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Accuracy and self-validation of automated bone age determination

The BoneXpert method for automated determination of bone age from hand X-rays was introduced in 2009 and is currently running in over 200 hospitals. The aim of this work is to present version 3 of the method and validate its accuracy and self-validation mechanism that automatically rejects an image...

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Autores principales: Martin, D. D., Calder, A. D., Ranke, M. B., Binder, G., Thodberg, H. H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9013398/
https://www.ncbi.nlm.nih.gov/pubmed/35430607
http://dx.doi.org/10.1038/s41598-022-10292-y
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author Martin, D. D.
Calder, A. D.
Ranke, M. B.
Binder, G.
Thodberg, H. H.
author_facet Martin, D. D.
Calder, A. D.
Ranke, M. B.
Binder, G.
Thodberg, H. H.
author_sort Martin, D. D.
collection PubMed
description The BoneXpert method for automated determination of bone age from hand X-rays was introduced in 2009 and is currently running in over 200 hospitals. The aim of this work is to present version 3 of the method and validate its accuracy and self-validation mechanism that automatically rejects an image if it is at risk of being analysed incorrectly. The training set included 14,036 images from the 2017 Radiological Society of North America (RSNA) Bone Age Challenge, 1642 images of normal Dutch and Californian children, and 8250 images from Tübingen from patients with Short Stature, Congenital Adrenal Hyperplasia and Precocious Puberty. The study resulted in a cross-validated root mean square (RMS) error in the Tübingen images of 0.62 y, compared to 0.72 y in the previous version. The RMS error on the RSNA test set of 200 images was 0.45 y relative to the average of six manual ratings. The self-validation mechanism rejected 0.4% of the RSNA images. 121 outliers among the self-validated images of the Tübingen study were rerated, resulting in 6 cases where BoneXpert deviated more than 1.5 years from the average of the three re-ratings, compared to 72 such cases for the original manual ratings. The accuracy of BoneXpert is clearly better than the accuracy of a single manual rating. The self-validation mechanism rejected very few images, typically with abnormal anatomy, and among the accepted images, there were 12 times fewer severe bone age errors than in manual ratings, suggesting that BoneXpert could be safer than manual rating.
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spelling pubmed-90133982022-04-21 Accuracy and self-validation of automated bone age determination Martin, D. D. Calder, A. D. Ranke, M. B. Binder, G. Thodberg, H. H. Sci Rep Article The BoneXpert method for automated determination of bone age from hand X-rays was introduced in 2009 and is currently running in over 200 hospitals. The aim of this work is to present version 3 of the method and validate its accuracy and self-validation mechanism that automatically rejects an image if it is at risk of being analysed incorrectly. The training set included 14,036 images from the 2017 Radiological Society of North America (RSNA) Bone Age Challenge, 1642 images of normal Dutch and Californian children, and 8250 images from Tübingen from patients with Short Stature, Congenital Adrenal Hyperplasia and Precocious Puberty. The study resulted in a cross-validated root mean square (RMS) error in the Tübingen images of 0.62 y, compared to 0.72 y in the previous version. The RMS error on the RSNA test set of 200 images was 0.45 y relative to the average of six manual ratings. The self-validation mechanism rejected 0.4% of the RSNA images. 121 outliers among the self-validated images of the Tübingen study were rerated, resulting in 6 cases where BoneXpert deviated more than 1.5 years from the average of the three re-ratings, compared to 72 such cases for the original manual ratings. The accuracy of BoneXpert is clearly better than the accuracy of a single manual rating. The self-validation mechanism rejected very few images, typically with abnormal anatomy, and among the accepted images, there were 12 times fewer severe bone age errors than in manual ratings, suggesting that BoneXpert could be safer than manual rating. Nature Publishing Group UK 2022-04-16 /pmc/articles/PMC9013398/ /pubmed/35430607 http://dx.doi.org/10.1038/s41598-022-10292-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Martin, D. D.
Calder, A. D.
Ranke, M. B.
Binder, G.
Thodberg, H. H.
Accuracy and self-validation of automated bone age determination
title Accuracy and self-validation of automated bone age determination
title_full Accuracy and self-validation of automated bone age determination
title_fullStr Accuracy and self-validation of automated bone age determination
title_full_unstemmed Accuracy and self-validation of automated bone age determination
title_short Accuracy and self-validation of automated bone age determination
title_sort accuracy and self-validation of automated bone age determination
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9013398/
https://www.ncbi.nlm.nih.gov/pubmed/35430607
http://dx.doi.org/10.1038/s41598-022-10292-y
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