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Autonomous artificial intelligence in pediatric radiology: the use and perception of BoneXpert for bone age assessment
BACKGROUND: The autonomous artificial intelligence (AI) system for bone age rating (BoneXpert) was designed to be used in clinical radiology practice as an AI-replace tool, replacing the radiologist completely. OBJECTIVE: The aim of this study was to investigate how the tool is used in clinical prac...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9192461/ https://www.ncbi.nlm.nih.gov/pubmed/35224658 http://dx.doi.org/10.1007/s00247-022-05295-w |
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author | Thodberg, Hans Henrik Thodberg, Benjamin Ahlkvist, Joanna Offiah, Amaka C. |
author_facet | Thodberg, Hans Henrik Thodberg, Benjamin Ahlkvist, Joanna Offiah, Amaka C. |
author_sort | Thodberg, Hans Henrik |
collection | PubMed |
description | BACKGROUND: The autonomous artificial intelligence (AI) system for bone age rating (BoneXpert) was designed to be used in clinical radiology practice as an AI-replace tool, replacing the radiologist completely. OBJECTIVE: The aim of this study was to investigate how the tool is used in clinical practice. Are radiologists more inclined to use BoneXpert to assist rather than replace themselves, and how much time is saved? MATERIALS AND METHODS: We sent a survey consisting of eight multiple-choice questions to 282 radiologists in departments in Europe already using the software. RESULTS: The 97 (34%) respondents came from 18 countries. Their answers revealed that before installing the automated method, 83 (86%) of the respondents took more than 2 min per bone age rating; this fell to 20 (21%) respondents after installation. Only 17/97 (18%) respondents used BoneXpert to completely replace the radiologist; the rest used it to assist radiologists to varying degrees. For instance, 39/97 (40%) never overruled the automated reading, while 9/97 (9%) overruled more than 5% of the automated ratings. The majority 58/97 (60%) of respondents checked the radiographs themselves to exclude features of underlying disease. CONCLUSION: BoneXpert significantly reduces reporting times for bone age determination. However, radiographic analysis involves more than just determining bone age. It also involves identification of abnormalities, and for this reason, radiologists cannot be completely replaced. AI systems originally developed to replace the radiologist might be more suitable as AI assist tools, particularly if they have not been validated to work autonomously, including the ability to omit ratings when the image is outside the range of validity. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00247-022-05295-w. |
format | Online Article Text |
id | pubmed-9192461 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-91924612022-06-15 Autonomous artificial intelligence in pediatric radiology: the use and perception of BoneXpert for bone age assessment Thodberg, Hans Henrik Thodberg, Benjamin Ahlkvist, Joanna Offiah, Amaka C. Pediatr Radiol Original Article BACKGROUND: The autonomous artificial intelligence (AI) system for bone age rating (BoneXpert) was designed to be used in clinical radiology practice as an AI-replace tool, replacing the radiologist completely. OBJECTIVE: The aim of this study was to investigate how the tool is used in clinical practice. Are radiologists more inclined to use BoneXpert to assist rather than replace themselves, and how much time is saved? MATERIALS AND METHODS: We sent a survey consisting of eight multiple-choice questions to 282 radiologists in departments in Europe already using the software. RESULTS: The 97 (34%) respondents came from 18 countries. Their answers revealed that before installing the automated method, 83 (86%) of the respondents took more than 2 min per bone age rating; this fell to 20 (21%) respondents after installation. Only 17/97 (18%) respondents used BoneXpert to completely replace the radiologist; the rest used it to assist radiologists to varying degrees. For instance, 39/97 (40%) never overruled the automated reading, while 9/97 (9%) overruled more than 5% of the automated ratings. The majority 58/97 (60%) of respondents checked the radiographs themselves to exclude features of underlying disease. CONCLUSION: BoneXpert significantly reduces reporting times for bone age determination. However, radiographic analysis involves more than just determining bone age. It also involves identification of abnormalities, and for this reason, radiologists cannot be completely replaced. AI systems originally developed to replace the radiologist might be more suitable as AI assist tools, particularly if they have not been validated to work autonomously, including the ability to omit ratings when the image is outside the range of validity. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00247-022-05295-w. Springer Berlin Heidelberg 2022-02-28 2022 /pmc/articles/PMC9192461/ /pubmed/35224658 http://dx.doi.org/10.1007/s00247-022-05295-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Thodberg, Hans Henrik Thodberg, Benjamin Ahlkvist, Joanna Offiah, Amaka C. Autonomous artificial intelligence in pediatric radiology: the use and perception of BoneXpert for bone age assessment |
title | Autonomous artificial intelligence in pediatric radiology: the use and perception of BoneXpert for bone age assessment |
title_full | Autonomous artificial intelligence in pediatric radiology: the use and perception of BoneXpert for bone age assessment |
title_fullStr | Autonomous artificial intelligence in pediatric radiology: the use and perception of BoneXpert for bone age assessment |
title_full_unstemmed | Autonomous artificial intelligence in pediatric radiology: the use and perception of BoneXpert for bone age assessment |
title_short | Autonomous artificial intelligence in pediatric radiology: the use and perception of BoneXpert for bone age assessment |
title_sort | autonomous artificial intelligence in pediatric radiology: the use and perception of bonexpert for bone age assessment |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9192461/ https://www.ncbi.nlm.nih.gov/pubmed/35224658 http://dx.doi.org/10.1007/s00247-022-05295-w |
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