PD10-02 DIFFERENTIATION OF LOW-FAT RENAL ANGIOMYOLIPOMAS FROM OTHER RENAL TUMORS: EFFECT OF T2-WEIGHTED MR IMAGING

You have accessJournal of UrologyKidney Cancer: Evaluation/Staging I1 Apr 2014PD10-02 DIFFERENTIATION OF LOW-FAT RENAL ANGIOMYOLIPOMAS FROM OTHER RENAL TUMORS: EFFECT OF T2-WEIGHTED MR IMAGING Xiaobo Ding, Liang Chen, and Huimao Zhang Xiaobo DingXiaobo Ding More articles by this author , Liang ChenLiang Chen More articles by this author , and Huimao ZhangHuimao Zhang More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2014.02.478AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES To retrospectively assess the usefulness of T2-weighted MR imaging for differentiating low-fat angiomyolipomas (AMLs) from other renal tumors. METHODS We retrospectively evaluated 82 patients with surgically proven renal masses (11 AMLs, 67 renal cell carcinomas [RCCs], and four oncocytomas), all of which showed no visible fat as well as gradual enhancement patterns on contrast-enhanced CT. Signal intensity was measured in each renal mass and in the spleen on T2-weighted images, and each signal intensity ratio (SIR) was calculated; SIR values were then compared in the AML and non-AML groups. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of the two parameters for differentiating the two groups. RESULTS The SIR values (78 ± 23% vs. 160 ± 78%, p = 0.0018) were significantly lower in the AML than in the non-AML group. The area under the ROC curve was 0.928 for SIR. The sensitivity and specificity in the diagnosis of AMLs were 90.2% and 90.4%, using SIR cut-off of 92.6%. CONCLUSIONS Signal intensity measurements on T2-weighted MR images can differentiate AML from non-AML in the kidney. © 2014FiguresReferencesRelatedDetails Volume 191Issue 4SApril 2014Page: e282 Advertisement Copyright & Permissions© 2014MetricsAuthor Information Xiaobo Ding More articles by this author Liang Chen More articles by this author Huimao Zhang More articles by this author Expand All Advertisement Advertisement PDF DownloadLoading ...