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Revised Thyroid Imaging Reporting and Data System (TIRADS): imitating the American College of Radiology TIRADS, a single-center retrospective study
BACKGROUND: The incidence of thyroid lumps is more and more high in population, and most biopsies of thyroid nodules are benign. To develop a practical risk stratification system based on five ultrasound features to stratify the malignancy risk of thyroid neoplasms. METHODS: This retrospective inves...
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/PMC10240023/ https://www.ncbi.nlm.nih.gov/pubmed/37284080 http://dx.doi.org/10.21037/qims-22-1307 |
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author | Liang, Fengping Li, Xiang Ji, Qiao He, Danni Yang, Mo Xu, Zuofeng |
author_facet | Liang, Fengping Li, Xiang Ji, Qiao He, Danni Yang, Mo Xu, Zuofeng |
author_sort | Liang, Fengping |
collection | PubMed |
description | BACKGROUND: The incidence of thyroid lumps is more and more high in population, and most biopsies of thyroid nodules are benign. To develop a practical risk stratification system based on five ultrasound features to stratify the malignancy risk of thyroid neoplasms. METHODS: This retrospective investigation enrolled 999 consecutive patients with 1,236 thyroid nodules who underwent ultrasound screening. Fine-needle aspiration and/or surgery was performed, and pathology results were obtained at the Seventh Affiliated Hospital of Sun Yat-sen University in Shenzhen, China, which is a tertiary referral center, from May 2018 to February 2022. Each thyroid nodule’s score was calculated based on five ultrasound features: composition, echogenicity, shape, margin, and echogenic foci. Additionally, each nodule’s malignancy rate was calculated. The chi-square test was used to test whether the malignancy rate was different among the three subcategories (scores of 4–6, 7–8, and 9 or more) of thyroid nodules. We proposed the revised Thyroid Imaging Reporting and Data System (R-TIRADS), and its sensitivity and specificity were compared to the two existing systems [the American College of Radiology TIRADS (ACR TIRADS) and the Korean Society of Thyroid Radiology TIRADS (K-TIRADS)]. RESULTS: The final dataset consisted of 425 nodules from 370 patients. The malignancy rates of three subcategories [malignancy rate: 28.8% (scores from 4–6), 64.7% (scores from 7–8), and 84.2% (scores of 9 or more)] were significantly different (P<0.01). The unnecessary biopsy rates of the three systems (ACR TIRADS, R-TIRADS, and K-TIRADS) were 28.7%, 25.2%, and 14.8%, respectively. The R-TIRADS presented better diagnostic performance than the ACR TIRADS or K-TIRADS [area under the curve: 0.79 (95% CI: 0.74–0.83) vs. 0.69 (95% CI: 0.64–0.75), P=0.046; 0.79 (95% CI: 0.74–0.83) vs. 0.66 (95% CI: 0.60–0.71), P=0.041, respectively]. The R-TIRADS had the highest sensitivity [0.746 (95% CI: 0.689–0.803)], followed by the K-TIRADS [0.399 (95% CI: 0.335–0.463), P=0.000] and ACR TIRADS [0.377 (95% CI: 0.314–0.441), P=0.000]. CONCLUSIONS: The R-TIRADS enables radiologists to diagnose thyroid nodules efficiently, and the number of unnecessary fine-needle aspirations can be considerably reduced. |
format | Online Article Text |
id | pubmed-10240023 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-102400232023-06-06 Revised Thyroid Imaging Reporting and Data System (TIRADS): imitating the American College of Radiology TIRADS, a single-center retrospective study Liang, Fengping Li, Xiang Ji, Qiao He, Danni Yang, Mo Xu, Zuofeng Quant Imaging Med Surg Original Article BACKGROUND: The incidence of thyroid lumps is more and more high in population, and most biopsies of thyroid nodules are benign. To develop a practical risk stratification system based on five ultrasound features to stratify the malignancy risk of thyroid neoplasms. METHODS: This retrospective investigation enrolled 999 consecutive patients with 1,236 thyroid nodules who underwent ultrasound screening. Fine-needle aspiration and/or surgery was performed, and pathology results were obtained at the Seventh Affiliated Hospital of Sun Yat-sen University in Shenzhen, China, which is a tertiary referral center, from May 2018 to February 2022. Each thyroid nodule’s score was calculated based on five ultrasound features: composition, echogenicity, shape, margin, and echogenic foci. Additionally, each nodule’s malignancy rate was calculated. The chi-square test was used to test whether the malignancy rate was different among the three subcategories (scores of 4–6, 7–8, and 9 or more) of thyroid nodules. We proposed the revised Thyroid Imaging Reporting and Data System (R-TIRADS), and its sensitivity and specificity were compared to the two existing systems [the American College of Radiology TIRADS (ACR TIRADS) and the Korean Society of Thyroid Radiology TIRADS (K-TIRADS)]. RESULTS: The final dataset consisted of 425 nodules from 370 patients. The malignancy rates of three subcategories [malignancy rate: 28.8% (scores from 4–6), 64.7% (scores from 7–8), and 84.2% (scores of 9 or more)] were significantly different (P<0.01). The unnecessary biopsy rates of the three systems (ACR TIRADS, R-TIRADS, and K-TIRADS) were 28.7%, 25.2%, and 14.8%, respectively. The R-TIRADS presented better diagnostic performance than the ACR TIRADS or K-TIRADS [area under the curve: 0.79 (95% CI: 0.74–0.83) vs. 0.69 (95% CI: 0.64–0.75), P=0.046; 0.79 (95% CI: 0.74–0.83) vs. 0.66 (95% CI: 0.60–0.71), P=0.041, respectively]. The R-TIRADS had the highest sensitivity [0.746 (95% CI: 0.689–0.803)], followed by the K-TIRADS [0.399 (95% CI: 0.335–0.463), P=0.000] and ACR TIRADS [0.377 (95% CI: 0.314–0.441), P=0.000]. CONCLUSIONS: The R-TIRADS enables radiologists to diagnose thyroid nodules efficiently, and the number of unnecessary fine-needle aspirations can be considerably reduced. AME Publishing Company 2023-05-15 2023-06-01 /pmc/articles/PMC10240023/ /pubmed/37284080 http://dx.doi.org/10.21037/qims-22-1307 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 Liang, Fengping Li, Xiang Ji, Qiao He, Danni Yang, Mo Xu, Zuofeng Revised Thyroid Imaging Reporting and Data System (TIRADS): imitating the American College of Radiology TIRADS, a single-center retrospective study |
title | Revised Thyroid Imaging Reporting and Data System (TIRADS): imitating the American College of Radiology TIRADS, a single-center retrospective study |
title_full | Revised Thyroid Imaging Reporting and Data System (TIRADS): imitating the American College of Radiology TIRADS, a single-center retrospective study |
title_fullStr | Revised Thyroid Imaging Reporting and Data System (TIRADS): imitating the American College of Radiology TIRADS, a single-center retrospective study |
title_full_unstemmed | Revised Thyroid Imaging Reporting and Data System (TIRADS): imitating the American College of Radiology TIRADS, a single-center retrospective study |
title_short | Revised Thyroid Imaging Reporting and Data System (TIRADS): imitating the American College of Radiology TIRADS, a single-center retrospective study |
title_sort | revised thyroid imaging reporting and data system (tirads): imitating the american college of radiology tirads, a single-center retrospective study |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10240023/ https://www.ncbi.nlm.nih.gov/pubmed/37284080 http://dx.doi.org/10.21037/qims-22-1307 |
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