Abstract
OBJECTIVE. 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. MATERIALS AND METHODS. 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. RESULTS. T he A DC was significantly lower i n RCC t han i n m inimal-fat A ML ( 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). CONCLUSION. 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.
| Original language | English |
|---|---|
| Pages (from-to) | 124-130 |
| Number of pages | 7 |
| Journal | American Journal of Roentgenology |
| Volume | 208 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2017 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Apparent diffusion coefficient
- DWI
- Diffusionweighted imaging
- MRI
- Minimal-fat angiomyolipoma
- Renal cell carcinoma
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