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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...

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Autores principales: Dobruch-Sobczak, Katarzyna Sylwia, Krauze, Agnieszka, Migda, Bartosz, Mlosek, Krzysztof, Słapa, Rafał Zenon, Bakuła-Zalewska, Elwira, Adamczewski, Zbigniew, Lewiński, Andrzej, Jakubowski, Wiesław, Dedecjus, Marek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
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.
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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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