Department of Ultrasound Medicine, Laboratory of Ultrasound Medicine and Artificial Intelligence, Experimental Center of Liwan Hospital, The Third Affiliated Hospital of Guangzhou Medical University, The Liwan Hospital of the Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510000, China.
Chin Med J (Engl). 2019 Aug 20;132(16):1974-1982. doi: 10.1097/CM9.0000000000000346.
Ultrasound imaging is well known to play an important role in the detection of thyroid disease, but the management of thyroid ultrasound remains inconsistent. Both standardized diagnostic criteria and new ultrasound technologies are essential for improving the accuracy of thyroid ultrasound. This study reviewed the global guidelines of thyroid ultrasound and analyzed their common characteristics for basic clinical screening. Advances in the application of a combination of thyroid ultrasound and artificial intelligence (AI) were also presented.
An extensive search of the PubMed database was undertaken, focusing on research published after 2001 with keywords including thyroid ultrasound, guideline, AI, segmentation, image classification, and deep learning.
Several types of articles, including original studies and literature reviews, were identified and reviewed to summarize the importance of standardization and new technology in thyroid ultrasound diagnosis.
Ultrasound has become an important diagnostic technique in thyroid nodules. Both standardized diagnostic criteria and new ultrasound technologies are essential for improving the accuracy of thyroid ultrasound. In the standardization, since there are no global consensus exists, common characteristics such as a multi-feature diagnosis, the performance of lymph nodes, explicit indications of fine needle aspiration, and the diagnosis of special populations should be focused on. Besides, evidence suggests that AI technique has a good effect on the unavoidable limitations of traditional ultrasound, and the combination of diagnostic criteria and AI may lead to a great promotion in thyroid diagnosis.
Standardization and development of novel techniques are key factors to improving thyroid ultrasound, and both should be considered in normal clinical use.
超声成像在甲状腺疾病的检测中起着重要作用，但甲状腺超声的管理仍不一致。标准化的诊断标准和新的超声技术对于提高甲状腺超声的准确性至关重要。本研究回顾了全球甲状腺超声指南，并分析了它们在基本临床筛查方面的共同特征。还介绍了甲状腺超声与人工智能（AI）结合应用的进展。
通过广泛搜索 PubMed 数据库，以包括甲状腺超声、指南、人工智能、分割、图像分类和深度学习在内的关键词，搜索了 2001 年后发表的研究。
确定并回顾了多种类型的文章，包括原始研究和文献综述，以总结甲状腺超声诊断中标准化和新技术的重要性。
超声已成为甲状腺结节的重要诊断技术。标准化的诊断标准和新的超声技术对于提高甲状腺超声的准确性至关重要。在标准化方面，由于目前还没有全球共识，因此应该关注多特征诊断、淋巴结表现、明确细针抽吸指征以及特殊人群的诊断等共同特征。此外，有证据表明 AI 技术对传统超声不可避免的局限性有很好的效果，诊断标准和 AI 的结合可能会极大地促进甲状腺的诊断。
标准化和新技术的发展是提高甲状腺超声的关键因素，在常规临床应用中应同时考虑这两个因素。
