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S-Detect Software vs. EU-TIRADS Classification: A Dual-Center Validation of Diagnostic Performance in Differentiation of Thyroid Nodules

Computer-aided diagnosis (CAD) and other risk stratification systems may improve ultrasound image interpretation. This prospective study aimed to compare the diagnostic performance of CAD and the European Thyroid Imaging Reporting and Data System (EU-TIRADS) classification applied by physicians with...

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Autores principales: Szczepanek-Parulska, Ewelina, Wolinski, Kosma, Dobruch-Sobczak, Katarzyna, Antosik, Patrycja, Ostalowska, Anna, Krauze, Agnieszka, Migda, Bartosz, Zylka, Agnieszka, Lange-Ratajczak, Malgorzata, Banasiewicz, Tomasz, Dedecjus, Marek, Adamczewski, Zbigniew, Slapa, Rafal Z., Mlosek, Robert K., Lewinski, Andrzej, Ruchala, Marek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7464710/
https://www.ncbi.nlm.nih.gov/pubmed/32756510
http://dx.doi.org/10.3390/jcm9082495
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author Szczepanek-Parulska, Ewelina
Wolinski, Kosma
Dobruch-Sobczak, Katarzyna
Antosik, Patrycja
Ostalowska, Anna
Krauze, Agnieszka
Migda, Bartosz
Zylka, Agnieszka
Lange-Ratajczak, Malgorzata
Banasiewicz, Tomasz
Dedecjus, Marek
Adamczewski, Zbigniew
Slapa, Rafal Z.
Mlosek, Robert K.
Lewinski, Andrzej
Ruchala, Marek
author_facet Szczepanek-Parulska, Ewelina
Wolinski, Kosma
Dobruch-Sobczak, Katarzyna
Antosik, Patrycja
Ostalowska, Anna
Krauze, Agnieszka
Migda, Bartosz
Zylka, Agnieszka
Lange-Ratajczak, Malgorzata
Banasiewicz, Tomasz
Dedecjus, Marek
Adamczewski, Zbigniew
Slapa, Rafal Z.
Mlosek, Robert K.
Lewinski, Andrzej
Ruchala, Marek
author_sort Szczepanek-Parulska, Ewelina
collection PubMed
description Computer-aided diagnosis (CAD) and other risk stratification systems may improve ultrasound image interpretation. This prospective study aimed to compare the diagnostic performance of CAD and the European Thyroid Imaging Reporting and Data System (EU-TIRADS) classification applied by physicians with S-Detect 2 software CAD based on Korean Thyroid Imaging Reporting and Data System (K-TIRADS) and combinations of both methods (MODELs 1 to 5). In all, 133 nodules from 88 patients referred to thyroidectomy with available histopathology or with unambiguous results of cytology were included. The S-Detect system, EU-TIRADS, and mixed MODELs 1–5 for the diagnosis of thyroid cancer showed a sensitivity of 89.4%, 90.9%, 84.9%, 95.5%, 93.9%, 78.9% and 93.9%; a specificity of 80.6%, 61.2%, 88.1%, 53.7%, 73.1%, 89.6% and 80.6%; a positive predictive value of 81.9%, 69.8%, 87.5%, 67%, 77.5%, 88.1% and 82.7%; a negative predictive value of 88.5%, 87.2%, 85.5%, 92.3%, 92.5%, 81.1% and 93.1%; and an accuracy of 85%, 75.9%, 86.5%, 74.4%, 83.5%, 84.2%, and 87.2%, respectively. Comparison showed superiority of the similar MODELs 1 and 5 over other mixed models as well as EU-TIRADS and S-Detect used alone (p-value < 0.05). S-Detect software is characterized with high sensitivity and good specificity, whereas EU-TIRADS has high sensitivity, but rather low specificity. The best diagnostic performance in malignant thyroid nodule (TN) risk stratification was obtained for the combined model of S-Detect (“possibly malignant” nodule) and simultaneously obtaining 4 or 5 points (MODEL 1) or exactly 5 points (MODEL 5) on the EU-TIRADS scale.
