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Re-Assessment of Applicability of Greulich and Pyle-Based Bone Age to Korean Children Using Manual and Deep Learning-Based Automated Method

PURPOSE: To evaluate the applicability of Greulich-Pyle (GP) standards to bone age (BA) assessment in healthy Korean children using manual and deep learning-based methods. MATERIALS AND METHODS: We collected 485 hand radiographs of healthy children aged 2–17 years (262 boys) between 2008 and 2017. B...

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Autores principales: Hwang, Jisun, Yoon, Hee Mang, Hwang, Jae-Yeon, Kim, Pyeong Hwa, Bak, Boram, Bae, Byeong Uk, Sung, Jinkyeong, Kim, Hwa Jung, Jung, Ah Young, Cho, Young Ah, Lee, Jin Seong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Yonsei University College of Medicine 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9226834/
https://www.ncbi.nlm.nih.gov/pubmed/35748080
http://dx.doi.org/10.3349/ymj.2022.63.7.683
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author Hwang, Jisun
Yoon, Hee Mang
Hwang, Jae-Yeon
Kim, Pyeong Hwa
Bak, Boram
Bae, Byeong Uk
Sung, Jinkyeong
Kim, Hwa Jung
Jung, Ah Young
Cho, Young Ah
Lee, Jin Seong
author_facet Hwang, Jisun
Yoon, Hee Mang
Hwang, Jae-Yeon
Kim, Pyeong Hwa
Bak, Boram
Bae, Byeong Uk
Sung, Jinkyeong
Kim, Hwa Jung
Jung, Ah Young
Cho, Young Ah
Lee, Jin Seong
author_sort Hwang, Jisun
collection PubMed
description PURPOSE: To evaluate the applicability of Greulich-Pyle (GP) standards to bone age (BA) assessment in healthy Korean children using manual and deep learning-based methods. MATERIALS AND METHODS: We collected 485 hand radiographs of healthy children aged 2–17 years (262 boys) between 2008 and 2017. Based on GP method, BA was assessed manually by two radiologists and automatically by two deep learning-based BA assessment (DLBAA), which estimated GP-assigned (original model) and optimal (modified model) BAs. Estimated BA was compared to chronological age (CA) using intraclass correlation (ICC), Bland-Altman analysis, linear regression, mean absolute error, and root mean square error. The proportion of children showing a difference >12 months between the estimated BA and CA was calculated. RESULTS: CA and all estimated BA showed excellent agreement (ICC ≥0.978, p<0.001) and significant positive linear correlations (R(2)≥0.935, p<0.001). The estimated BA of all methods showed systematic bias and tended to be lower than CA in younger patients, and higher than CA in older patients (regression slopes ≤-0.11, p<0.001). The mean absolute error of radiologist 1, radiologist 2, original, and modified DLBAA models were 13.09, 13.12, 11.52, and 11.31 months, respectively. The difference between estimated BA and CA was >12 months in 44.3%, 44.5%, 39.2%, and 36.1% for radiologist 1, radiologist 2, original, and modified DLBAA models, respectively. CONCLUSION: Contemporary healthy Korean children showed different rates of skeletal development than GP standard-BA, and systemic bias should be considered when determining children’s skeletal maturation.
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spelling pubmed-92268342022-07-07 Re-Assessment of Applicability of Greulich and Pyle-Based Bone Age to Korean Children Using Manual and Deep Learning-Based Automated Method Hwang, Jisun Yoon, Hee Mang Hwang, Jae-Yeon Kim, Pyeong Hwa Bak, Boram Bae, Byeong Uk Sung, Jinkyeong Kim, Hwa Jung Jung, Ah Young Cho, Young Ah Lee, Jin Seong Yonsei Med J Original Article PURPOSE: To evaluate the applicability of Greulich-Pyle (GP) standards to bone age (BA) assessment in healthy Korean children using manual and deep learning-based methods. MATERIALS AND METHODS: We collected 485 hand radiographs of healthy children aged 2–17 years (262 boys) between 2008 and 2017. Based on GP method, BA was assessed manually by two radiologists and automatically by two deep learning-based BA assessment (DLBAA), which estimated GP-assigned (original model) and optimal (modified model) BAs. Estimated BA was compared to chronological age (CA) using intraclass correlation (ICC), Bland-Altman analysis, linear regression, mean absolute error, and root mean square error. The proportion of children showing a difference >12 months between the estimated BA and CA was calculated. RESULTS: CA and all estimated BA showed excellent agreement (ICC ≥0.978, p<0.001) and significant positive linear correlations (R(2)≥0.935, p<0.001). The estimated BA of all methods showed systematic bias and tended to be lower than CA in younger patients, and higher than CA in older patients (regression slopes ≤-0.11, p<0.001). The mean absolute error of radiologist 1, radiologist 2, original, and modified DLBAA models were 13.09, 13.12, 11.52, and 11.31 months, respectively. The difference between estimated BA and CA was >12 months in 44.3%, 44.5%, 39.2%, and 36.1% for radiologist 1, radiologist 2, original, and modified DLBAA models, respectively. CONCLUSION: Contemporary healthy Korean children showed different rates of skeletal development than GP standard-BA, and systemic bias should be considered when determining children’s skeletal maturation. Yonsei University College of Medicine 2022-07 2022-06-14 /pmc/articles/PMC9226834/ /pubmed/35748080 http://dx.doi.org/10.3349/ymj.2022.63.7.683 Text en © Copyright: Yonsei University College of Medicine 2022 https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Hwang, Jisun
Yoon, Hee Mang
Hwang, Jae-Yeon
Kim, Pyeong Hwa
Bak, Boram
Bae, Byeong Uk
Sung, Jinkyeong
Kim, Hwa Jung
Jung, Ah Young
Cho, Young Ah
Lee, Jin Seong
Re-Assessment of Applicability of Greulich and Pyle-Based Bone Age to Korean Children Using Manual and Deep Learning-Based Automated Method
title Re-Assessment of Applicability of Greulich and Pyle-Based Bone Age to Korean Children Using Manual and Deep Learning-Based Automated Method
title_full Re-Assessment of Applicability of Greulich and Pyle-Based Bone Age to Korean Children Using Manual and Deep Learning-Based Automated Method
title_fullStr Re-Assessment of Applicability of Greulich and Pyle-Based Bone Age to Korean Children Using Manual and Deep Learning-Based Automated Method
title_full_unstemmed Re-Assessment of Applicability of Greulich and Pyle-Based Bone Age to Korean Children Using Manual and Deep Learning-Based Automated Method
title_short Re-Assessment of Applicability of Greulich and Pyle-Based Bone Age to Korean Children Using Manual and Deep Learning-Based Automated Method
title_sort re-assessment of applicability of greulich and pyle-based bone age to korean children using manual and deep learning-based automated method
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9226834/
https://www.ncbi.nlm.nih.gov/pubmed/35748080
http://dx.doi.org/10.3349/ymj.2022.63.7.683
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