Abstract
BACKGROUND: Accurate preoperative differentiation between benign and malignant ovarian tumors is essential for optimal patient management and surgical planning. Ultrasonography remains the first-line imaging modality, and the International Ovarian Tumor Analysis (IOTA) Simple Rules provide a standardized approach for risk stratification. OBJECTIVE: This study aimed to evaluate the diagnostic accuracy of IOTA scoring in differentiating benign and malignant ovarian tumors by correlating ultrasound findings with histopathological outcomes. METHODS: This prospective diagnostic validation study included 75 women with ovarian tumors undergoing surgical management at the Department of Obstetrics and Gynaecology, Institute of Maternal and Child Health (IMCH), Government Medical College, a tertiary care teaching hospital in Kozhikode, India, between January and December 2019. Preoperative ultrasonography was performed using transabdominal and/or transvaginal approaches, and ovarian masses were classified according to the IOTA Simple Rules. Histopathology served as the reference standard. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. RESULTS: Abdominal pain was the most common presenting symptom (62.7%). Histopathology confirmed malignancy in 9.3% of cases, with benign tumors comprising the majority. Epithelial tumors represented the most common histopathological subtype (88%). Among benign ultrasound features, acoustic shadowing (B3) was the most frequent, while unilocular cysts (B1) demonstrated the highest predictive accuracy. Among malignant features, ascites (M2) showed the highest predictive performance. IOTA scoring demonstrated a sensitivity of 85.7%, specificity of 91.2%, PPV of 50.0%, and NPV of 98.4%. CONCLUSION: The IOTA Simple Rules demonstrate good diagnostic accuracy in the preoperative evaluation of ovarian tumors. The particularly high negative predictive value supports their utility as a reliable, non-invasive triage tool for safely excluding malignancy in benign-dominant populations, thereby aiding appropriate surgical planning and referral decisions.