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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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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 |
Sumario: | 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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