Literature DB >> 33503181

Comparison of Different Ultrasound Classification Systems of Thyroid Nodules for Identifying Malignant Potential: A Cross-sectional Study.

Hua Chen1,2, Jun Ye2, Jianming Song2, Yuguang You2, Weihua Chen2, Yanna Liu3.   

Abstract

OBJECTIVE: In our organization, it has been necessary in our organization to calculate the risk categories according to the American Thyroid Association (ATA), the American Association of Clinical Endocrinologists/American College of Endocrinology/Associazione Medici Endocrinologi (AACE/ACE/AME), and the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TIRADS) classification systems for each patient, from the year 2019; these are also required to be registered in the database. This creates a barrier to medical collaboration in everyday radiological practice because using multiple rating systems can be confusing for both readers and patients. For the change in routine practice, this study aimed to compare diagnostic parameters of the ATA, AACE/ACE/AME, and ACR TIRADS classification systems for the detection of suspicious thyroid nodule(s) considering the results of fine-needle aspiration cytopathology as the reference standard.
METHODS: Data on ultrasound characteristics (2,000 nodules) and fine-needle aspiration cytopathology (39 nodules) were included in the analysis. The decision making of fine-needle aspiration biopsies was evaluated from the ultrasound characteristics as per the ATA, AACE/ACE/AME, and ACR TIRADS classification systems.
RESULTS: The ATA, AACE/ACE/AME, and ACR TIRADS recommended 26, 32, and 37 nodules for fine-needle aspiration biopsies, respectively. Considering the results of fine-needle aspiration cytopathology as the reference standard, the ATA, AACE/ACE/AME, and ACR TIRADS classification systems had 0.993, 0.996, and 0.998 sensitivity, respectively. The accuracies were 0.641, 0.795, and 0.923, respectively.
CONCLUSION: The ACR TIRADS classification system is less invasive and can identify suspicious nodules more accurately than that of ATA and AACE/ACE/AME.

Entities:  

Mesh:

Year:  2021        PMID: 33503181      PMCID: PMC7798132          DOI: 10.6061/clinics/2021/e2126

Source DB:  PubMed          Journal:  Clinics (Sao Paulo)        ISSN: 1807-5932            Impact factor:   2.365


  18 in total

1.  AMERICAN ASSOCIATION OF CLINICAL ENDOCRINOLOGISTS, AMERICAN COLLEGE OF ENDOCRINOLOGY, AND ASSOCIAZIONE MEDICI ENDOCRINOLOGI MEDICAL GUIDELINES FOR CLINICAL PRACTICE FOR THE DIAGNOSIS AND MANAGEMENT OF THYROID NODULES--2016 UPDATE.

Authors:  Hossein Gharib; Enrico Papini; Jeffrey R Garber; Daniel S Duick; R Mack Harrell; Laszlo Hegedüs; Ralf Paschke; Roberto Valcavi; Paolo Vitti
Journal:  Endocr Pract       Date:  2016-05       Impact factor: 3.443

2.  Fine needle aspiration biopsy indications for thyroid nodules: compare a point-based risk stratification system with a pattern-based risk stratification system.

Authors:  Jing-Liang Ruan; Hai-Yun Yang; Rong-Bin Liu; Ming Liang; Ping Han; Xiao-Lin Xu; Bao-Ming Luo
Journal:  Eur Radiol       Date:  2019-02-04       Impact factor: 5.315

3.  Correction to: Diagnostic Performance of Ultrasound-Based Risk-Stratification Systems for Thyroid Nodules: Comparison of the 2015 American Thyroid Association Guidelines with the 2016 Korean Thyroid Association/Korean Society of Thyroid Radiology and 2017 American College of Radiology Guidelines Ha EJ, Na DG, Moon W-J, Lee YH, and Choi N Thyroid 2018;28:1532-1537. DOI: 10.1089/thy.2018.0094.

Authors: 
Journal:  Thyroid       Date:  2019-01       Impact factor: 6.568

4.  Comparison among TIRADS (ACR TI-RADS and KWAK- TI-RADS) and 2015 ATA Guidelines in the diagnostic efficiency of thyroid nodules.

Authors:  Luying Gao; Xuehua Xi; Yuxin Jiang; Xiao Yang; Ying Wang; Shenling Zhu; Xingjian Lai; Xiaoyan Zhang; Ruina Zhao; Bo Zhang
Journal:  Endocrine       Date:  2019-01-18       Impact factor: 3.633

5.  Re: ACR Thyroid Imaging, Reporting and Data System (TI-RADS): White Paper of the ACR TI-RADS Committee.

Authors:  Franklin N Tessler; William D Middleton; Edward G Grant; Jenny K Hoang
Journal:  J Am Coll Radiol       Date:  2018-02-01       Impact factor: 5.532

6.  Interobserver Variability of Sonographic Features Used in the American College of Radiology Thyroid Imaging Reporting and Data System.

Authors:  Jenny K Hoang; William D Middleton; Alfredo E Farjat; Sharlene A Teefey; Nicole Abinanti; Fernando J Boschini; Abraham J Bronner; Nirvikar Dahiya; Barbara S Hertzberg; Justin R Newman; Daniel Scanga; Robert C Vogler; Franklin N Tessler
Journal:  AJR Am J Roentgenol       Date:  2018-04-27       Impact factor: 3.959

7.  Validation and comparison of three newly-released Thyroid Imaging Reporting and Data Systems for cancer risk determination.

Authors:  Ting Xu; Ya Wu; Run-Xin Wu; Yu-Zhi Zhang; Jing-Yu Gu; Xin-Hua Ye; Wei Tang; Shu-Hang Xu; Chao Liu; Xiao-Hong Wu
Journal:  Endocrine       Date:  2018-11-24       Impact factor: 3.633

8.  The 2017 Bethesda System for Reporting Thyroid Cytopathology.

Authors:  Edmund S Cibas; Syed Z Ali
Journal:  Thyroid       Date:  2017-11       Impact factor: 6.568

9.  Reducing the Number of Unnecessary Thyroid Biopsies While Improving Diagnostic Accuracy: Toward the "Right" TIRADS.

Authors:  Giorgio Grani; Livia Lamartina; Valeria Ascoli; Daniela Bosco; Marco Biffoni; Laura Giacomelli; Marianna Maranghi; Rosa Falcone; Valeria Ramundo; Vito Cantisani; Sebastiano Filetti; Cosimo Durante
Journal:  J Clin Endocrinol Metab       Date:  2019-01-01       Impact factor: 5.958

10.  Inter-rater agreement and reliability of thoracic ultrasonographic findings in feedlot calves, with or without naturally occurring bronchopneumonia.

Authors:  S Buczinski; C Buathier; A M Bélanger; H Michaux; N Tison; E Timsit
Journal:  J Vet Intern Med       Date:  2018-08-22       Impact factor: 3.333

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