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 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.

A new implementation of digital X-ray radiogrammetry and reference curves of four indices of cortical bone for healthy European adults.

UNLABELLED: Digital X-ray radiogrammetry performs measurements on a hand radiograph in digital form. We present an improved implementation of the method and provide reference curves for four indices for the amount of bone. We collected 1662 hand radiographs of healthy subjects of age 9-100 years. PURPOSE: The digital X-ray radiogrammetry (DXR) method has been shown to be efficient for diagnosis of osteoporosis and for assessment of progression of rheumatoid arthritis. The aim of this work is to present a new DXR implementation and reference curves of four indices of cortical bone and to compare their relative SDs in healthy subjects at fixed age and gender. MATERIALS AND METHODS: A total of 1662 hand radiographs of healthy subjects of age 9-100 years were collected in Jena in 2001-2005. We also used a longitudinal study of 116 Danish children born in 1952 with on average 11 images taken over the age range 7 to 40 years. The new DXR method reconstructs the whole metacarpal contour so that the metacarpal lengths can be measured and used in two of the indices. The new DXR method automatically validates 97 % of the images and is implemented as a local server for PACS users. RESULTS: The Danish bone health index (BHI) data are consistent with the Jena data and also with the published BHI reference for healthy children. BHI is found to have smaller relative SD than the other three indices in the Jena cohort over the age range 20-80 years. CONCLUSION: The new DXR method is an extension of the existing BoneXpert method for children, which allows patients to be followed from childhood into adulthood with the same method. By making all four indices of cortical bone available within the same medical device, it becomes possible to decide which index has the best relation to fracture risk in future studies.