| 郑丽萍,徐晚虹,吕国荣,林婉玲.优化TI-RADS分类鉴别诊断甲状腺良恶性结节[J].中国医学影像技术,2016,32(11):1668~1672 |
| 优化TI-RADS分类鉴别诊断甲状腺良恶性结节 |
| Optimized TI-RADS classification in differential diagnosis of benign and malignant thyroid nodules |
| 投稿时间：2016-05-30 修订日期：2016-09-14 |
| DOI：10.13929/j.1003-3289.2016.11.011 |
| 中文关键词: 甲状腺肿瘤 超声检查 甲状腺影像学报告和数据系统 |
| 英文关键词:Thyroid neoplasms Ultrasography Thyroid imaging reporting and data system |
| 基金项目: |
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| 中文摘要: |
| 目的 探讨优化的甲状腺影像学报告和数据系统（TI-RADS）分类方法在甲状腺结节诊断中的临床应用价值。方法 回顾性分析376例甲状腺结节患者共466个结节的超声图像，并与病理结果对照，按照美国放射学会（ACR）最新提出的甲状腺结节分类术语，对结节成分、结节大小、内部回声、纵横比、边缘、内部钙化、血供情况和颈部异常淋巴结进行χ2检验和多因素Logistic回归分析；筛选出有价值的征象作为TI-RADS分类的超声评价体系，并对所有结节进行分类，并评价其诊断效能。结果 甲状腺恶性结节的独立预测因子有颈部异常淋巴结、微钙化、纵横比≥1、边缘不光整、极低回声及实性成分6个征象，OR值分别为8.695、8.397、7.207、6.993、5.725、3.342；以上述恶性征象作为TI-RADS评价体系，2名医师诊断一致性较好（Kappa=0.767，P<0.05）；TI-RADS分类以4b作为良恶性截点诊断效能最佳，其诊断敏感度、特异度、准确率分别为85.10%（80/94）、88.71%（330/372）、87.98%（410/466）。结论 优化的TI-RADS分类方法在甲状腺结节良恶性的诊断和鉴别诊断中具有较高的应用价值。 |
| 英文摘要: |
| Objective To investigate the clinical application value of optimized thyroid imaging reporting and data system (TI-RADS) classification method in diagnosis of thyroid nodules. Methods Ultrasonographic imaging data of 376 patients with 466 thyroid nodules were retrospectively analyzed and compared with the pathologic diagnosis. There were 8 signs, accorded to the terminology for thyroid nodules that newly suggested by American College of Radiology, including nodules composition, size, internal echo, aspect ratio, edge, internal calcification, the blood supply and abnormal lymph nodes in the neck, were analyzed by the χ2 test and multiple factors Logistic regression analysis. Using the valuable signs as the evaluated system of TI-RADS classification, all the nodules were classified. And then the diagnostic efficacy was evaluated. Results The independent predictors of malignant thyroid nodules were abnormal neck lymph nodes, micro calcification, aspect ratio≥1, irregular margin, very low echo and solid component, and their OR were 8.695, 8.397, 7.207, 6.993, 5.725, 3.342, respectively. When the above malignant signs were used as the evaluation system of TI-RADS, and the consistency of the two doctors was excellent (Kappa=0.767, P<0.05). TI-RADS classification with 4b as the cut-off for diagnosis of benign and malignant had the best performance, and the diagnostic sensitivity, specificity, accuracy was 85.10% (80/94), 88.71% (330/372) and 87.98% (410/466), respectively. Conclusion Optimized TI-RADS classification method has high application value in diagnosing and differentiating malignant from benign thyroid nodules. |
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