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Reliability of Thyroid Imaging Reporting and Data System (TIRADS) Classification in Differentiating Benign from Malignant Thyroid Nodules

机译:甲状腺影像报告和数据系统(TIRADS)分类在区分良性和恶性甲状腺结节中的可靠性

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Background: Ultrasonography (US) is the best diagnostic tool in the initial assessment of thyroid nodule. Giving its appropriateness and accessibility, ultrasound-based thyroid imaging reporting and data systems (TIRADS) classifications have been developed with main goal to standardize reporting and facilitate communication between practitioners, and to indicate when fine-needle aspiration biopsy (FNAB) should be performed. Objective: To determine the reliability of Russ’ modified TIRADS classification in predicting thyroid malignancy. Materials and Methods: It was a cross sectional study carried out at Centre Hospitalier de Lagny, Marne La Vallée (France). Consecutive records of patients with focal thyroid nodules on ultrasound (US) for which US-guided FNAB was performed and pathology results were available, from January 2007 to August 2012, were selected for review. The risk of malignancy of each TIRADS category was determined and correlation with pathology assessed. Statistical performances of some US features were also assessed. The threshold for statistical significance was set at 0.05. Results: A total of 430 records of patients were eligible. Twenty-three out of 430 (5.3%) nodules were malignant. The risk of malignancy of the TIRADS categories were as follows: TIRADS2 0%, TIRADS3 2.2%, TIRADS4A 5.9%, TIRADS4B 57.9%, TIRADS5 100% (Gamma statistic = 0.85; Spearman correlation = 0.30, Pearson’s R = 0.37, p Conclusion: Russ’ modified TIRADS classification is reliable in predicting thyroid malignancy. More evidence is nevertheless necessary for widespread adoption and use.
机译:背景:超声检查(US)是甲状腺结节初始评估中的最佳诊断工具。考虑到其适当性和可及性,已经开发了基于超声的甲状腺成像报告和数据系统(TIRADS)分类,其主要目的是标准化报告并促进从业者之间的交流,并指出何时应进行细针穿刺活检(FNAB)。目的:确定Russ改良的TIRADS分类在预测甲状腺恶性肿瘤中的可靠性。材料和方法:这是在法国马恩河谷的Lagny中心医院进行的横断面研究。选择从2007年1月至2012年8月在超声(US)上连续行超声检查(美国)的甲状腺局部结节患者的病历,并对其进行病理学检查。确定每种TIRADS类别的恶性风险,并评估其与病理的相关性。还评估了某些美国功能的统计性能。统计显着性的阈值设置为0.05。结果:共有430例患者记录符合条件。 430个结节中有23个(5.3%)为恶性。 TIRADS类别的恶性风险如下:TIRADS2 0%,TIRADS3 2.2%,TIRADS4A 5.9%,TIRADS4B 57.9%,TIRADS5 100%(伽马统计量= 0.85; Spearman相关度= 0.30,Pearson's R = 0.37,p结论:Russ改良的TIRADS分类法可以可靠地预测甲状腺恶性肿瘤,但仍需要更多证据才能广泛采用和使用。

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