Literature DB >> 27805843

Diagnosis and Management of Small Thyroid Nodules: A Comparative Study with Six Guidelines for Thyroid Nodules.

Jung Hyun Yoon1, Kyunghwa Han1, Eun-Kyung Kim1, Hee Jung Moon1, Jin Young Kwak1.   

Abstract

Purpose To investigate the diagnostic performances of six guidelines used to assess thyroid nodules and to determine whether any of these guidelines identify cancers of aggressive form in this population. Materials and Methods From March 2007 to February 2010, 4696 thyroid nodules that were 1-2 cm in 4585 patients were diagnosed as benign or malignant on the basis of cytopathologic results. Ultrasonographic examinations of the thyroid nodules were retrospectively reviewed and categorized according to the categories defined by six previously published guidelines for thyroid nodules. Diagnostic performances of each guideline for diagnosing thyroid cancer were calculated and compared by using the generalized estimating equation method for logistic regression. Multivariate regression analysis was used to analyze predictors for distant metastasis and recurrence and persistence in patients with small thyroid cancer. Results Of the 4696 thyroid nodules, 3652 (77.8%) were benign and 1044 (22.2%) were malignant. Followed were 873 patients who were diagnosed with small thyroid cancer, of whom 12 had distant metastasis and 66 had recurrence or persistence of disease. Specificity, positive predictive value, and accuracy were highest with criteria developed by Kim et al (83.1%, 59.6%, and 84.0%, respectively), while sensitivity and negative predictive value were highest with Thyroid Imaging Reporting and Data System developed by Kwak et al (98.8% and 98.6%, respectively; P < .001). Positive findings that indicated fine-needle aspiration in the guidelines did not show significant association with distant metastasis or recurrence or persistence (P > .05), but the study power was low to detect a difference. Conclusion With its high specificity and accuracy, criteria from Kim et al may be an effective guideline to use in the management of small thyroid nodules. © RSNA, 2016 Online supplemental material is available for this article.

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Year:  2016        PMID: 27805843     DOI: 10.1148/radiol.2016160641

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  20 in total

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Authors:  Xiao-Li Wu; Jia-Rui Du; Hui Wang; Chun-Xiang Jin; Guo-Qing Sui; Dong-Yan Yang; Yuan-Qiang Lin; Qiang Luo; Ping Fu; He-Qun Li; Deng-Ke Teng
Journal:  Endocrine       Date:  2019-03-04       Impact factor: 3.633

2.  Pathologic basis of the sonographic differences between thyroid cancer and noninvasive follicular thyroid neoplasm with papillary-like nuclear features.

Authors:  Grace C H Yang; Karen O Fried
Journal:  Ultrasonography       Date:  2017-08-19

3.  European Thyroid Association Guidelines for Ultrasound Malignancy Risk Stratification of Thyroid Nodules in Adults: The EU-TIRADS.

Authors:  Gilles Russ; Steen J Bonnema; Murat Faik Erdogan; Cosimo Durante; Rose Ngu; Laurence Leenhardt
Journal:  Eur Thyroid J       Date:  2017-08-08

4.  A machine-learning algorithm for distinguishing malignant from benign indeterminate thyroid nodules using ultrasound radiomic features.

Authors:  Xavier M Keutgen; Hui Li; Kelvin Memeh; Julian Conn Busch; Jelani Williams; Li Lan; David Sarne; Brendan Finnerty; Peter Angelos; Thomas J Fahey; Maryellen L Giger
Journal:  J Med Imaging (Bellingham)       Date:  2022-05-26

5.  Summary of Meta-analyses of Studies Involving TIRADS Classifications (EU-TIRADS, ACR-TIRADS, and K-TIRADS) in Evaluating the Malignant Potential of Focal Lesions of The Thyroid Gland.

Authors:  Katarzyna Dobruch-Sobczak; Zbigniew Adamczewski; Marek Dedecjus; Andrzej Lewiński; Bartosz Migda; Marek Ruchała; Anna Skowrońska-Szcześniak; Ewelina Szczepanek-Parulska; Klaudia Zajkowska; Agnieszka Żyłka
Journal:  J Ultrason       Date:  2022-04-27

6.  Thyroid imaging reporting and data system (TIRADS) for ultrasound features of nodules: multicentric retrospective study in China.

Authors:  JianQiao Zhou; YanYan Song; WeiWei Zhan; Xi Wei; Sheng Zhang; RuiFang Zhang; Ying Gu; Xia Chen; Liying Shi; XiaoMao Luo; LiChun Yang; QiaoYing Li; BaoYan Bai; XinHua Ye; Hong Zhai; Hua Zhang; XiaoHong Jia; YiJie Dong; JingWen Zhang; ZhiFang Yang; HuiTing Zhang; Yi Zheng; WenWen Xu; LiMei Lai; LiXue Yin
Journal:  Endocrine       Date:  2020-08-27       Impact factor: 3.633

7.  2020 Chinese guidelines for ultrasound malignancy risk stratification of thyroid nodules: the C-TIRADS.

Authors:  JianQiao Zhou; LiXue Yin; Xi Wei; Sheng Zhang; YanYan Song; BaoMing Luo; JianChu Li; LinXue Qian; LiGang Cui; Wen Chen; ChaoYang Wen; YuLan Peng; Qin Chen; Man Lu; Min Chen; Rong Wu; Wei Zhou; EnSheng Xue; YingJia Li; LiChun Yang; ChengRong Mi; RuiFang Zhang; Gang Wu; GuoQing Du; DaoZhong Huang; WeiWei Zhan
Journal:  Endocrine       Date:  2020-08-21       Impact factor: 3.633

8.  Diagnostic performance of US-based FNAB criteria of the 2020 Chinese guideline for malignant thyroid nodules: comparison with the 2017 American College of Radiology guideline, the 2015 American Thyroid Association guideline, and the 2016 Korean Thyroid Association guideline.

Authors:  Hui Zhu; Yan Yang; Senmin Wu; Kai Chen; Hongxia Luo; Jianle Huang
Journal:  Quant Imaging Med Surg       Date:  2021-08

9.  An efficient deep convolutional neural network model for visual localization and automatic diagnosis of thyroid nodules on ultrasound images.

Authors:  Jialin Zhu; Sheng Zhang; Ruiguo Yu; Zhiqiang Liu; Hongyan Gao; Bing Yue; Xun Liu; Xiangqian Zheng; Ming Gao; Xi Wei
Journal:  Quant Imaging Med Surg       Date:  2021-04

10.  Cytologically indeterminate thyroid nodules: increased diagnostic performance with combination of US TI-RADS and a new scoring system.

Authors:  Ya-Ping He; Hui-Xiong Xu; Chong-Ke Zhao; Li-Ping Sun; Xiao-Long Li; Wen-Wen Yue; Le-Hang Guo; Dan Wang; Wei-Wei Ren; Qiao Wang; Shen Qu
Journal:  Sci Rep       Date:  2017-07-31       Impact factor: 4.379

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