Small (< 4 cm) Renal Tumors With Predominantly Low Signal Intensity on T2-Weighted Images: Differentiation of Minimal-Fat Angiomyolipoma From Renal Cell Carcinoma.
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.


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
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 × 10-3mm2/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).


CONCLUSIONS
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.
1 Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-dong, Gangnam-gu, Seoul, Republic of Korea 135-710.|2 Present address: School of Medicine, Kangwon National University, Chuncheon, Republic of Korea.
Jung Jae
JJ
Park
1 Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-dong, Gangnam-gu, Seoul, Republic of Korea 135-710.|3 Department of Medical Device Management and Research, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea.
Chan Kyo
CK
Kim
D000273:Adipose Tissue / Q000000981:diagnostic imaging*; D000328:Adult; D000368:Aged; D018207:Angiomyolipoma / Q000000981:diagnostic imaging*; D002292:Carcinoma, Renal Cell / Q000000981:diagnostic imaging* / Q000473:pathology; D003937:Diagnosis, Differential; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007680:Kidney Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012737:Sex Factors; D047368:Tumor Burden
DWI; MRI; apparent diffusion coefficient; diffusion-weighted imaging; minimal-fat angiomyolipoma; renal cell carcinoma