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Gynecology Imaging Reporting and Data System (GI-RADS): diagnostic performance and inter-reviewer agreement

机译:妇科成像报告和数据系统(GI-RAD):诊断性能和审核互联协议

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Objective To evaluate diagnostic performance and inter-reviewer agreement (IRA) of the Gynecologic Imaging Reporting and Data System (GI-RADS) for diagnosis of adnexal masses (AMs) by pelvic ultrasound (US). Patients and methods A prospective multicenter study included 308 women (mean age, 41 +/- 12.5 years; range, 15-73 years) with 325 AMs detected by US. All US examinations were analyzed, and AMs were categorized into five categories according to the GI-RADS classification. We used histopathology and US follow-up as the reference standards for calculating diagnostic performance of GI-RADS for detecting malignant AMs. The Fleiss kappa (kappa) tests were applied to evaluate the IRA of GI-RADS scoring results for predicting malignant AMs. Results A total of 325 AMs were evaluated: 127 (39.1%) were malignant and 198 (60.9%) were benign. Of 95 AMs categorized as GI-RADS 2 (GR2), none was malignant; of 94 AMs categorized as GR3, three were malignant; of 13 AMs categorized as GR4, six were malignant; and of 123 AMs categorized as GR5, 118 were malignant. On a lesion-based analysis, the GI-RADS had a sensitivity, a specificity, and an accuracy of 92.9%, 97.5%, and 95.7%, respectively, when regarding only those AMs classified as GR5 for predicting malignancy. Considering combined GR4 and GR5 as a predictor for malignancy, the sensitivity, specificity, and accuracy of GI-RADS were 97.6%, 93.9%, and 95.4%, respectively. The IRA of the GI-RADS category was very good (kappa = 0.896). The best cutoff value for predicting malignant AMs was >GR3. Conclusions The GI-RADS is very valuable for improving US structural reports.
机译:目的探讨妇科影像学报告和数据系统(GI-RAD)的诊断性能和审查人员协议(IRA),用于通过盆腔超声(US)诊断附件群(AMS)的诊断。患者和方法潜在的多中心研究包括308名女性(平均年龄,41 +/- 12.5岁;范围,15-73岁),由我们检测到325AM。根据GI-RADS分类,对所有美国考试进行了分析,AMS分为五类。我们使用组织病理学和美国随访作为计算GI-RAD诊断性能以检测恶性AMS的参考标准。 Fleiss Kappa(Kappa)测试被应用于评估GI-RADS评分结果的IRA,以预测恶性AMS。结果共有325AMS评估:127(39.1%)是恶性的,198(60.9%)是良性的。 95AMS分类为GI-RADS 2(GR2),没有恶性; 94 ams分类为GR3,三个是恶性的; 13个AMS分为GR4,六个是恶性的;并且123 ams分为GR5,118年是恶性的。在基于病变的分析中,在只有仅归类为GR5的AMS以预测恶性肿瘤的那些AMS,GI-RAD分别具有92.9%,97.5%和95.7%的准确性。将GR4和GR5组合作为恶性肿瘤的预测因子,GI-rads的敏感性,特异性和准确性分别为97.6%,93.9%和95.4%。 GI-RADS类别的IRA非常好(Kappa = 0.896)。预测恶性AMS的最佳截止值> GR3。结论GI-rads对改善美国的结构报告非常有价值。

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