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Diagnostic and therapeutic performances of three score-based Thyroid Imaging Reporting and Data Systems after application of equal size thresholds
BACKGROUND: The aim of this study was to explore the diagnostic and therapeutic performances of the artificial intelligence (AI), American College of Radiology (ACR), and Kwak Thyroid Imaging Reporting and Data Systems (TIRADSs) using the size thresholds for fine needle aspiration (FNA) and follow-u...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10102798/ https://www.ncbi.nlm.nih.gov/pubmed/37064344 http://dx.doi.org/10.21037/qims-22-592 |
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author | Si, Cai-Feng Fu, Chao Cui, Yi-Yang Li, Jing Huang, Yuan-Jing Cui, Ke-Fei |
author_facet | Si, Cai-Feng Fu, Chao Cui, Yi-Yang Li, Jing Huang, Yuan-Jing Cui, Ke-Fei |
author_sort | Si, Cai-Feng |
collection | PubMed |
description | BACKGROUND: The aim of this study was to explore the diagnostic and therapeutic performances of the artificial intelligence (AI), American College of Radiology (ACR), and Kwak Thyroid Imaging Reporting and Data Systems (TIRADSs) using the size thresholds for fine needle aspiration (FNA) and follow-up defined in the ACR TIRADS. METHODS: This retrospective study included 3,833 consecutive thyroid nodules identified in 2,590 patients from January 2010 to August 2017. Ultrasound (US) features were reviewed using the 2017 white paper of the ACR TIRADS. US categories were assigned according to the ACR/AI and Kwak TIRADS. We applied the thresholds for FNA and follow-up defined in the ACR TIRADS to the Kwak TIRADS. The diagnostic and therapeutic performances were calculated and compared using the McNemar or DeLong methods. RESULTS: The AI TIRADS had higher specificity, accuracy, and area under the curve (AUC) than did the ACR and Kwak TIRADS (specificity: 64.6% vs. 57.4% and 52.69%; accuracy: 78.5% vs. 75.4% and 73.0%; AUC: 88.2% vs. 86.6% and 86.0%; all P values <0.05). Meanwhile, the AI TIRADS had a lower FNA rate (FNAR), unnecessary FNA rate (UFR), and follow-up rate (FUR) than did the ACR and Kwak TIRADS using the size thresholds of the ACR TIRADS (specificity: 30.9% vs. 34.4% and 36.9%; accuracy: 41.1% vs. 47.8% and 48.7%; AUC: 34.2% vs. 37.7% and 41.0%; all P values <0.05). In addition, the Kwak TIRADS incorporating the size thresholds of the ACR TIRADS was almost similar to the ACR TIRADS in diagnostic and therapeutical performance. CONCLUSIONS: The ACR TIRADS can be simplified, which potentially enhances its diagnostic and therapeutic performance. The method of score-based TIRADS (counting in the Kwak TIRADS and weighting in the ACR and AI TIRADS) might not determine the diagnostic and therapeutic performances of the TIRADS. Thus, we propose choosing a straightforward and practical TIRADS in daily practice. |
format | Online Article Text |
id | pubmed-10102798 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-101027982023-04-15 Diagnostic and therapeutic performances of three score-based Thyroid Imaging Reporting and Data Systems after application of equal size thresholds Si, Cai-Feng Fu, Chao Cui, Yi-Yang Li, Jing Huang, Yuan-Jing Cui, Ke-Fei Quant Imaging Med Surg Original Article BACKGROUND: The aim of this study was to explore the diagnostic and therapeutic performances of the artificial intelligence (AI), American College of Radiology (ACR), and Kwak Thyroid Imaging Reporting and Data Systems (TIRADSs) using the size thresholds for fine needle aspiration (FNA) and follow-up defined in the ACR TIRADS. METHODS: This retrospective study included 3,833 consecutive thyroid nodules identified in 2,590 patients from January 2010 to August 2017. Ultrasound (US) features were reviewed using the 2017 white paper of the ACR TIRADS. US categories were assigned according to the ACR/AI and Kwak TIRADS. We applied the thresholds for FNA and follow-up defined in the ACR TIRADS to the Kwak TIRADS. The diagnostic and therapeutic performances were calculated and compared using the McNemar or DeLong methods. RESULTS: The AI TIRADS had higher specificity, accuracy, and area under the curve (AUC) than did the ACR and Kwak TIRADS (specificity: 64.6% vs. 57.4% and 52.69%; accuracy: 78.5% vs. 75.4% and 73.0%; AUC: 88.2% vs. 86.6% and 86.0%; all P values <0.05). Meanwhile, the AI TIRADS had a lower FNA rate (FNAR), unnecessary FNA rate (UFR), and follow-up rate (FUR) than did the ACR and Kwak TIRADS using the size thresholds of the ACR TIRADS (specificity: 30.9% vs. 34.4% and 36.9%; accuracy: 41.1% vs. 47.8% and 48.7%; AUC: 34.2% vs. 37.7% and 41.0%; all P values <0.05). In addition, the Kwak TIRADS incorporating the size thresholds of the ACR TIRADS was almost similar to the ACR TIRADS in diagnostic and therapeutical performance. CONCLUSIONS: The ACR TIRADS can be simplified, which potentially enhances its diagnostic and therapeutic performance. The method of score-based TIRADS (counting in the Kwak TIRADS and weighting in the ACR and AI TIRADS) might not determine the diagnostic and therapeutic performances of the TIRADS. Thus, we propose choosing a straightforward and practical TIRADS in daily practice. AME Publishing Company 2023-02-23 2023-04-01 /pmc/articles/PMC10102798/ /pubmed/37064344 http://dx.doi.org/10.21037/qims-22-592 Text en 2023 Quantitative Imaging in Medicine and Surgery. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Si, Cai-Feng Fu, Chao Cui, Yi-Yang Li, Jing Huang, Yuan-Jing Cui, Ke-Fei Diagnostic and therapeutic performances of three score-based Thyroid Imaging Reporting and Data Systems after application of equal size thresholds |
title | Diagnostic and therapeutic performances of three score-based Thyroid Imaging Reporting and Data Systems after application of equal size thresholds |
title_full | Diagnostic and therapeutic performances of three score-based Thyroid Imaging Reporting and Data Systems after application of equal size thresholds |
title_fullStr | Diagnostic and therapeutic performances of three score-based Thyroid Imaging Reporting and Data Systems after application of equal size thresholds |
title_full_unstemmed | Diagnostic and therapeutic performances of three score-based Thyroid Imaging Reporting and Data Systems after application of equal size thresholds |
title_short | Diagnostic and therapeutic performances of three score-based Thyroid Imaging Reporting and Data Systems after application of equal size thresholds |
title_sort | diagnostic and therapeutic performances of three score-based thyroid imaging reporting and data systems after application of equal size thresholds |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10102798/ https://www.ncbi.nlm.nih.gov/pubmed/37064344 http://dx.doi.org/10.21037/qims-22-592 |
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