Sungmin Woo1, Chong Hyun Suh2,3, Jeong Yeon Cho1,4, Sang Youn Kim1, Seung Hyup Kim1,4. 1. 1 Department of Radiology, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 110-744, Republic of Korea. 2. 2 Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea. 3. 3 Department of Radiology, Namwon Medical Center, Jeollabuk-do, Republic of Korea. 4. 4 Institute of Radiation Medicine and Kidney Research Institute, Seoul National University Medical Research Center, Seoul, Republic of Korea.
Abstract
OBJECTIVE: The purpose of this article is to systematically review and perform a meta-analysis of the diagnostic performance of CT for diagnosis of fat-poor angiomyolipoma (AML) in patients with renal masses. MATERIALS AND METHODS: MEDLINE and EMBASE were systematically searched up to February 2, 2017. We included diagnostic accuracy studies that used CT for diagnosis of fat-poor AML in patients with renal masses, using pathologic examination as the reference standard. Two independent reviewers assessed the methodologic quality using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Sensitivity and specificity of included studies were calculated and were pooled and plotted in a hierarchic summary ROC plot. Sensitivity analyses using several clinically relevant covariates were performed to explore heterogeneity. RESULTS: Fifteen studies (2258 patients) were included. Pooled sensitivity and specificity were 0.67 (95% CI, 0.48-0.81) and 0.97 (95% CI, 0.89-0.99), respectively. Substantial and considerable heterogeneity was present with regard to sensitivity and specificity (I2 = 91.21% and 78.53%, respectively). At sensitivity analyses, the specificity estimates were comparable and consistently high across all subgroups (0.93-1.00), but sensitivity estimates showed significant variation (0.14-0.82). Studies using pixel distribution analysis (n = 3) showed substantially lower sensitivity estimates (0.14; 95% CI, 0.04-0.40) compared with the remaining 12 studies (0.81; 95% CI, 0.76-0.85). CONCLUSION: CT shows moderate sensitivity and excellent specificity for diagnosis of fat-poor AML in patients with renal masses. When methods other than pixel distribution analysis are used, better sensitivity can be achieved.
OBJECTIVE: The purpose of this article is to systematically review and perform a meta-analysis of the diagnostic performance of CT for diagnosis of fat-poor angiomyolipoma (AML) in patients with renal masses. MATERIALS AND METHODS: MEDLINE and EMBASE were systematically searched up to February 2, 2017. We included diagnostic accuracy studies that used CT for diagnosis of fat-poor AML in patients with renal masses, using pathologic examination as the reference standard. Two independent reviewers assessed the methodologic quality using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Sensitivity and specificity of included studies were calculated and were pooled and plotted in a hierarchic summary ROC plot. Sensitivity analyses using several clinically relevant covariates were performed to explore heterogeneity. RESULTS: Fifteen studies (2258 patients) were included. Pooled sensitivity and specificity were 0.67 (95% CI, 0.48-0.81) and 0.97 (95% CI, 0.89-0.99), respectively. Substantial and considerable heterogeneity was present with regard to sensitivity and specificity (I2 = 91.21% and 78.53%, respectively). At sensitivity analyses, the specificity estimates were comparable and consistently high across all subgroups (0.93-1.00), but sensitivity estimates showed significant variation (0.14-0.82). Studies using pixel distribution analysis (n = 3) showed substantially lower sensitivity estimates (0.14; 95% CI, 0.04-0.40) compared with the remaining 12 studies (0.81; 95% CI, 0.76-0.85). CONCLUSION: CT shows moderate sensitivity and excellent specificity for diagnosis of fat-poor AML in patients with renal masses. When methods other than pixel distribution analysis are used, better sensitivity can be achieved.
Authors: Joseph R Grajo; Nikhil V Batra; Shahab Bozorgmehri; Laura L Magnelli; Jonathan Pavlinec; Padraic O'Malley; Li-Ming Su; Paul L Crispen Journal: Abdom Radiol (NY) Date: 2021-03-04
Authors: Jérémie F Cohen; Jonathan J Deeks; Lotty Hooft; Jean-Paul Salameh; Daniël A Korevaar; Constantine Gatsonis; Sally Hopewell; Harriet A Hunt; Chris J Hyde; Mariska M Leeflang; Petra Macaskill; Trevor A McGrath; David Moher; Johannes B Reitsma; Anne W S Rutjes; Yemisi Takwoingi; Marcello Tonelli; Penny Whiting; Brian H Willis; Brett Thombs; Patrick M Bossuyt; Matthew D F McInnes Journal: BMJ Date: 2021-03-15