Age estimation is a crucial element of forensic medicine to assess the chronological age of living individuals without or lacking valid legal documentation. Methods used in practice are labor-intensive, subjective, and frequently comprise radiation exposure. Recently, also non-invasive methods using magnetic resonance imaging (MRI) have evaluated and confirmed a correlation between growth plate ossification in long bones and the chronological age of young subjects. However, automated and user-independent approaches are required to perform reliable assessments on large datasets. The aim of this study was to develop a fully automated and computer-based method for age estimation based on 3D knee MRIs using machine learning. The proposed solution is based on three parts: image-preprocessing, bone segmentation, and age estimation. A total of 185 coronal and 404 sagittal MR volumes from Caucasian male subjects in the age range of 13 and 21 years were available. The best result of the fivefold cross-validation was a mean absolute error of 0.67 ± 0.49 years in age regression and an accuracy of 90.9%, a sensitivity of 88.6%, and a specificity of 94.2% in classification (18-year age limit) using a combination of convolutional neural networks and tree-based machine learning algorithms. The potential of deep learning for age estimation is reflected in the results and can be further improved if it is trained on even larger and more diverse datasets.

Purpose: To investigate the healthy pancreas with diffusion‐weighted imaging (DWI) for characterization of age and gender‐related differences in apparent diffusion coefficient (ADC) values.Materials and Methods: Sixty six volunteers were prospectively enrolled (33 male, 33 female; range 1.4 to 83.7 years of age) and echo‐planar DWI of the pancreas was performed. ADC values were measured in the pancreas head, body, and tail using a pixel‐by‐pixel approach. Effects of age and gender on ADC values were analyzed using a two‐factorial multivariate analysis of variance (MANOVA).Results: ADC values correlated inversely with the age of the volunteers. The mean global pancreatic ADC values (× 10⁻³ mm²/s) in the age groups 0–20 years, 21–40 years, and > 40 years were 1.18 ± 0.19, 1.07 ± 0.13, and 0.99 ± 0.18, respectively. Female individuals had higher mean global ADC values than male (1.13 ± 0.14 versus 1.02 ± 0.18 × 10⁻³ mm²/s). MANOVA showed significant effects of age (P value 0.022, eta² = 0.13) and gender (P value 0.001, eta² = 0.28) on ADC values.Conclusion: Pancreatic ADC values decline with ageing and show significant gender differences with higher mean values in females. The awareness of baseline values adjusted to age and gender will be important for correct interpretation of individual cases and design of future studies. J. Magn. Reson. Imaging 2013;37:886–891.

Anorectal and cloacal malformations are a broad mix of congenital abnormalities related to the distal rectum and anus. Confusion exists between all the forms in this large and heterogeneous group. The spectrum includes everything from anal stenosis, ventral anus, anal atresia (with and without fistula) and the full spectrum of cloacal malformations. Imaging in these conditions is done through the whole armamentarium of radiologic modalities, with very different imaging strategies seen across the centres where these conditions are managed. In 2017, the European Society of Paediatric Radiology (ESPR) abdominal imaging task force issued recommendations on the imaging algorithm and standards for imaging anorectal malformations. This was followed by further letters and clarifications together with an active multispecialty session on the different imaging modalities for anorectal malformations at the 2018 ESPR meeting in Berlin. Through this paper, the abdominal task force updates its guidelines and recommended imaging algorithm for anorectal malformations.

Objectives: To assess epiphyseal growth plate closure of the knee for forensic age estimation using an ultrasound (US)-based method and to compare the findings with MRI. Methods: Thirty-three healthy male individuals (age, 14.4–19.3 years) were prospectively evaluated for epiphyseal growth plate closure of the right knee by recordings of two-dimensional US volumes and a high-resolution T1-weighted MRI sequence. The degree of epiphyseal growth plate closure was rated independently by two readers for each method using a modality specific three-point scale that differentiates between an open physis (S1), a partially closed physis (S2), and a closed physis (S3). Results: The inter-rater agreement was high for the US (Cohen’s kappa (CK): femur 95.2%, tibia 81.3%, fibula 86.3%) and the MRI method (CK: femur 70.2%, tibia 90.8%, fibula 79.8%). The degree of growth plate closure associated positively with advancing age. The US system showed a clearer separation of median ages with lower overlap than the MRI system. Open growth plates on minors (< S3 on femur and tibia) were identified by US with higher sensitivity (1.0 vs. 0.7) and slightly lower specificity (0.7 vs. 0.85) compared with MRI. The examination time was substantially shorter on US than on MRI (2.65 ± 0.91 min vs. 24.72 ± 2.72 min; p < 0.001). Conclusions: The US method for evaluation of growth plate closure of the knee can reliably assign male individuals to different ossification stages and identifies minors with high accuracy. More studies with larger numbers are needed to further evaluate this method. Key Points: • US is feasible to determine the degree of epiphyseal growth plate closure of the knee, shows a high degree of reliability, and is comparable to MRI. • US of the knee can detect open growth plates on male minors with high accuracy. • US of the knee may be used as a fast, non-invasive imaging tool for forensic age estimation to identify male minors.