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spelling pubmed-74647102020-09-04 S-Detect Software vs. EU-TIRADS Classification: A Dual-Center Validation of Diagnostic Performance in Differentiation of Thyroid Nodules Szczepanek-Parulska, Ewelina Wolinski, Kosma Dobruch-Sobczak, Katarzyna Antosik, Patrycja Ostalowska, Anna Krauze, Agnieszka Migda, Bartosz Zylka, Agnieszka Lange-Ratajczak, Malgorzata Banasiewicz, Tomasz Dedecjus, Marek Adamczewski, Zbigniew Slapa, Rafal Z. Mlosek, Robert K. Lewinski, Andrzej Ruchala, Marek J Clin Med Article Computer-aided diagnosis (CAD) and other risk stratification systems may improve ultrasound image interpretation. This prospective study aimed to compare the diagnostic performance of CAD and the European Thyroid Imaging Reporting and Data System (EU-TIRADS) classification applied by physicians with S-Detect 2 software CAD based on Korean Thyroid Imaging Reporting and Data System (K-TIRADS) and combinations of both methods (MODELs 1 to 5). In all, 133 nodules from 88 patients referred to thyroidectomy with available histopathology or with unambiguous results of cytology were included. The S-Detect system, EU-TIRADS, and mixed MODELs 1–5 for the diagnosis of thyroid cancer showed a sensitivity of 89.4%, 90.9%, 84.9%, 95.5%, 93.9%, 78.9% and 93.9%; a specificity of 80.6%, 61.2%, 88.1%, 53.7%, 73.1%, 89.6% and 80.6%; a positive predictive value of 81.9%, 69.8%, 87.5%, 67%, 77.5%, 88.1% and 82.7%; a negative predictive value of 88.5%, 87.2%, 85.5%, 92.3%, 92.5%, 81.1% and 93.1%; and an accuracy of 85%, 75.9%, 86.5%, 74.4%, 83.5%, 84.2%, and 87.2%, respectively. Comparison showed superiority of the similar MODELs 1 and 5 over other mixed models as well as EU-TIRADS and S-Detect used alone (p-value < 0.05). S-Detect software is characterized with high sensitivity and good specificity, whereas EU-TIRADS has high sensitivity, but rather low specificity. The best diagnostic performance in malignant thyroid nodule (TN) risk stratification was obtained for the combined model of S-Detect (“possibly malignant” nodule) and simultaneously obtaining 4 or 5 points (MODEL 1) or exactly 5 points (MODEL 5) on the EU-TIRADS scale. MDPI 2020-08-03 /pmc/articles/PMC7464710/ /pubmed/32756510 http://dx.doi.org/10.3390/jcm9082495 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Szczepanek-Parulska, Ewelina
Wolinski, Kosma
Dobruch-Sobczak, Katarzyna
Antosik, Patrycja
Ostalowska, Anna
Krauze, Agnieszka
Migda, Bartosz
Zylka, Agnieszka
Lange-Ratajczak, Malgorzata
Banasiewicz, Tomasz
Dedecjus, Marek
Adamczewski, Zbigniew
Slapa, Rafal Z.
Mlosek, Robert K.
Lewinski, Andrzej
Ruchala, Marek
S-Detect Software vs. EU-TIRADS Classification: A Dual-Center Validation of Diagnostic Performance in Differentiation of Thyroid Nodules
title S-Detect Software vs. EU-TIRADS Classification: A Dual-Center Validation of Diagnostic Performance in Differentiation of Thyroid Nodules
title_full S-Detect Software vs. EU-TIRADS Classification: A Dual-Center Validation of Diagnostic Performance in Differentiation of Thyroid Nodules
title_fullStr S-Detect Software vs. EU-TIRADS Classification: A Dual-Center Validation of Diagnostic Performance in Differentiation of Thyroid Nodules
title_full_unstemmed S-Detect Software vs. EU-TIRADS Classification: A Dual-Center Validation of Diagnostic Performance in Differentiation of Thyroid Nodules
title_short S-Detect Software vs. EU-TIRADS Classification: A Dual-Center Validation of Diagnostic Performance in Differentiation of Thyroid Nodules
title_sort s-detect software vs. eu-tirads classification: a dual-center validation of diagnostic performance in differentiation of thyroid nodules
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7464710/
https://www.ncbi.nlm.nih.gov/pubmed/32756510
http://dx.doi.org/10.3390/jcm9082495
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