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  • Title: Magnetic resonance imaging of the sternal extremity of the clavicle in forensic age estimation: towards more sound age estimates.
    Author: Hillewig E, Degroote J, Van der Paelt T, Visscher A, Vandemaele P, Lutin B, D'Hooghe L, Vandriessche V, Piette M, Verstraete K.
    Journal: Int J Legal Med; 2013 May; 127(3):677-89. PubMed ID: 23224029.
    Abstract:
    OBJECTIVES: The development of the sternal extremity of the clavicle was examined prospectively with magnetic resonance imaging (MRI) for forensic bone age assessment. The objectives were to examine whether these results were comparable with the literature on plain radiography and CT, to provide age prediction intervals that correctly reflect the high variability in clavicular growth among individuals and to investigate whether MRI of the clavicle can be used to differentiate between individuals younger or older than 18 years. METHODS: The clavicles of 220 volunteers (16-26 years) were examined with 3-T MRI and evaluated according to the Schmeling and Kreitner classification (Schmeling, Int J Legal Med 118:5-8, 2004; Kreitner, Eur Radiol 8:1116-1122, 1998). An additional hand/wrist radiograph was taken and evaluated according to Greulich and Pyle (1959). After a descriptive analysis, a multivariate ordinal regression model was fitted and embedded in a Bayesian framework based on Thevissen et al. (Int J Legal Med 124:35-42, 2009). RESULTS: The descriptive results were concordant with the literature, although the Kreitner classification is recommended and simultaneous evaluation of the hand is considered a basic requirement (Schmeling, Int J Legal Med 118:5-8, 2004). The 95 % credibility interval for both genders with bilateral stage IV is 20-26 years. The corresponding estimated probability of being younger than 18 years is 0.8 % in females and 0.2 % in males. CONCLUSION: MRI of the sternal extremity of the clavicle can be used to differentiate between being younger or older than 18, but a simultaneous evaluation of the hand/wrist is essential. Future evaluation of the predictive performance of the model, using comparable but larger reference samples, is necessary to validate these results.
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