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Artificial intelligence system can achieve comparable results to experts for bone age assessment of Chinese children with abnormal growth and development
OBJECTIVE: Bone age (BA) is a crucial indicator for revealing the growth and development of children. This study tested the performance of a fully automated artificial intelligence (AI) system for BA assessment of Chinese children with abnormal growth and development. MATERIALS AND METHODS: A fully...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7127473/ https://www.ncbi.nlm.nih.gov/pubmed/32274267 http://dx.doi.org/10.7717/peerj.8854 |
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author | Wang, Fengdan Gu, Xiao Chen, Shi Liu, Yongliang Shen, Qing Pan, Hui Shi, Lei Jin, Zhengyu |
author_facet | Wang, Fengdan Gu, Xiao Chen, Shi Liu, Yongliang Shen, Qing Pan, Hui Shi, Lei Jin, Zhengyu |
author_sort | Wang, Fengdan |
collection | PubMed |
description | OBJECTIVE: Bone age (BA) is a crucial indicator for revealing the growth and development of children. This study tested the performance of a fully automated artificial intelligence (AI) system for BA assessment of Chinese children with abnormal growth and development. MATERIALS AND METHODS: A fully automated AI system based on the Greulich and Pyle (GP) method was developed for Chinese children by using 8,000 BA radiographs from five medical centers nationwide in China. Then, a total of 745 cases (360 boys and 385 girls) with abnormal growth and development from another tertiary medical center of north China were consecutively collected between January and October 2018 to test the system. The reference standard was defined as the result interpreted by two experienced reviewers (a radiologist with 10 years and an endocrinologist with 15 years of experience in BA reading) through consensus using the GP atlas. BA accuracy within 1 year, root mean square error (RMSE), mean absolute difference (MAD), and 95% limits of agreement according to the Bland-Altman plot were statistically calculated. RESULTS: For Chinese pediatric patients with abnormal growth and development, the accuracy of this new automated AI system within 1 year was 84.60% as compared to the reference standard, with the highest percentage of 89.45% in the 12- to 18-year group. The RMSE, MAD, and 95% limits of agreement of the AI system were 0.76 years, 0.58 years, and −1.547 to 1.428, respectively, according to the Bland-Altman plot. The largest difference between the AI and experts’ BA result was noted for patients of short stature with bone deformities, severe osteomalacia, or different rates of maturation of the carpals and phalanges. CONCLUSIONS: The developed automated AI system could achieve comparable BA results to experienced reviewers for Chinese children with abnormal growth and development. |
format | Online Article Text |
id | pubmed-7127473 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71274732020-04-09 Artificial intelligence system can achieve comparable results to experts for bone age assessment of Chinese children with abnormal growth and development Wang, Fengdan Gu, Xiao Chen, Shi Liu, Yongliang Shen, Qing Pan, Hui Shi, Lei Jin, Zhengyu PeerJ Pediatrics OBJECTIVE: Bone age (BA) is a crucial indicator for revealing the growth and development of children. This study tested the performance of a fully automated artificial intelligence (AI) system for BA assessment of Chinese children with abnormal growth and development. MATERIALS AND METHODS: A fully automated AI system based on the Greulich and Pyle (GP) method was developed for Chinese children by using 8,000 BA radiographs from five medical centers nationwide in China. Then, a total of 745 cases (360 boys and 385 girls) with abnormal growth and development from another tertiary medical center of north China were consecutively collected between January and October 2018 to test the system. The reference standard was defined as the result interpreted by two experienced reviewers (a radiologist with 10 years and an endocrinologist with 15 years of experience in BA reading) through consensus using the GP atlas. BA accuracy within 1 year, root mean square error (RMSE), mean absolute difference (MAD), and 95% limits of agreement according to the Bland-Altman plot were statistically calculated. RESULTS: For Chinese pediatric patients with abnormal growth and development, the accuracy of this new automated AI system within 1 year was 84.60% as compared to the reference standard, with the highest percentage of 89.45% in the 12- to 18-year group. The RMSE, MAD, and 95% limits of agreement of the AI system were 0.76 years, 0.58 years, and −1.547 to 1.428, respectively, according to the Bland-Altman plot. The largest difference between the AI and experts’ BA result was noted for patients of short stature with bone deformities, severe osteomalacia, or different rates of maturation of the carpals and phalanges. CONCLUSIONS: The developed automated AI system could achieve comparable BA results to experienced reviewers for Chinese children with abnormal growth and development. PeerJ Inc. 2020-04-01 /pmc/articles/PMC7127473/ /pubmed/32274267 http://dx.doi.org/10.7717/peerj.8854 Text en ©2020 Wang et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Pediatrics Wang, Fengdan Gu, Xiao Chen, Shi Liu, Yongliang Shen, Qing Pan, Hui Shi, Lei Jin, Zhengyu Artificial intelligence system can achieve comparable results to experts for bone age assessment of Chinese children with abnormal growth and development |
title | Artificial intelligence system can achieve comparable results to experts for bone age assessment of Chinese children with abnormal growth and development |
title_full | Artificial intelligence system can achieve comparable results to experts for bone age assessment of Chinese children with abnormal growth and development |
title_fullStr | Artificial intelligence system can achieve comparable results to experts for bone age assessment of Chinese children with abnormal growth and development |
title_full_unstemmed | Artificial intelligence system can achieve comparable results to experts for bone age assessment of Chinese children with abnormal growth and development |
title_short | Artificial intelligence system can achieve comparable results to experts for bone age assessment of Chinese children with abnormal growth and development |
title_sort | artificial intelligence system can achieve comparable results to experts for bone age assessment of chinese children with abnormal growth and development |
topic | Pediatrics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7127473/ https://www.ncbi.nlm.nih.gov/pubmed/32274267 http://dx.doi.org/10.7717/peerj.8854 |
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