卵巢-附体成像报告和数据系统 (O-RADS) 超声波版本2019:在病理确认的附体质中,对更新版本 (v2022) 的前性验证和比较
Yassir Edrees Almalki1, Mohammad Abd Alkhalik Basha2, Mohamad Gamal Nada3
1Division of Radiology, Department of Medicine, Medical College, Najran University, Najran, Kingdom of Saudi Arabia.
European radiology
|November 28, 2024
概括
与v2019相比,更新的卵巢-附体报告和数据系统 (O-RADS) 超声波v2022略有提高了附体质的诊断准确性. 这种增强的风险分层有助于为卵巢癌管理做出更好的临床决策.
科学领域:
- 放射学和成像学 放射学和成像学
- 妇科瘤学 妇科瘤学
- 诊断的准确性 诊断的准确性
背景情况:
- 准确的附带质量 (AMs) 的分类对于适当的患者管理和治疗策略至关重要.
- 卵巢-尾报告和数据系统 (O-RADS) 超声波是评估AMs的标准化系统.
- 对分类系统的持续更新旨在提高诊断性能.
研究的目的:
- 评估O-RADS超声波v2019和v2022的诊断准确性和可靠性,以对附质量进行分类.
- 为了比较O-RADS超声波v2019与更新的v2022系统在预测恶性瘤方面的性能.
- 评估两个O-RADS版本的观察者间协议.
主要方法:
- 一项前性研究包括977名怀疑AM的妇女,分析了855名AM.
- 经验丰富的放射科医生使用O-RADS超声波v2019对AM进行分类,然后回顾图像进行v2022分类.
- 组织病理学作为参考标准;诊断准确性和观察者间一致性 (Fleiss kappa) 被计算.
主要成果:
- 这两种O-RADS版本都显示出良好的诊断准确性 (AUC 0.9060.936).
- 与v2019相比,更新的v2022显示了略高的精度 (82.586.7%),灵敏度 (93.695.0%) 和特异性 (78.184.1%).
- 在两种版本中都观察到完美的观察者间一致性 (κ = 0.960.97).
结论:
- 超声波分类系统O-RADS对于预测恶性AMS的准确和可靠.
- 更新后的 v2022 版本在诊断准确性和风险分层方面比 v2019.2019 版本略有改进.
- 使用O-RADS v2022进行增强的风险分层支持改善卵巢癌护理的临床决策和患者结果.
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