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Article Abstract

Purpose: Differentiating between benign and malignant ovarian masses remains a significant clinical challenge. Although the Ovarian-Adnexal Reporting and Data System Ultrasound Version 2022 (O-RADS US v2022) provides standardized terminology and high sensitivity, its specificity remains suboptimal, potentially leading to overdiagnosis and overtreatment. Incorporating tumor vascularity evaluation via contrast-enhanced ultrasound (CEUS) and serum tumor markers like CA125 may enhance diagnostic accuracy and help guide clinical management more effectively.

Methods: A retrospective study of 909 patients with adnexal masses undergoing ultrasound at Sichuan Cancer Hospital from May 2022 to March 2025 was conducted. O-RADS US v2022, CEUS scores, and CA125 levels were analyzed to develop a novel scoring system (OCC-US). Diagnostic performance was evaluated using ROC curves, logistic regression, and inter-observer agreement analysis. Additionally, a temporally independent validation cohort was retrospectively assembled to assess the generalizability and diagnostic accuracy of the OCC-US model.

Results: A total of 609 patients were enrolled in the development cohort between May 2022 and May 2024. ROC analysis identified O-RADS US v2022 ≥ 4, CEUS score ≥ 4, and CA125 ≥ 37.815 U/mL as independent predictors of malignancy. Based on these variables, the OCC-US scoring system was developed, assigning 2 points each for O-RADS ≥ 4 and CEUS score ≥ 4, and 1 point for CA125 ≥ 37.815 U/mL (total score range: 0-5). OCC-US achieved the highest diagnostic performance with an AUC of 0.916, outperforming OC-US (0.891), CEUS (0.877), O-RADS US v2022 (0.871), and CA125 (0.784). It significantly improved specificity (85.4% vs. 71.5%, P < 0.001) while maintaining high sensitivity (84.9%), reducing the false-positive rate from 23.1% (O-RADS US v2022) to 6.2%. OCC-US also reduced unnecessary surgical recommendations from 300 (O-RADS US v2022) to 243 (P < 0.001). Inter-observer agreement was excellent (κ = 0.840, P < 0.001), indicating high reliability. In the temporally independent external validation cohort (300 patients enrolled between June 2024 and March 2025), the OCC-US model maintained stable diagnostic performance, with an AUC of 0.867.

Conclusion: The OCC-US model enhances diagnostic specificity while maintaining high sensitivity, optimizing risk stratification and surgical decision-making. Further multi-center prospective studies are needed for broader validation.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12312314PMC
http://dx.doi.org/10.1186/s40644-025-00918-5DOI Listing

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Purpose: Differentiating between benign and malignant ovarian masses remains a significant clinical challenge. Although the Ovarian-Adnexal Reporting and Data System Ultrasound Version 2022 (O-RADS US v2022) provides standardized terminology and high sensitivity, its specificity remains suboptimal, potentially leading to overdiagnosis and overtreatment. Incorporating tumor vascularity evaluation via contrast-enhanced ultrasound (CEUS) and serum tumor markers like CA125 may enhance diagnostic accuracy and help guide clinical management more effectively.

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J Ovarian Res

June 2025

Department of Ultrasound, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, No. 55, Sec. 4, South Renmin Road, Chengdu, 610042, China.

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Article Synopsis
  • This study developed a method to automatically classify ovarian lesions in sonograms using a deep convolutional neural network (DCNN) model called ConvNeXt-Tiny and compared it to other models.
  • A large dataset of sonograms was classified by experienced sonographers according to O-RADS guidelines, and the DCNN models were trained to predict these classifications.
  • The ConvNeXt-Tiny model demonstrated high accuracy and reduced classification time for sonographers, indicating it could effectively assist in clinical settings.
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