Abdel Razek Ahmed Abdel Khalek, Ashmalla Germeen Albair, Gaballa Gada, Nada Nadia
Department of Diagnostic Radiology, Mansoura Faculty of Medicine, Mansoura 13551, Egypt.
Department of pathology, Mansoura faculty of medicine, Mansoura, Egypt.
Eur J Radiol. 2015 Dec;84(12):2533-8. doi: 10.1016/j.ejrad.2015.09.001. Epub 2015 Sep 12.
To establish proposal ultrasound parotid imaging reporting and data system (PIRADS) for classification and prediction of malignancy of parotid lesions and to assess the inter-observer agreement of this system.
Retrospective analysis of ultrasound and power Duplex images of 142 patients with parotid lesions by two reviewers. Parotid focal lesions were classified into nine patterns and then categorized into five groups: PIRADS 1, definitively benign; PIRADS 2, probably benign; PIRADS 3, indeterminate; PIRADS 4, probably malignant; and PIRADS 5, highly suggestive malignant.
There was excellent interobserver agreement of both reviewers for patterns and PIRADS (K=0.84, P=0.001) with 92% percent agreement. There was excellent agreement of PIRADS 1 (K=1.00, P=0.001), PIRADS 2 (K=0.97, P=0.001), PIRADS 3 (K=0.86, P=0.001) and PIRADS 5 (K=0.88, P=0.001) and good agreement of PIRADS 4 (K=0.67, P=0.001). The Odds ratio of PIRADS 3, 4 and 5 were 1.36 (95% CI=0.39-4.55), 7.11 (95% CI=3.02-11.15) and 8.27 (95% CI=3.49-10.27) respectively. The accuracy was 92% and 90%, sensitivity was 79% and 65%, specificity was 94% and 96% of PIRADS of both reviewers respectively.
The proposed PIRADS is a reliable non-invasive imaging modality that can be used for categorizing parotid lesions and prediction of malignancy.
建立腮腺病变恶性程度分类及预测的超声腮腺成像报告和数据系统(PIRADS),并评估该系统观察者间的一致性。
两名观察者对142例腮腺病变患者的超声及能量多普勒图像进行回顾性分析。腮腺局灶性病变分为9种模式,然后分为5组:PIRADS 1,肯定为良性;PIRADS 2,可能为良性;PIRADS 3,不确定;PIRADS 4,可能为恶性;PIRADS 5,高度提示为恶性。
两名观察者对模式和PIRADS的观察者间一致性极佳(K=0.84,P=0.001),一致性为92%。PIRADS 1(K=1.00,P=0.001)、PIRADS 2(K=0.97,P=0.001)、PIRADS 3(K=0.86,P=0.001)和PIRADS 5(K=0.88,P=0.001)的一致性极佳,PIRADS 4(K=0.67,P=0.001)的一致性良好。PIRADS 3、4和5的优势比分别为1.36(95%可信区间=0.39-4.55)、7.11(95%可信区间=3.02-11.15)和8.27(95%可信区间=3.49-10.27)。两名观察者PIRADS的准确率分别为92%和90%,敏感性分别为79%和65%,特异性分别为94%和96%。
所提出的PIRADS是一种可靠的非侵入性成像方法,可用于腮腺病变的分类和恶性程度预测。