Yong Hee Kim1, Kyunghwa Han1, Young Taik Oh1, Dae Chul Jung1, Nam Hoon Cho2, Sung Yoon Park3. 1. Department of Radiology, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Republic of Korea. 2. Department of Pathology, Yonsei University College of Medicine, Seoul, Republic of Korea. 3. Department of Radiology, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Republic of Korea. yoonio@yuhs.ac.
Abstract
PURPOSE: To assess whether morphologic analysis using computed tomography (CT) could differentiate between fat-poor angiomyolipoma (fpAML) and renal cell carcinoma (RCC). METHODS: A total of 602 patients with a histologically confirmed fpAML (n = 49) or RCC (n = 553) were evaluated. All renal lesions were less than 4 cm in size and had no gross fat on contrast-enhanced CT. For morphologic analysis, overflowing beer sign and angular interface were evaluated. Overflowing beer sign was defined as contact length between bulging-out portion of a mass and the adjacent renal capsule of 3 mm or greater. Angular interface was defined as the angle of parenchymal portion of a mass of 90° or less. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were assessed. Multivariate analysis was conducted to determine which variable is predictive of fpAML. RESULTS: Sensitivity, specificity, PPV, NPV, and accuracy were 61.2% (30/49), 97.1% (537/553), 65.2% (30/46), 96.6% (537/556), and 94.2% (567/602) with overflowing beer sign, while they were 55.1% (27/49), 81.9% (453/553), 21.3% (27/127), 95.4% (453/475), and 79.7% (480/602) with angular interface for fpAML, respectively. Both CT variables were predictive of fpAML (overflowing beer sign, odds ratio = 132.881, p < 0.001; angular interface, odds ratio = 5.766, p = 0.010). The multivariate model with CT variables showed good performance for predicting fpAML (AUC, 0.871 with angular interface, 0.943 with overflowing beer sign, and 0.949 with both). CONCLUSION: Morphologic analysis with contrast-enhanced CT may be useful for differentiating fpAML from RCC. Overflowing beer sign has the potential as an imaging biomarker for fpAML.
PURPOSE: To assess whether morphologic analysis using computed tomography (CT) could differentiate between fat-poor angiomyolipoma (fpAML) and renal cell carcinoma (RCC). METHODS: A total of 602 patients with a histologically confirmed fpAML (n = 49) or RCC (n = 553) were evaluated. All renal lesions were less than 4 cm in size and had no gross fat on contrast-enhanced CT. For morphologic analysis, overflowing beer sign and angular interface were evaluated. Overflowing beer sign was defined as contact length between bulging-out portion of a mass and the adjacent renal capsule of 3 mm or greater. Angular interface was defined as the angle of parenchymal portion of a mass of 90° or less. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were assessed. Multivariate analysis was conducted to determine which variable is predictive of fpAML. RESULTS: Sensitivity, specificity, PPV, NPV, and accuracy were 61.2% (30/49), 97.1% (537/553), 65.2% (30/46), 96.6% (537/556), and 94.2% (567/602) with overflowing beer sign, while they were 55.1% (27/49), 81.9% (453/553), 21.3% (27/127), 95.4% (453/475), and 79.7% (480/602) with angular interface for fpAML, respectively. Both CT variables were predictive of fpAML (overflowing beer sign, odds ratio = 132.881, p < 0.001; angular interface, odds ratio = 5.766, p = 0.010). The multivariate model with CT variables showed good performance for predicting fpAML (AUC, 0.871 with angular interface, 0.943 with overflowing beer sign, and 0.949 with both). CONCLUSION: Morphologic analysis with contrast-enhanced CT may be useful for differentiating fpAML from RCC. Overflowing beer sign has the potential as an imaging biomarker for fpAML.
Authors: Raouf M Seyam; Waleed K Alkhudair; Said A Kattan; Mohamed F Alotaibi; Hassan M Alzahrani; Waleed M Altaweel Journal: J Kidney Cancer VHL Date: 2017-10-16