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Integration of Sonoelastography Into the TIRADS Lexicon Could Influence the Classification
Aim: Numerous TIRADS (Thyroid Image Reporting and Data System) classifications have been developed, and various ultrasound (US) parameters are employed in different countries. The aim of our study was to introduce risk classification and management in a native population based on the Guidelines of P...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6421271/ https://www.ncbi.nlm.nih.gov/pubmed/30915032 http://dx.doi.org/10.3389/fendo.2019.00127 |
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author | Dobruch-Sobczak, Katarzyna Sylwia Krauze, Agnieszka Migda, Bartosz Mlosek, Krzysztof Słapa, Rafał Zenon Bakuła-Zalewska, Elwira Adamczewski, Zbigniew Lewiński, Andrzej Jakubowski, Wiesław Dedecjus, Marek |
author_facet | Dobruch-Sobczak, Katarzyna Sylwia Krauze, Agnieszka Migda, Bartosz Mlosek, Krzysztof Słapa, Rafał Zenon Bakuła-Zalewska, Elwira Adamczewski, Zbigniew Lewiński, Andrzej Jakubowski, Wiesław Dedecjus, Marek |
author_sort | Dobruch-Sobczak, Katarzyna Sylwia |
collection | PubMed |
description | Aim: Numerous TIRADS (Thyroid Image Reporting and Data System) classifications have been developed, and various ultrasound (US) parameters are employed in different countries. The aim of our study was to introduce risk classification and management in a native population based on the Guidelines of Polish National Societies Diagnostics and Treatment of Thyroid Carcinoma but with the addition of sonoelastography. Materials and Methods: We examined prospectively 208 patients with 305 thyroid lesions employing B-mode ultrasound and sonoelastography (SE). Nodule composition, echogenicity, margins, shape, presence or absence of calcifications, thyroid capsule, nodule size were assessed using B-mode ultrasound. Moreover, sonoelastography results were presented using the Asteria scale. Results: In univariate analysis, the following US features were significantly associated with malignancy: >50% solid /solid component, marked hypoechogenicity, ill-defined margins, micro and macrocalcification, taller-than wide shape, no/partial halo pattern, infiltration of the capsule and an Asteria score of 4. Multivariate logistic regression analysis of B-mode features revealed that ill-defined margins (OR 10.77), markedly hypoechogenicity (OR 5.12), microcalcifications (OR 4.85), thyroid capsule infiltrations (OR 3.2), macrocalcifications (OR 3.01), and hard lesion in SE (OR 6.85) were associated with a higher Odds Ratio (OR) for malignancy. Multivariate logistic regression analysis revealed that combining two features increases the OR and the best combination was irregular margins and Asteria scale 4 (OR 20.21). Adding a third feature did not increase the OR. Conclusions: Sonoelastography increases the value risk of predicted malignancy, with consequent different approach to further clinical investigation and management. A solitary feature (Asteria 4) in a solid tumor can result in its categorization as TIRADS 4, but coexistence with high risk features allows it to be upgraded to TIRADS 5. The irregular margin was the strongest single feature which allowed for the assignment of a solid tumor into TIRADS 5 category. The highest accuracy was found by combining the features of age, margin, echogenicity (markedly hypoechoic), capsule infiltration, microcalcifications and sonoelastography (Asteria 3,4) of the tumors. |
format | Online Article Text |
id | pubmed-6421271 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-64212712019-03-26 Integration of Sonoelastography Into the TIRADS Lexicon Could Influence the Classification Dobruch-Sobczak, Katarzyna Sylwia Krauze, Agnieszka Migda, Bartosz Mlosek, Krzysztof Słapa, Rafał Zenon Bakuła-Zalewska, Elwira Adamczewski, Zbigniew Lewiński, Andrzej Jakubowski, Wiesław Dedecjus, Marek Front Endocrinol (Lausanne) Endocrinology Aim: Numerous TIRADS (Thyroid Image Reporting and Data System) classifications have been developed, and various ultrasound (US) parameters are employed in different countries. The aim of our study was to introduce risk classification and management in a native population based on the Guidelines of Polish National Societies Diagnostics and Treatment of Thyroid Carcinoma but with the addition of sonoelastography. Materials and Methods: We examined prospectively 208 patients with 305 thyroid lesions employing B-mode ultrasound and sonoelastography (SE). Nodule composition, echogenicity, margins, shape, presence or absence of calcifications, thyroid capsule, nodule size were assessed using B-mode ultrasound. Moreover, sonoelastography results were presented using the Asteria scale. Results: In univariate analysis, the following US features were significantly associated with malignancy: >50% solid /solid component, marked hypoechogenicity, ill-defined margins, micro and macrocalcification, taller-than wide shape, no/partial halo pattern, infiltration of the capsule and an Asteria score of 4. Multivariate logistic regression analysis of B-mode features revealed that ill-defined margins (OR 10.77), markedly hypoechogenicity (OR 5.12), microcalcifications (OR 4.85), thyroid capsule infiltrations (OR 3.2), macrocalcifications (OR 3.01), and hard lesion in SE (OR 6.85) were associated with a higher Odds Ratio (OR) for malignancy. Multivariate logistic regression analysis revealed that combining two features increases the OR and the best combination was irregular margins and Asteria scale 4 (OR 20.21). Adding a third feature did not increase the OR. Conclusions: Sonoelastography increases the value risk of predicted malignancy, with consequent different approach to further clinical investigation and management. A solitary feature (Asteria 4) in a solid tumor can result in its categorization as TIRADS 4, but coexistence with high risk features allows it to be upgraded to TIRADS 5. The irregular margin was the strongest single feature which allowed for the assignment of a solid tumor into TIRADS 5 category. The highest accuracy was found by combining the features of age, margin, echogenicity (markedly hypoechoic), capsule infiltration, microcalcifications and sonoelastography (Asteria 3,4) of the tumors. Frontiers Media S.A. 2019-03-11 /pmc/articles/PMC6421271/ /pubmed/30915032 http://dx.doi.org/10.3389/fendo.2019.00127 Text en Copyright © 2019 Dobruch-Sobczak, Krauze, Migda, Mlosek, Słapa, Bakuła-Zalewska, Adamczewski, Lewiński, Jakubowski and Dedecjus. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology Dobruch-Sobczak, Katarzyna Sylwia Krauze, Agnieszka Migda, Bartosz Mlosek, Krzysztof Słapa, Rafał Zenon Bakuła-Zalewska, Elwira Adamczewski, Zbigniew Lewiński, Andrzej Jakubowski, Wiesław Dedecjus, Marek Integration of Sonoelastography Into the TIRADS Lexicon Could Influence the Classification |
title | Integration of Sonoelastography Into the TIRADS Lexicon Could Influence the Classification |
title_full | Integration of Sonoelastography Into the TIRADS Lexicon Could Influence the Classification |
title_fullStr | Integration of Sonoelastography Into the TIRADS Lexicon Could Influence the Classification |
title_full_unstemmed | Integration of Sonoelastography Into the TIRADS Lexicon Could Influence the Classification |
title_short | Integration of Sonoelastography Into the TIRADS Lexicon Could Influence the Classification |
title_sort | integration of sonoelastography into the tirads lexicon could influence the classification |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6421271/ https://www.ncbi.nlm.nih.gov/pubmed/30915032 http://dx.doi.org/10.3389/fendo.2019.00127 |
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