Correlation

Internal medicine

Neurology

Neuroradiology

Nuclear medicine

Mathematics

Algorithm

Statistics

Psychiatry

Mean squared error

Machine learning

Absolute deviation

Political science

Artificial intelligence

Geometry

Computer science

Reading (process)

Medicine

Bone age

European Radiology Experimental

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 &lt; 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 &lt; 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.

Artificial intelligence in bone age assessment: accuracy and efficiency of a novel fully automated algorithm compared to the Greulich-Pyle method