A critical comparative study of the performance of three AI-assisted programs for bone age determination.
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| Title: | A critical comparative study of the performance of three AI-assisted programs for bone age determination. |
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| Authors: | Pape, Johanna1 (AUTHOR), Rosolowski, Maciej2 (AUTHOR), Pfäffle, Roland3 (AUTHOR), Beeskow, Anne B.4 (AUTHOR), Gräfe, Daniel1 (AUTHOR) Daniel.Graefe@medizin.uni-leipzig.de |
| Source: | European Radiology. Mar2025, Vol. 35 Issue 3, p1190-1196. 7p. |
| Subjects: | Artificial intelligence, Standard deviations, Artificial bones, Accounting exams, Age groups |
| Abstract: | Objectives: To date, AI-supported programs for bone age (BA) determination for medical use in Europe have almost only been validated separately, according to Greulich and Pyle (G&P). Therefore, the current study aimed to compare the performance of three programs, namely BoneXpert, PANDA, and BoneView, on a single Central European population. Materials and methods: For this retrospective study, hand radiographs of 306 children aged 1–18 years, stratified by gender and age, were included. A subgroup consisting of the age group accounting for 90% of examinations in clinical practice was formed. The G&P BA was estimated by three human experts—as ground truth—and three AI-supported programs. The mean absolute deviation, the root mean squared error (RMSE), and dropouts by the AI were calculated. Results: The correlation between all programs and the ground truth was prominent (R2 ≥ 0.98). In the total group, BoneXpert had a lower RMSE than BoneView and PANDA (0.62 vs. 0.65 and 0.75 years) with a dropout rate of 2.3%, 20.3% and 0%, respectively. In the subgroup, there was less difference in RMSE (0.66 vs. 0.68 and 0.65 years, max. 4% dropouts). The standard deviation between the AI readers was lower than that between the human readers (0.54 vs. 0.62 years, p < 0.01). Conclusion: All three AI programs predict BA after G&P in the main age range with similar high reliability. Differences arise at the boundaries of childhood. Key Points: QuestionThere is a lack of comparative, independent validation for artificial intelligence-based bone age estimation in children. FindingsThree commercially available programs estimate bone age after Greulich and Pyle with similarly high reliability in a central European cohort. Clinical relevanceThe comparative study will help the reader choose a software for bone age estimation approved for the European market depending on the targeted age group and economic considerations. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Objectives: To date, AI-supported programs for bone age (BA) determination for medical use in Europe have almost only been validated separately, according to Greulich and Pyle (G&P). Therefore, the current study aimed to compare the performance of three programs, namely BoneXpert, PANDA, and BoneView, on a single Central European population. Materials and methods: For this retrospective study, hand radiographs of 306 children aged 1–18 years, stratified by gender and age, were included. A subgroup consisting of the age group accounting for 90% of examinations in clinical practice was formed. The G&P BA was estimated by three human experts—as ground truth—and three AI-supported programs. The mean absolute deviation, the root mean squared error (RMSE), and dropouts by the AI were calculated. Results: The correlation between all programs and the ground truth was prominent (R2 ≥ 0.98). In the total group, BoneXpert had a lower RMSE than BoneView and PANDA (0.62 vs. 0.65 and 0.75 years) with a dropout rate of 2.3%, 20.3% and 0%, respectively. In the subgroup, there was less difference in RMSE (0.66 vs. 0.68 and 0.65 years, max. 4% dropouts). The standard deviation between the AI readers was lower than that between the human readers (0.54 vs. 0.62 years, p < 0.01). Conclusion: All three AI programs predict BA after G&P in the main age range with similar high reliability. Differences arise at the boundaries of childhood. Key Points: QuestionThere is a lack of comparative, independent validation for artificial intelligence-based bone age estimation in children. FindingsThree commercially available programs estimate bone age after Greulich and Pyle with similarly high reliability in a central European cohort. Clinical relevanceThe comparative study will help the reader choose a software for bone age estimation approved for the European market depending on the targeted age group and economic considerations. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 09387994 |
| DOI: | 10.1007/s00330-024-11169-6 |
