Gynecologic Imaging and Reporting Data System for classifying adnexal masses
Juan L Alcázar 1 , Luis Rodriguez-Guzman 2 , Julio Vara 3 , Fernando Amor 2 , Linder Diaz 4 , Humberto Vaccaro 2
Introduction: To perform a systematic review and meta-analysis of the diagnostic performance of the so-called Gynecologic Imaging and Report Data System (GI-RADS) for classifying adnexal masses.
Evidence acquisition: A search for studies reporting about the use of GI-RADS system for classifying adnexal masses from January 2009 to December 2021 was performed in Medline (Pubmed), Google Scholar, Scopus, Cochrane, and Web of Science databases. Pooled sensitivity, specificity, positive and negative likelihood ratios and diagnostic odd ratio (DOR) were calculated. Studies' quality was evaluated using QUADAS-2.
Evidence synthesis: We identified 510 citations. Ultimately, 26 studies comprising 7350 masses were included. Mean prevalence of ovarian malignancy was 26%. The risk of bias was high in eight studies for domain "patient selection" and low for "index test," "reference test" domains for all studies. Overall, pooled estimated sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio and DOR of GI-RADS system for classifying adnexal masses were 94% (95% confidence interval [CI]=91-96%), 90% (95% CI=87-92%), 9.1 (95% CI=7.0-11.9), and 0.07 (95% CI=0.05-0.11), and 132 (95% CI=78-221), respectively. Heterogeneity was high for both sensitivity and specificity. Meta-regression showed that multiple observers and study's design explained this heterogeneity among studies.
Conclusions: GI-RADS system has a good diagnostic performance for classifying adnexal masses.