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Multi-Reader Multi-Case Study for Performance Evaluation of High-Risk Thyroid Ultrasound with Computer-Aided Detection

Physicians use sonographic characteristics as a reference for the possible diagnosis of thyroid cancers. The purpose of this study was to investigate whether physicians were more effective in their tentative diagnosis based on the information provided by a computer-aided detection (CAD) system. A co...

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Autores principales: Wu, Ming-Hsun, Chen, Kuen-Yuan, Shih, Shyang-Rong, Ho, Ming-Chih, Tai, Hao-Chih, Chang, King-Jen, Chen, Argon, Chen, Chiung-Nien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7072687/
https://www.ncbi.nlm.nih.gov/pubmed/32041119
http://dx.doi.org/10.3390/cancers12020373
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author Wu, Ming-Hsun
Chen, Kuen-Yuan
Shih, Shyang-Rong
Ho, Ming-Chih
Tai, Hao-Chih
Chang, King-Jen
Chen, Argon
Chen, Chiung-Nien
author_facet Wu, Ming-Hsun
Chen, Kuen-Yuan
Shih, Shyang-Rong
Ho, Ming-Chih
Tai, Hao-Chih
Chang, King-Jen
Chen, Argon
Chen, Chiung-Nien
author_sort Wu, Ming-Hsun
collection PubMed
description Physicians use sonographic characteristics as a reference for the possible diagnosis of thyroid cancers. The purpose of this study was to investigate whether physicians were more effective in their tentative diagnosis based on the information provided by a computer-aided detection (CAD) system. A computer compared software-defined and physician-adjusted tumor loci. A multicenter, multireader, and multicase (MRMC) study was designed to compare clinician performance without and with the use of CAD. Interobserver variability was also analyzed. Excellent, satisfactory, and poor segmentations were observed in 25.3%, 58.9%, and 15.8% of nodules, respectively. There were 200 patients with 265 nodules in the study set. Nineteen physicians scored the malignancy potential of the nodules. The average area under the curve (AUC) of all readers was 0.728 without CAD and significantly increased to 0.792 with CAD. The average standard deviation of the malignant potential score significantly decreased from 18.97 to 16.29. The mean malignant potential score significantly decreased from 35.01 to 31.24 for benign cases. With the CAD system, an additional 7.6% of malignant nodules would be suggested for further evaluation, and biopsy would not be recommended for an additional 10.8% of benign nodules. The results demonstrated that applying a CAD system would improve clinicians’ interpretations and lessen the variability in diagnosis. However, more studies are needed to explore the use of the CAD system in an actual ultrasound diagnostic situation where much more benign thyroid nodules would be seen.
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spelling pubmed-70726872020-03-19 Multi-Reader Multi-Case Study for Performance Evaluation of High-Risk Thyroid Ultrasound with Computer-Aided Detection Wu, Ming-Hsun Chen, Kuen-Yuan Shih, Shyang-Rong Ho, Ming-Chih Tai, Hao-Chih Chang, King-Jen Chen, Argon Chen, Chiung-Nien Cancers (Basel) Article Physicians use sonographic characteristics as a reference for the possible diagnosis of thyroid cancers. The purpose of this study was to investigate whether physicians were more effective in their tentative diagnosis based on the information provided by a computer-aided detection (CAD) system. A computer compared software-defined and physician-adjusted tumor loci. A multicenter, multireader, and multicase (MRMC) study was designed to compare clinician performance without and with the use of CAD. Interobserver variability was also analyzed. Excellent, satisfactory, and poor segmentations were observed in 25.3%, 58.9%, and 15.8% of nodules, respectively. There were 200 patients with 265 nodules in the study set. Nineteen physicians scored the malignancy potential of the nodules. The average area under the curve (AUC) of all readers was 0.728 without CAD and significantly increased to 0.792 with CAD. The average standard deviation of the malignant potential score significantly decreased from 18.97 to 16.29. The mean malignant potential score significantly decreased from 35.01 to 31.24 for benign cases. With the CAD system, an additional 7.6% of malignant nodules would be suggested for further evaluation, and biopsy would not be recommended for an additional 10.8% of benign nodules. The results demonstrated that applying a CAD system would improve clinicians’ interpretations and lessen the variability in diagnosis. However, more studies are needed to explore the use of the CAD system in an actual ultrasound diagnostic situation where much more benign thyroid nodules would be seen. MDPI 2020-02-06 /pmc/articles/PMC7072687/ /pubmed/32041119 http://dx.doi.org/10.3390/cancers12020373 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
Wu, Ming-Hsun
Chen, Kuen-Yuan
Shih, Shyang-Rong
Ho, Ming-Chih
Tai, Hao-Chih
Chang, King-Jen
Chen, Argon
Chen, Chiung-Nien
Multi-Reader Multi-Case Study for Performance Evaluation of High-Risk Thyroid Ultrasound with Computer-Aided Detection
title Multi-Reader Multi-Case Study for Performance Evaluation of High-Risk Thyroid Ultrasound with Computer-Aided Detection
title_full Multi-Reader Multi-Case Study for Performance Evaluation of High-Risk Thyroid Ultrasound with Computer-Aided Detection
title_fullStr Multi-Reader Multi-Case Study for Performance Evaluation of High-Risk Thyroid Ultrasound with Computer-Aided Detection
title_full_unstemmed Multi-Reader Multi-Case Study for Performance Evaluation of High-Risk Thyroid Ultrasound with Computer-Aided Detection
title_short Multi-Reader Multi-Case Study for Performance Evaluation of High-Risk Thyroid Ultrasound with Computer-Aided Detection
title_sort multi-reader multi-case study for performance evaluation of high-risk thyroid ultrasound with computer-aided detection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7072687/
https://www.ncbi.nlm.nih.gov/pubmed/32041119
http://dx.doi.org/10.3390/cancers12020373
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