Ovarian Lesions Diagnosis Based on Ultrasound Ovarian-Adnexal Reporting and Data System Classification | ||||
| The Egyptian Journal of Hospital Medicine | ||||
| Article 148, Volume 99, Issue 1, April 2025, Page 2427-2434 PDF (616.05 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/ejhm.2025.435016 | ||||
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| Abstract | ||||
| 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. | ||||
| Keywords | ||||
| Ovarian cancer; Ovarian lesions; Risk stratification system; Ultrasound O-RADS v2022 | ||||
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