Literature DB >> 30474824

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

Ting Xu1, Ya Wu2, Run-Xin Wu3, Yu-Zhi Zhang4, Jing-Yu Gu2, Xin-Hua Ye5, Wei Tang1, Shu-Hang Xu6, Chao Liu6, Xiao-Hong Wu7.   

Abstract

PURPOSE: To validate and compare diagnostic value of three newly-released Thyroid Imaging Reporting and Data Systems (TIRADS) for cancer risk determination.
METHODS: Total 2031 patients with 2465 thyroid nodules were recruited for this study. Ultrasound (US) images were categorized based on three TIRADS editions established by Korean Society of Thyroid Radiology (KSThR), European Thyroid Association (ETA) and American College of Radiology (ACR). ROC curves were established to compare diagnostic value.
RESULTS: Total 1460 benign and 1005 malignant nodules were enrolled. The malignancy rates of each category in KSThR-TIRADS were 2.8%, 5.1%, 33.7% and 79.6%, respectively. For European-TIRADS, 0, 3.1, 22.8, and 73.5% of nodules categorized as 2 to 5 were malignant. Distribution of carcinomas among ACR-TIRADS categories was 0%, 2.3%, 7.5%, 40.1% and 81.4%, respectively. In terms of diagnostic value, KSThR-TIRADS had highest AUC (0.855) and specificity (87.4%), while lowest (71.4%) sensitivity. ACR-TIRADS showed best sensitivity (96.6%) with lowest specificity (52.9%) and the AUC (0.846) was slightly lower than KSThR-TIRADS. Total 56.1, 45.4, and 37.4% fine-needle aspiration biopsy (FNAB) were recommended by KSThR, ETA and ACR, revealing 42.8%, 44.5% and 53.6% malignant lesions, respectively. The rate of unnecessary FNAB was lowest with the ACR (17.3%), followed by ETA (25.2%) and KSThR (32.1%).
CONCLUSION: All these US models showed great value in predicting thyroid malignancy. Among them, KSThR-TIRADS showed the most effective diagnostic performance in specificity, while ACR-TIRADS yielded best sensitivity. As for FNAB criteria, ACR-TIRADS showed the lowest rate of unnecessary FNAB and highest rate of malignancy in FNAB.

Entities:  

Keywords:  Diagnostic value; Malignancy; Thyroid nodule; Ultrasound

Year:  2018        PMID: 30474824     DOI: 10.1007/s12020-018-1817-8

Source DB:  PubMed          Journal:  Endocrine        ISSN: 1355-008X            Impact factor:   3.633


  41 in total

1.  Management of thyroid nodules detected at US: Society of Radiologists in Ultrasound consensus conference statement.

Authors:  Mary C Frates; Carol B Benson; J William Charboneau; Edmund S Cibas; Orlo H Clark; Beverly G Coleman; John J Cronan; Peter M Doubilet; Douglas B Evans; John R Goellner; Ian D Hay; Barbara S Hertzberg; Charles M Intenzo; R Brooke Jeffrey; Jill E Langer; P Reed Larsen; Susan J Mandel; William D Middleton; Carl C Reading; Steven I Sherman; Franklin N Tessler
Journal:  Radiology       Date:  2005-12       Impact factor: 11.105

2.  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; Lincoln L Berland; Sharlene A Teefey; John J Cronan; Michael D Beland; Terry S Desser; Mary C Frates; Lynwood W Hammers; Ulrike M Hamper; Jill E Langer; Carl C Reading; Leslie M Scoutt; A Thomas Stavros
Journal:  J Am Coll Radiol       Date:  2017-04-02       Impact factor: 5.532

3.  Thyroid Imaging Reporting and Data System Risk Stratification of Thyroid Nodules: Categorization Based on Solidity and Echogenicity.

Authors:  Dong Gyu Na; Jung Hwan Baek; Jin Yong Sung; Ji-Hoon Kim; Jae Kyun Kim; Young Jun Choi; Hyobin Seo
Journal:  Thyroid       Date:  2016-02-09       Impact factor: 6.568

Review 4.  Diagnostic performance of shear wave elastography in the identification of malignant thyroid nodules: a meta-analysis.

Authors:  Peiliang Lin; Minqi Chen; Baoxian Liu; Siwen Wang; Xiaoxi Li
Journal:  Eur Radiol       Date:  2014-08-12       Impact factor: 5.315

Review 5.  Real-time ultrasound elastography for differentiation of benign and malignant thyroid nodules: a meta-analysis.

Authors:  Jiasi Sun; Jingyu Cai; Xuemei Wang
Journal:  J Ultrasound Med       Date:  2014-03       Impact factor: 2.153

6.  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

7.  The EFSUMB Guidelines and Recommendations for the Clinical Practice of Contrast-Enhanced Ultrasound (CEUS) in Non-Hepatic Applications: Update 2017 (Long Version).

Authors:  Paul S Sidhu; Vito Cantisani; Christoph F Dietrich; Odd Helge Gilja; Adrian Saftoiu; Eva Bartels; Michele Bertolotto; Fabrizio Calliada; Dirk-André Clevert; David Cosgrove; Annamaria Deganello; Mirko D'Onofrio; Francesco Maria Drudi; Simon Freeman; Christopher Harvey; Christian Jenssen; Ernst-Michael Jung; Andrea Sabine Klauser; Nathalie Lassau; Maria Franca Meloni; Edward Leen; Carlos Nicolau; Christian Nolsoe; Fabio Piscaglia; Francesco Prada; Helmut Prosch; Maija Radzina; Luca Savelli; Hans-Peter Weskott; Hessel Wijkstra
Journal:  Ultraschall Med       Date:  2018-03-06       Impact factor: 6.548

8.  Thyroid imaging reporting and data system for US features of nodules: a step in establishing better stratification of cancer risk.

