Background: Ovarian neoplasms are the leading death cause in gynecologic cancers. The need for universally recognized standardized imaging tool yielded the US O-RADS v2022 being its latest iteration. Objectives: To evaluate and integrate ultrasound Ovarian-Adnexal Reporting and Data System (O-RADS) classification system into assessment of ovarian lesions and provide a consistent interpretation for proper risk stratification and management recommendation. Patients and Methods: This is a prospective study that was conducted on all female patients having ovarian lesions either incidentally discovered upon routine ultrasound examination, clinically suspected ovarian lesion or pre-operative evaluation of known ovarian masses attending at Menoufia University Hospitals over six months starting from October 2023 according to inclusion and exclusion criteria. Results: Our study included 112 patients; 92% of scanned ovarian lesions were benign and 8% were malignant. The most common lesion was hemorrhagic cysts, classified as O-RADS 2 and 3, accounting for 42.9%. Mucinous cystadenocarcinoma was the most noted malignant lesion equating for 3.6%. Using ≥ O-RADS 4 as cut-off point for the malignant categories demonstrates optimal diagnostic performance, ROC analysis yielded 100% sensitivity and 99.03% specificity, AUC of 0.998 (95% CI= 0.994-1.000), PPV 90%, NPV 100% and FPR 0.97%. Our high diagnostic accuracy likely reflects rigorous case adjudication. Conclusion: The US O-RADS v2022 classification system achieves a standardized non-invasive approach to properly characterize ovarian lesions with high sensitivity in differentiating benign from malignant lesions. Prospective multicenter studies with larger, demographically heterogenous cohorts are warranted to validate generalizability.
(2025). Ovarian Lesions Diagnosis Based on Ultrasound Ovarian-Adnexal Reporting and Data System Classification. The Egyptian Journal of Hospital Medicine, 99(1), 2427-2434. doi: 10.21608/ejhm.2025.435016
MLA
. "Ovarian Lesions Diagnosis Based on Ultrasound Ovarian-Adnexal Reporting and Data System Classification", The Egyptian Journal of Hospital Medicine, 99, 1, 2025, 2427-2434. doi: 10.21608/ejhm.2025.435016
HARVARD
(2025). 'Ovarian Lesions Diagnosis Based on Ultrasound Ovarian-Adnexal Reporting and Data System Classification', The Egyptian Journal of Hospital Medicine, 99(1), pp. 2427-2434. doi: 10.21608/ejhm.2025.435016
VANCOUVER
Ovarian Lesions Diagnosis Based on Ultrasound Ovarian-Adnexal Reporting and Data System Classification. The Egyptian Journal of Hospital Medicine, 2025; 99(1): 2427-2434. doi: 10.21608/ejhm.2025.435016