TY  - JOUR
A1  - Booz, Christian
A1  - Yel, Ibrahim
A1  - Wichmann, Julian
A1  - Böttger, Sabine
A1  - Al Kamali, Ahmed
A1  - Albrecht, Moritz Hans Ernst
A1  - Martin, Simon S.
A1  - Lenga, Lukas Fabian
A1  - Huizinga, Nicole A.
A1  - D’Angelo, Tommaso
A1  - Cavallaro, Marco
A1  - Vogl, Thomas J.
A1  - Bodelle, Boris
T1  - Artificial intelligence in bone age assessment: accuracy and efficiency of a novel fully automated algorithm compared to the Greulich-Pyle method
T2  - European radiology experimental
N2  - Background: Bone age (BA) assessment performed by artificial intelligence (AI) is of growing interest due to improved accuracy, precision and time efficiency in daily routine. The aim of this study was to investigate the accuracy and efficiency of a novel AI software version for automated BA assessment in comparison to the Greulich-Pyle method.
Methods: Radiographs of 514 patients were analysed in this retrospective study. Total BA was assessed independently by three blinded radiologists applying the GP method and by the AI software. Overall and gender-specific BA assessment results, as well as reading times of both approaches, were compared, while the reference BA was defined by two blinded experienced paediatric radiologists in consensus by application of the Greulich-Pyle method.
Results: Mean absolute deviation (MAD) and root mean square deviation (RSMD) were significantly lower between AI-derived BA and reference BA (MAD 0.34 years, RSMD 0.38 years) than between reader-calculated BA and reference BA (MAD 0.79 years, RSMD 0.89 years; p < 0.001). The correlation between AI-derived BA and reference BA (r = 0.99) was significantly higher than between reader-calculated BA and reference BA (r = 0.90; p < 0.001). No statistical difference was found in reader agreement and correlation analyses regarding gender (p = 0.241). Mean reading times were reduced by 87% using the AI system.
Conclusions: A novel AI software enabled highly accurate automated BA assessment. It may improve efficiency in clinical routine by reducing reading times without compromising the accuracy compared with the Greulich-Pyle method.
KW  - Age determination by skeleton
KW  - Algorithms
KW  - Artificial intelligence
KW  - Image processing (computer-assisted)
KW  - Retrospective studies
Y1  - 2020
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/53121
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-531214
SN  - 2509-9280
N1  - Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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.
VL  - 4
IS  - 1, Art. 6
SP  - 1
EP  - 8
PB  - Springer International Publishing
CY  - [Cham]
ER  -