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整合O-RADS US v2022、超声造影(CEUS)和CA125以提高卵巢肿块的诊断鉴别能力:OCC-US模型的开发

Integrating O-RADS US v2022, CEUS, and CA125 to enhance the diagnostic differentiation of ovarian masses: development of the OCC-US model.

作者信息

Jiang Zhuolin, Pu Wei, Luo Xinyi, Zhang Jie, Jia Shijun, Zhang Guonan, Zhu Yi

机构信息

Department of Ultrasound, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China (UESTC), Chengdu, 610041, China.

Department Gynecologic Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China (UESTC), Chengdu, 610041, China.

出版信息

Cancer Imaging. 2025 Jul 30;25(1):96. doi: 10.1186/s40644-025-00918-5.

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.

摘要

目的

鉴别卵巢良恶性肿块仍然是一项重大的临床挑战。尽管2022年版卵巢附件报告和数据系统超声(O-RADS US v2022)提供了标准化术语且具有高敏感性,但其特异性仍不理想,可能导致过度诊断和过度治疗。通过超声造影(CEUS)评估肿瘤血管以及检测血清肿瘤标志物如CA125,可能会提高诊断准确性并更有效地指导临床管理。

方法

对2022年5月至2025年3月在四川省肿瘤医院接受超声检查的909例附件肿块患者进行回顾性研究。分析O-RADS US v2022、CEUS评分和CA125水平,以建立一种新的评分系统(OCC-US)。使用ROC曲线、逻辑回归和观察者间一致性分析评估诊断性能。此外,回顾性组建一个时间独立的验证队列,以评估OCC-US模型的普遍性和诊断准确性。

结果

2022年5月至2024年5月期间,共有609例患者纳入开发队列。ROC分析确定O-RADS US v2022≥4、CEUS评分≥4和CA125≥37.815 U/mL为恶性肿瘤的独立预测因素。基于这些变量,开发了OCC-US评分系统,O-RADS≥4和CEUS评分≥4各赋2分,CA125≥37.815 U/mL赋1分(总分范围:0-5分)。OCC-US的诊断性能最佳,AUC为0.916,优于OC-US(0.891)、CEUS(0.877)、O-RADS US v2022(0.871)和CA125(0.784)。它显著提高了特异性(85.4%对71.5%,P<0.001),同时保持了高敏感性(84.9%),将假阳性率从23.1%(O-RADS US v2022)降至6.2%。OCC-US还将不必要的手术建议从300例(O-RADS US v2022)减少到243例(P<0.001)。观察者间一致性良好(κ=0.840,P<0.001),表明可靠性高。在时间独立的外部验证队列(2024年6月至2025年3月纳入300例患者)中,OCC-US模型保持了稳定的诊断性能,AUC为0.867。

结论

OCC-US模型在保持高敏感性的同时提高了诊断特异性,优化了风险分层和手术决策。需要进一步开展多中心前瞻性研究以进行更广泛的验证。

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