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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Main Authors: Ewelina Szczepanek-Parulska, Kosma Wolinski, Katarzyna Dobruch-Sobczak, Patrycja Antosik, Anna Ostalowska, Agnieszka Krauze, Bartosz Migda, Agnieszka Zylka, Malgorzata Lange-Ratajczak, Tomasz Banasiewicz, Marek Dedecjus, Zbigniew Adamczewski, Rafal Z. Slapa, Robert K. Mlosek, Andrzej Lewinski, Marek Ruchala
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Journal of Clinical Medicine
Subjects:
Online Access:https://www.mdpi.com/2077-0383/9/8/2495
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author Ewelina Szczepanek-Parulska
Kosma Wolinski
Katarzyna Dobruch-Sobczak
Patrycja Antosik
Anna Ostalowska
Agnieszka Krauze
Bartosz Migda
Agnieszka Zylka
Malgorzata Lange-Ratajczak
Tomasz Banasiewicz
Marek Dedecjus
Zbigniew Adamczewski
Rafal Z. Slapa
Robert K. Mlosek
Andrzej Lewinski
Marek Ruchala
spellingShingle Ewelina Szczepanek-Parulska
Kosma Wolinski
Katarzyna Dobruch-Sobczak
Patrycja Antosik
Anna Ostalowska
Agnieszka Krauze
Bartosz Migda
Agnieszka Zylka
Malgorzata Lange-Ratajczak
Tomasz Banasiewicz
Marek Dedecjus
Zbigniew Adamczewski
Rafal Z. Slapa
Robert K. Mlosek
Andrzej Lewinski
Marek Ruchala
S-Detect Software vs. EU-TIRADS Classification: A Dual-Center Validation of Diagnostic Performance in Differentiation of Thyroid Nodules
Journal of Clinical Medicine
thyroid nodules
thyroid cancer
ultrasound
computer-aided diagnosis
S-Detect
EU-TIRADS
author_facet Ewelina Szczepanek-Parulska
Kosma Wolinski
Katarzyna Dobruch-Sobczak
Patrycja Antosik
Anna Ostalowska
Agnieszka Krauze
Bartosz Migda
Agnieszka Zylka
Malgorzata Lange-Ratajczak
Tomasz Banasiewicz
Marek Dedecjus
Zbigniew Adamczewski
Rafal Z. Slapa
Robert K. Mlosek
Andrzej Lewinski
Marek Ruchala
author_sort Ewelina Szczepanek-Parulska
title 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_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_sort s-detect software vs. eu-tirads classification: a dual-center validation of diagnostic performance in differentiation of thyroid nodules
publisher MDPI AG
series Journal of Clinical Medicine
issn 2077-0383
publishDate 2020-08-01
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 (<i>p</i>-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.
topic thyroid nodules
thyroid cancer
ultrasound
computer-aided diagnosis
S-Detect
EU-TIRADS
url https://www.mdpi.com/2077-0383/9/8/2495
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spelling doaj-9566150cd1f04439b2ac7e9a68b586052020-11-25T02:38:08ZengMDPI AGJournal of Clinical Medicine2077-03832020-08-0192495249510.3390/jcm9082495S-Detect Software vs. EU-TIRADS Classification: A Dual-Center Validation of Diagnostic Performance in Differentiation of Thyroid NodulesEwelina Szczepanek-Parulska0Kosma Wolinski1Katarzyna Dobruch-Sobczak2Patrycja Antosik3Anna Ostalowska4Agnieszka Krauze5Bartosz Migda6Agnieszka Zylka7Malgorzata Lange-Ratajczak8Tomasz Banasiewicz9Marek Dedecjus10Zbigniew Adamczewski11Rafal Z. Slapa12Robert K. Mlosek13Andrzej Lewinski14Marek Ruchala15Department of Endocrinology, Metabolism and Internal Medicine, Poznan University of Medical Sciences, 60-355 Poznan, PolandDepartment of Endocrinology, Metabolism and Internal Medicine, Poznan University of Medical Sciences, 60-355 Poznan, PolandRadiology Department II, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, PolandDepartment of Endocrinology, Metabolism and Internal Medicine, Poznan University of Medical Sciences, 60-355 Poznan, PolandDepartment of Endocrinology, Metabolism and Internal Medicine, Poznan University of Medical Sciences, 60-355 Poznan, PolandDiagnostic Imaging Department, Medical University of Warsaw, 2nd Faculty of Medicine with the English Division and the Physiotherapy Division, 03-242 Warsaw, PolandDiagnostic Imaging Department, Medical University of Warsaw, 2nd Faculty of Medicine with the English Division and the Physiotherapy Division, 03-242 Warsaw, PolandDepartment of Oncological Endocrinology and Nuclear Medicine, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, PolandDepartment of General, Endocrinological, and Oncological Surgery and Gastrointestinal Oncology, Poznan University of Medical Sciences, 60-355 Poznan, PolandDepartment of General, Endocrinological, and Oncological Surgery and Gastrointestinal Oncology, Poznan University of Medical Sciences, 60-355 Poznan, PolandDepartment of Oncological Endocrinology and Nuclear Medicine, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, PolandDepartment of Endocrinology and Metabolic Diseases, Medical University of Lodz, 90-419 Lodz, PolandDiagnostic Imaging Department, Medical University of Warsaw, 2nd Faculty of Medicine with the English Division and the Physiotherapy Division, 03-242 Warsaw, PolandDiagnostic Imaging Department, Medical University of Warsaw, 2nd Faculty of Medicine with the English Division and the Physiotherapy Division, 03-242 Warsaw, PolandDepartment of Endocrinology and Metabolic Diseases, Medical University of Lodz, 90-419 Lodz, PolandDepartment of Endocrinology, Metabolism and Internal Medicine, Poznan University of Medical Sciences, 60-355 Poznan, PolandComputer-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 (<i>p</i>-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.https://www.mdpi.com/2077-0383/9/8/2495thyroid nodulesthyroid cancerultrasoundcomputer-aided diagnosisS-DetectEU-TIRADS