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Refined risk stratification with O-RADS ultrasound v2022: Diagnostic performance compared with v2019 and the ADNEX
Xueqing Wei1, Wen Yang2, Fangxuan Li3
1Department of Diagnostic and Therapeutic Ultrasonography, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China; National Clinical Research Center for Cancer, Tianjin, China; Key Laboratory of Cancer Prevention and Therapy, Tianjin, China; Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Objective:
To evaluate the diagnostic performance and reproducibility of the Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound version 2022 (v2022) compared with O-RADS ultrasound version 2019 (v2019) and the Assessment of Different NEoplasias in the adneXa (ADNEX) model for adnexal mass risk stratification.
Methods:
This retrospective analysis of prospectively collected data included 434 women with surgically confirmed adnexal masses who underwent pelvic ultrasound from January 2022 to December 2023. Three radiologists independently assigned O-RADS ultrasound v2019 and v2022 categories, with consensus classifications used for diagnostic performance analysis. ADNEX malignancy risks were calculated using the official online calculator with serum CA125 included. Diagnostic performance was assessed using receiver operating characteristic analysis, and reader agreement using weighted κ statistics.
Results:
The cohort included 192 benign and 242 malignant lesions. O-RADS ultrasound v2022 showed excellent discriminatory performance, with an area under the curve of 0.935, sensitivity of 98.3%, specificity of 70.8%, and accuracy of 86.2% at the threshold of category ≥ 4. The areas under the curve of O-RADS ultrasound v2022, O-RADS ultrasound v2019, and ADNEX were not significantly different: 0.935, 0.919, and 0.930, respectively. Compared with v2019 and ADNEX, v2022 showed numerically higher specificity. Compared with v2019, v2022 also showed consistently higher inter- and intra-reader agreement.
Conclusion:
O-RADS ultrasound v2022 demonstrated diagnostic performance comparable to that of v2019 and the ADNEX model, while showing numerically higher specificity and greater reader agreement. These findings support v2022 as a refined and reproducible framework for ultrasound-based adnexal mass risk stratification.
