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Coreelman, H; De, Tobel, J; Widek, T; Urschler, M; Fieuws, S; Thevissen, PW; Verstraete, KL.
Magnetic resonance imaging for multi-factorial age estimation using Bayes' rule: a validation study in two independent samples.
Int J Legal Med. 2025;
Doi: 10.1007/s00414-025-03499-x
Web of Science
PubMed
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- Co-Autor*innen der Med Uni Graz
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Urschler Martin
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Widek Thomas
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- Abstract:
- OBJECTIVES: Multi-factorial age estimation (MFA) models have been developed based on Bayes' rule, combining MRI data of the third molars (T), left wrist (W) and/or both clavicles (C). Internal cross-validated performance was reported, but external validation is needed before bringing the approach into practice. This study aimed to validate these MFA models in two independent samples. METHODS: In the Ghent sample, W + C MRI was prospectively conducted in 108 healthy Caucasian volunteers (52 males, 56 females) aged 16 to 21 years. In the Graz sample, T + W + C MRI was prospectively conducted in 335 healthy Caucasian males aged 13 to 24 years. Development was staged and checked for intra-observer reliability, and age estimation performances were tested. RESULTS: Staging clavicles was most prone to intra-observer variability. Applying the W + C model to Ghent males rendered a mean absolute error of 1.55 years, a root mean square error of 1.90 years, 70.6% correctly categorised adults and 94.4% correctly categorised minors. In females, the results were 1.49 years, 1.83 years, 92.1% and 66.7%, respectively. Regarding the Graz sample, the W + C results were 1.66 years, 2.08 years, 94.7% and 80.7%, respectively. For the T + W + C model, the results were 1.41 years, 1.80 years, 95.2% and 81.5%, respectively. CONCLUSION: The T + W + C and W + C models rendered a similar accuracy of the point prediction of age in both validation samples. However, they bared a larger risk of wrongfully categorising a minor as an adult than reported for internal validation, stressing the importance of the prediction interval for age estimation in practice.
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