Longitudinal visibility of MRI findings in living victims of strangulation.

Initial experiences with magnetic resonance imaging (MRI) of living strangulation victims demonstrated additional findings of internal injuries compared to the standard clinical forensic examination. However, existing studies on the use of MRI for this purpose mostly focused on the first 48 h after the incident. The aims of this study were (a) to evaluate the longitudinal visibility of MRI findings after violence against the neck by performing two MRI examinations within 12 days and a minimum of four days between both MRI scans and (b) to assess which MRI sequences were most helpful for the detection of injuries. Twenty strangulation victims participated in this study and underwent one (n = 8) or two (n = 12) MRI scans. The first MRI examination was conducted during the first five days, the second five to 12 days after the incident. Two blinded radiologists assessed the MRI data and looked for lesions in the structures of the neck. In total, 140 findings were reported in the 32 MRI examinations. Most of the findings were detected in the thyroid and the muscles of the neck. T2-weighted SPACE with fat suppression, T1-weighted TSE and T1-weighted MPRAGE were rated as the most helpful MRI sequences. Subjects who showed findings in the initial scan also demonstrated comparable results in the second scan, which was performed on average 8.4 days after the incident. Our results show that even up to 12 days after the incident, the criminal proceeding of strangulation cases may greatly profit from the information provided by an MRI examination of the neck in addition to the standard clinical forensic examination.

What automated age estimation of hand and wrist MRI data tells us about skeletal maturation in male adolescents.

BACKGROUND: Age estimation of individuals is important in human biology and has various medical and forensic applications. Recent interest in MR-based methods aims to investigate alternatives for established methods involving ionising radiation. Automatic, software-based methods additionally promise improved estimation objectivity. AIM: To investigate how informative automatically selected image features are regarding their ability to discriminate age, by exploring a recently proposed software-based age estimation method for MR images of the left hand and wrist. SUBJECTS AND METHODS: One hundred and two MR datasets of left hand images are used to evaluate age estimation performance, consisting of bone and epiphyseal gap volume localisation, computation of one age regression model per bone mapping image features to age and fusion of individual bone age predictions to a final age estimate. RESULTS: Quantitative results of the software-based method show an age estimation performance with a mean absolute difference of 0.85 years (SD = 0.58 years) to chronological age, as determined by a cross-validation experiment. Qualitatively, it is demonstrated how feature selection works and which image features of skeletal maturation are automatically chosen to model the non-linear regression function. CONCLUSION: Feasibility of automatic age estimation based on MRI data is shown and selected image features are found to be informative for describing anatomical changes during physical maturation in male adolescents.

Fully automatic bone age estimation from left hand MR images.

There has recently been an increased demand in bone age estimation (BAE) of living individuals and human remains in legal medicine applications. A severe drawback of established BAE techniques based on X-ray images is radiation exposure, since many countries prohibit scanning involving ionizing radiation without diagnostic reasons. We propose a completely automated method for BAE based on volumetric hand MRI images. On our database of 56 male caucasian subjects between 13 and 19 years, we are able to estimate the subjects age with a mean difference of 0.85 ± 0.58 years compared to the chronological age, which is in line with radiologist results using established radiographic methods. We see this work as a promising first step towards a novel MRI based bone age estimation system, with the key benefits of lacking exposure to ionizing radiation and higher accuracy due to exploitation of volumetric data.