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A novel TIRADS of US classification

BACKGROUND: Thyroid imaging reporting and data system (TIRADS) is the assessment of a risk stratification of thyroid nodules, usually using a score. However, there is no consensus as to the version of TIRADS for reporting the results of thyroid ultrasound in clinic. The objective of this study is to...

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Autores principales: Zhuang, Yan, Li, Cheng, Hua, Zhan, Chen, Ke, Lin, Jiang Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6006938/
https://www.ncbi.nlm.nih.gov/pubmed/29914498
http://dx.doi.org/10.1186/s12938-018-0507-3
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author Zhuang, Yan
Li, Cheng
Hua, Zhan
Chen, Ke
Lin, Jiang Li
author_facet Zhuang, Yan
Li, Cheng
Hua, Zhan
Chen, Ke
Lin, Jiang Li
author_sort Zhuang, Yan
collection PubMed
description BACKGROUND: Thyroid imaging reporting and data system (TIRADS) is the assessment of a risk stratification of thyroid nodules, usually using a score. However, there is no consensus as to the version of TIRADS for reporting the results of thyroid ultrasound in clinic. The objective of this study is to develop a practical TIRADS with which to categorize thyroid nodules and stratify their malignant risk. METHODS: A TIRADS scoring system was developed to provide more decision levels than standard scoring through the selection of the ultrasound features which include the calcification shape, margins, taller-than-wide, internal echo, blood flow quantization of features, setting of the weight, and calculation of the score. Ultimately, the accuracy of our TIRADS was evaluated by comparing with the results of current vision of TIRADS and thyroid radiologist in 153 patients who had US-guided fine-needle aspiration biopsy. RESULTS: Classification results showed that the total accuracy reached 97% (100% of malignant and 95% of the benign) in 153 cases (benign:78, malignant:75). The percentages of malignancy is defined in our TIRADS were as follows: TIRADS 2 (0% malignancy), TIRADS 3 (3.6% malignancy), TIRADS 4 (17–75% malignancy), and TIRADS 5 (98% malignancy). CONCLUSIONS: We established a novel TIRADS to predict the malignancy risk of the thyroid nodules based on six categories US features by a scoring system, which included a standardized vocabulary and score and a quantified risk assessment. The results showed that objective quantitative classification of thyroid nodules by our TIRADS can be useful in guiding management decisions.
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spelling pubmed-60069382018-06-26 A novel TIRADS of US classification Zhuang, Yan Li, Cheng Hua, Zhan Chen, Ke Lin, Jiang Li Biomed Eng Online Research BACKGROUND: Thyroid imaging reporting and data system (TIRADS) is the assessment of a risk stratification of thyroid nodules, usually using a score. However, there is no consensus as to the version of TIRADS for reporting the results of thyroid ultrasound in clinic. The objective of this study is to develop a practical TIRADS with which to categorize thyroid nodules and stratify their malignant risk. METHODS: A TIRADS scoring system was developed to provide more decision levels than standard scoring through the selection of the ultrasound features which include the calcification shape, margins, taller-than-wide, internal echo, blood flow quantization of features, setting of the weight, and calculation of the score. Ultimately, the accuracy of our TIRADS was evaluated by comparing with the results of current vision of TIRADS and thyroid radiologist in 153 patients who had US-guided fine-needle aspiration biopsy. RESULTS: Classification results showed that the total accuracy reached 97% (100% of malignant and 95% of the benign) in 153 cases (benign:78, malignant:75). The percentages of malignancy is defined in our TIRADS were as follows: TIRADS 2 (0% malignancy), TIRADS 3 (3.6% malignancy), TIRADS 4 (17–75% malignancy), and TIRADS 5 (98% malignancy). CONCLUSIONS: We established a novel TIRADS to predict the malignancy risk of the thyroid nodules based on six categories US features by a scoring system, which included a standardized vocabulary and score and a quantified risk assessment. The results showed that objective quantitative classification of thyroid nodules by our TIRADS can be useful in guiding management decisions. BioMed Central 2018-06-18 /pmc/articles/PMC6006938/ /pubmed/29914498 http://dx.doi.org/10.1186/s12938-018-0507-3 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Zhuang, Yan
Li, Cheng
Hua, Zhan
Chen, Ke
Lin, Jiang Li
A novel TIRADS of US classification
title A novel TIRADS of US classification
title_full A novel TIRADS of US classification
title_fullStr A novel TIRADS of US classification
title_full_unstemmed A novel TIRADS of US classification
title_short A novel TIRADS of US classification
title_sort novel tirads of us classification
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6006938/
https://www.ncbi.nlm.nih.gov/pubmed/29914498
http://dx.doi.org/10.1186/s12938-018-0507-3
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