Applicability of T1-weighted MRI in the assessment of forensic age based on the epiphyseal closure of the humeral head

Abstract

This work investigates the value of magnetic resonance imaging analysis of proximal epiphyseal fusion in research examining the growth and development of the humerus and its potential utility in establishing forensic age estimation. In this study, 428 proximal humeral epiphyses (patient age, 12-30 years) were evaluated with T1-weighted turbo spin echo (T1 TSE) sequences in coronal oblique orientation on shoulder MRI images. A scoring system was created following a combination of the Schmeling and Kellinghaus methods. Spearman's rank correlation analysis revealed a significant positive relationship between age and ossification stage of the proximal humeral epiphysis (all subjects: rho = 0.664, p < 0.001; males: 0.631, p < 0.001; females: rho = 0.651, p < 0.001). The intra- and inter-observer reliability assessed using Cohen's kappa statistic was κ = 0.898 and κ = 0.828, respectively. The earliest age of epiphysis closure was 17 years for females and 18 years for males. MRI of the proximal humeral epiphysis can be considered advantageous for forensic age estimation of living individuals in a variety of situations, ranging from monitoring public health to estimating the age of illegal immigrants/asylum seekers, minors engaged in criminal activities, and illegal participants in competitive sports, without the danger of radiation exposure.

Forensic age estimation via magnetic resonance imaging of knee in the Turkish population: use of T1-TSE sequence

“…All studies, except Jopp et al [19], used the Schmeling staging system and Kellinghaus's substages in the evaluation of the distal femoral epiphysis and proximal tibial epiphysis with T1-TSE sequence MRI. The Schmeling and Kellinghaus staging systems make use of a bone biology-based staging system, and its reproducibility and feasibility on X-ray and CT images, as well as MRI with T1 sequences, have been shown on various research projects [14][15][16][17][23][24][25]. Verified data on the trabecular architecture can be obtained with the T1-TSE sequence [28,29].…”

“…The system defined by Schmeling et al [21] and Kellinghaus et al [22], based on the anatomical staging of epiphyseal development, can be easily implemented with T1-weighted MRI sequences. In past T1-weighted MRI studies, on the evaluation of the distal femoral epiphysis [15][16][17], proximal tibial epiphysis [14,16,17,20], distal radial epiphysis [23,24], and proximal humeral epiphysis [25], the anatomical structure was successfully investigated by using the staging system defined by Schmeling et al [21] and Kellinghaus et al [22]. The results showed that the data obtained by MRI of the knee region is a potential supportive age estimation method for German and Chinese population [14][15][16][17]20].…”

Forensic age estimation based on fast spin-echo proton density (FSE PD)–weighted MRI of the distal radial epiphysis

“…Studies have assessed different epiphyseal areas using ultrasound and magnetic resonance imaging (MRI). For example, both modalities have been used to evaluate the development of distal radial epiphysis [6][7][8][9][10][11][12][13][14][15][16]; other studies have assessed the utility of measurements performed in the knee, ankle, elbow, clavicle, proximal humerus, and iliac crest [17][18][19][20][21][22][23][24][25][26][27][28][29].…”

The accuracy of age estimation from pulp chamber/crown volume ratio of canines obtained by cone beam computed tomography images: an Egyptian study

“…Precise age estimation is an important clue in criminal and civil events for both living and deceased persons. Legal decisions in many situations such as immigrants, refugees, competency to consent, criminal responsibility, and age falsification depend on the role of forensic practitioners in determining the age of living persons (Ekizoglu et al 2019). Besides, age identification has a crucial role in reconstructing the biological profile of unidentified dead bodies and body remains in case of mass disasters (Muñoz et al 2018).…”