Authors:  Jin Young Kwak; Kyung Hwa Han; Jung Hyun Yoon; Hee Jung Moon; Eun Ju Son; So Hee Park; Hyun Kyung Jung; Ji Soo Choi; Bo Mi Kim; Eun-Kyung Kim
Journal:  Radiology       Date:  2011-07-19       Impact factor: 11.105

9.  Malignancy risk stratification in thyroid nodules with benign results on cytology: combination of thyroid imaging reporting and data system and Bethesda system.

Authors:  Hee Jung Moon; Eun-Kyung Kim; Jin Young Kwak
Journal:  Ann Surg Oncol       Date:  2014-02-21       Impact factor: 5.344

Review 10.  The accuracy of thyroid nodule ultrasound to predict thyroid cancer: systematic review and meta-analysis.

Authors:  Juan P Brito; Michael R Gionfriddo; Alaa Al Nofal; Kasey R Boehmer; Aaron L Leppin; Carl Reading; Matthew Callstrom; Tarig A Elraiyah; Larry J Prokop; Marius N Stan; M Hassan Murad; John C Morris; Victor M Montori
Journal:  J Clin Endocrinol Metab       Date:  2013-11-25       Impact factor: 5.958

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  25 in total

1.  Use of the Thyroid Imaging Reporting and Data System (TIRADS) in clinical practice: an Italian survey.

Authors:  Giovanni Mauri; Salvatore Gitto; Vito Cantisani; Gianfranco Vallone; Cosima Schiavone; Enrico Papini; Luca Maria Sconfienza
Journal:  Endocrine       Date:  2020-01-25       Impact factor: 3.633

2.  Ultrasound-Based Indications for Thyroid Fine-Needle Aspiration: Outcome of a TIRADS-Based Approach versus Operators' Expertise.

Authors:  Tamas Solymosi; Laszlo Hegedüs; Steen Joop Bonnema; Andrea Frasoldati; Laszlo Jambor; Gabor Laszlo Kovacs; Enrico Papini; Karoly Rucz; Gilles Russ; Zsolt Karanyi; Endre V Nagy
Journal:  Eur Thyroid J       Date:  2020-11-25

3.  Comparison of different systems of ultrasound (US) risk stratification for malignancy in elderly patients with thyroid nodules. Real world experience.

Authors:  Fernando Di Fermo; Noelia Sforza; Melanie Rosmarin; Yanina Morosan Allo; Carina Parisi; Jimena Santamaria; Nestor Pacenza; Carlos Zuk; Cristina Faingold; Florencia Ferraro; Tomas Meroño; Gabriela Brenta
Journal:  Endocrine       Date:  2020-04-14       Impact factor: 3.633

4.  Diagnostic performance rates of the ACR-TIRADS and EU-TIRADS based on histopathological evidence.

Authors:  İlhan Hekimsoy; Egemen Öztürk; Yeşim Ertan; Mehmet Nurullah Orman; Gülgün Kavukçu; Ahmet Gökhan Özgen; Murat Özdemir; Süha Süreyya Özbek
Journal:  Diagn Interv Radiol       Date:  2021-07       Impact factor: 2.630

5.  Evaluation of the Diagnostic Performance of EU-TIRADS in Discriminating Benign from Malignant Thyroid Nodules: A Prospective Study in One Referral Center.

Authors:  Roussanka D Kovatcheva; Alexander D Shinkov; Inna D Dimitrova; Ralitsa B Ivanova; Kalin N Vidinov; Radina S Ivanova
Journal:  Eur Thyroid J       Date:  2020-05-18

6.  Deep Learning Based on ACR TI-RADS Can Improve the Differential Diagnosis of Thyroid Nodules.

Authors:  Ge-Ge Wu; Wen-Zhi Lv; Rui Yin; Jian-Wei Xu; Yu-Jing Yan; Rui-Xue Chen; Jia-Yu Wang; Bo Zhang; Xin-Wu Cui; Christoph F Dietrich
Journal:  Front Oncol       Date:  2021-04-27       Impact factor: 6.244

7.  Comparison of British Thyroid Association, American College of Radiology TIRADS and Artificial Intelligence TIRADS with histological correlation: diagnostic performance for predicting thyroid malignancy and unnecessary fine needle aspiration rate.

Authors:  Linda Watkins; Greg O'Neill; David Young; Claire McArthur
Journal:  Br J Radiol       Date:  2021-06-09       Impact factor: 3.039

Review 8.  Contemporary Thyroid Nodule Evaluation and Management.

Authors:  Giorgio Grani; Marialuisa Sponziello; Valeria Pecce; Valeria Ramundo; Cosimo Durante
Journal:  J Clin Endocrinol Metab       Date:  2020-09-01       Impact factor: 5.958

9.  TIRADS Management Guidelines in the Investigation of Thyroid Nodules; Illustrating the Concerns, Costs, and Performance.

Authors:  Tom James Cawood; Georgia Rose Mackay; Penny Jane Hunt; Donal O'Shea; Stephen Skehan; Yi Ma
Journal:  J Endocr Soc       Date:  2020-03-10

10.  The Diagnostic Efficiency of Ultrasound Computer-Aided Diagnosis in Differentiating Thyroid Nodules: A Systematic Review and Narrative Synthesis.

Authors:  Nonhlanhla Chambara; Michael Ying
Journal:  Cancers (Basel)       Date:  2019-11-08       Impact factor: 6.639

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