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A Novel Tool for Collaborative and Blinded Orthopedic Image Analysis

Image analysis plays a central role in orthopedics and research but comes with many challenges, including anonymization, bias, and achieving efficient analyses using multiple independent observers. Appropriate software is still lacking. Tyche is a free online tool that displays images in a random or...

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Autores principales: Schippers, Philipp, Meurer, Andrea, Schnetz, Matthias, Ewald, Larissa, Ruckes, Christian, Hoffmann, Reinhard, Gramlich, Yves
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10532740/
https://www.ncbi.nlm.nih.gov/pubmed/37763209
http://dx.doi.org/10.3390/life13091805
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author Schippers, Philipp
Meurer, Andrea
Schnetz, Matthias
Ewald, Larissa
Ruckes, Christian
Hoffmann, Reinhard
Gramlich, Yves
author_facet Schippers, Philipp
Meurer, Andrea
Schnetz, Matthias
Ewald, Larissa
Ruckes, Christian
Hoffmann, Reinhard
Gramlich, Yves
author_sort Schippers, Philipp
collection PubMed
description Image analysis plays a central role in orthopedics and research but comes with many challenges, including anonymization, bias, and achieving efficient analyses using multiple independent observers. Appropriate software is still lacking. Tyche is a free online tool that displays images in a random order without showing any metadata. Additionally, when using Tyche, observers can store results in the same window, and the final results are immediately visible to the project manager. In this study, we compared results from Tyche with those from a validated tool. One hundred pelvic radiographs were analyzed separately by five orthopedic surgeons using both Tyche and the validated software. Common orthopedic measurement modalities and scores were determined. The methods were compared using intra-class correlations and Fleiss’ kappa coefficients as well as Bland–Altman plots. Significant correlations ranging from r = 0.17 (Kallgren and Lawrence Score) to r = 0.99 (area measurements) were calculated for inter- and intraobserver agreements between the two tools for all measurements. The Bland–Altman plots indicated the non-inferiority of either tool. The images were analyzed significantly faster when Tyche was used. We conclude that Tyche is a valid tool for use in orthopedic image analysis. Tyche could be utilized for determining inter- and intraobserver agreements, in multicenter studies and for score validations.
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spelling pubmed-105327402023-09-28 A Novel Tool for Collaborative and Blinded Orthopedic Image Analysis Schippers, Philipp Meurer, Andrea Schnetz, Matthias Ewald, Larissa Ruckes, Christian Hoffmann, Reinhard Gramlich, Yves Life (Basel) Article Image analysis plays a central role in orthopedics and research but comes with many challenges, including anonymization, bias, and achieving efficient analyses using multiple independent observers. Appropriate software is still lacking. Tyche is a free online tool that displays images in a random order without showing any metadata. Additionally, when using Tyche, observers can store results in the same window, and the final results are immediately visible to the project manager. In this study, we compared results from Tyche with those from a validated tool. One hundred pelvic radiographs were analyzed separately by five orthopedic surgeons using both Tyche and the validated software. Common orthopedic measurement modalities and scores were determined. The methods were compared using intra-class correlations and Fleiss’ kappa coefficients as well as Bland–Altman plots. Significant correlations ranging from r = 0.17 (Kallgren and Lawrence Score) to r = 0.99 (area measurements) were calculated for inter- and intraobserver agreements between the two tools for all measurements. The Bland–Altman plots indicated the non-inferiority of either tool. The images were analyzed significantly faster when Tyche was used. We conclude that Tyche is a valid tool for use in orthopedic image analysis. Tyche could be utilized for determining inter- and intraobserver agreements, in multicenter studies and for score validations. MDPI 2023-08-24 /pmc/articles/PMC10532740/ /pubmed/37763209 http://dx.doi.org/10.3390/life13091805 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Schippers, Philipp
Meurer, Andrea
Schnetz, Matthias
Ewald, Larissa
Ruckes, Christian
Hoffmann, Reinhard
Gramlich, Yves
A Novel Tool for Collaborative and Blinded Orthopedic Image Analysis
title A Novel Tool for Collaborative and Blinded Orthopedic Image Analysis
title_full A Novel Tool for Collaborative and Blinded Orthopedic Image Analysis
title_fullStr A Novel Tool for Collaborative and Blinded Orthopedic Image Analysis
title_full_unstemmed A Novel Tool for Collaborative and Blinded Orthopedic Image Analysis
title_short A Novel Tool for Collaborative and Blinded Orthopedic Image Analysis
title_sort novel tool for collaborative and blinded orthopedic image analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10532740/
https://www.ncbi.nlm.nih.gov/pubmed/37763209
http://dx.doi.org/10.3390/life13091805
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