Obstetrics and Gynecology Residents Can Accurately Classify Benign Ovarian Tumors Using the International Ovarian Tumor Analysis Rules.
OBJECTIVES: Recognition of benign versus malignant tumors is essential in gynecologic ultrasound (US). The International Ovarian Tumor Analysis (IOTA) rules have been proposed as part of resident US training. The objective of this study was to examine whether they could be accurately used by obstetrics and gynecology residents in Rwanda. METHODS: Patients undergoing explorative laparotomy for adnexal masses at the University Teaching Hospital of Kigali were included. Before the study, a didactic lecture on the IOTA rules for classifying adnexal masses was performed. Preoperative transabdominal US examinations were performed by residents at different levels of training, who were blinded to the results of prior US examinations. The IOTA classification was compared to the final pathologic diagnosis. RESULTS: There were 72 patients who underwent 116 US examinations. Only 15.5% of US examinations were considered inconclusive. First-year residents (12) correctly diagnosed 18 of 20 masses (90%) as benign and 4 of 4 as malignant. Second-year residents (9) classified 29 of 29 masses correctly. Third-year residents (10) accurately identified 21 of 22 (95.5%) as benign and 5 of 5 as malignant. Fourth-year residents (13) accurately identified 11 of 12 (91.7%) as benign and 6 of 6 as malignant. Therefore, 74 of 78 tumors (94.9%) considered benign by IOTA rules were confirmed by histologic results. Similarly, all 20 tumors classified as malignant were confirmed. Overall, the sensitivities to diagnose benign and malignant tumors by the IOTA rules were 83.3% and 100%, respectively. The positive and negative predictive values were 100% and 94.9%. There were no significant differences noted between residency years. CONCLUSIONS: All levels of Rwandan obstetrics and gynecology residents were able to use the IOTA rules to accurately distinguish benign from malignant tumors.
Sebajuri, JMV; Magriples, U; Small, M; Ntasumbumuyange, D; Rulisa, S; Bazzett-Matabele, L
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