AI-based bone age assessment versus forensic expert panel: agreement, sex bias, and ethical implications.

Journal: International journal of legal medicine
Published Date:

Abstract

BACKGROUND: Forensic age estimation is frequently requested when chronological age is unknown or contested. While automated bone age systems have been validated in clinical populations, their performance against committee-based forensic reference standards-and their compatibility with the AGFAD-compliant Mindestalter (minimum chronological age) framework-has not been systematically addressed in cases of unknown chronological age. METHODS: In this retrospective single-centre study, we investigated the technical agreement between BoneXpert and an institutional Forensic Expert Panel (FEP) -the legally recognised reference standard in Turkish forensic practice-rather than validating BoneXpert as a stand-alone forensic tool. Hand-wrist radiographs of 128 cases (44 males, 84 females; 2016-2024) were reassessed using the Greulich-Pyle atlas (FEP) and BoneXpert. Agreement and bias were analysed using pairedt-tests, intraclass correlation coefficients, and Bland-Altman plots. In addition, a complementary minimum-age threshold analysis was performed within the Mindestalter framework using the minimum chronological ages reported by Tisè et al. RESULTS: Excellent agreement was observed (overall ICC = 0.956; males 0.987; females 0.907). A small but significant bias (-0.24 years) indicated underestimation by BoneXpert, driven by female cases (-0.34 years; no significant bias in males). Under the Mindestalter framework, BoneXpert never classified a case as proven above a legal threshold when the FEP did not. Concordance was 93.8% (κ = 0.834) at the 14-year threshold and 80.5% (κ = 0.604) at the 15-year threshold. At the 18-year threshold, neither method could prove that the threshold had been reached using hand-wrist GP-based assessment alone. CONCLUSION: BoneXpert provides consistent and ethically conservative results but should be used only as a decision-support tool within a multidisciplinary expert-led workflow, in line with AGFAD recommendations.

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