantly increased to 0.937 with a cutoff value of 1.129 × 10-3 mm2/s. For making the diagnosis of minimal-fat AML if the ADC was greater than the threshold, sensitivity was 89.7% and specificity was 88.2% (p = 0.02). In small renal tumors with predominantly low SI on T2-weighted images, ADC is useful for differentiating minimal-fat AML from RCC. Combining ADC with male sex increases the accuracy of RCC prediction.

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