Forensic anthropologists tasked with identification of skeletal remains often have to set up new strategies to overcome the limitations of conventional individualizing markers. A sound acquaintance with non-metric traits is essential for a reliable distinction between normal variations and pathological or traumatic conditions, yet the role of cranial variants in the identification process is still somehow ill-defined. One hundred crania (50 males and 50 females) of known sex and age were selected from the Collezione Antropologica LABANOF (a documented contemporary skeletal collection) and non-metric traits were scored as present or absent and by side. The frequencies of 13 traits were used to calculate the compound probabilities to find an individual with an exact combination of cranial features in the worldwide population. The probabilities of the majority of the individuals (53%) are within the 1 out of 10 million–1 out of 1 million interval. However, a fair number of subjects (25%) of the sample have the probabilities falling into the 1 out of 1 billion–1 out of 100 million interval, while the probabilities of a small portion of the sample (10%) are less than 1 out of 1 billion. This pilot study illustrates that some combinations of cranial variants are quite rare and may represent potential evidence to discern presumptive identifications, when an appropriate set of traits is selected and antemortem data are available for comparison. However, further research on larger and various samples is needed to confirm or discard the use of combinations of cranial non-metric traits as individualizing markers.

In literature, 3D-3D superimposition has been widely recognized as a valid method for personal identification. However, very little information is available about possible variability due to differences in protocols of registration of 3D models and calculation of RMS (root mean square) point-to-point distance. Frontal sinuses from 50 CT scans were segmented twice through the ITK-SNAP software and grouped in two samples (1 and 2). Maximum breadth, height and volume were measured. 3D models belonging to the same subject were then superimposed one on each other in 50 matches. In addition, superimposition of 50 random mismatches was performed. For each superimposition, the procedure was repeated four times choosing different reference models both for registration and calculation of RMS. Differences in RMS value among protocols of registration and RMS calculation were assessed through paired Student’s t-test (p < 0.05). Possible correlations between differences in RMS among groups and differences in frontal sinus size between the superimposed models were analysed through calculation of Pearson’s correlation coefficient (p < 0.05). Results showed that RMS calculation did not yield significant differences according to which 3D model is used as reference; on the other hand, RMS values from registration procedure significantly differ according to which model is chosen as reference, but only in the mismatch group (p < 0.001). Differences in RMS value according to RMS calculation are dependent upon all the three measurements, whereas differences according to registration protocols were significantly related only with the breadth of frontal sinuses but only in mismatches (p < 0.001). In no case, superimpositions of RMS values were found between matches and mismatches. This article for the first time proves that the protocol of registration and calculation of RMS significantly influences the results of 3D-3D superimposition only in case of mismatches.

Bone age is an indicator of bone maturity and is useful for the treatment of different pediatric conditions as well as for legal issues. Bone age can be assessed by the analysis of different skeletal segments and teeth and through several methods; however, traditional bone age assessment is a complicated and time-consuming process, prone to inter- and intra-observer variability. There is a high demand for fully automated systems, but creating an accurate and reliable solution has proven difficult. Deep learning technology, machine learning, and Convolutional Neural Networks-based systems, which are rapidly evolving, have shown promising results in automated bone age assessment. We provide the background of bone age estimation, its usefulness and traditional methods of assessment, and review the currently artificial-intelligence-based solutions for bone age assessment and the future perspectives of these applications.

Paranasal sinuses represent one of the most individualizing structures of the human body and some of them have been already analyzed for possible applications to personal identification, such as the frontal and sphenoid sinuses. This study explores the application of 3D–3D superimposition to maxillary sinuses in personal identification. One hundred head CT-scans of adult subjects (equally divided among males and females) were extracted from a hospital database. Maxillary sinuses were segmented twice from each subject through ITK-SNAP software and the correspondent 3D models were automatically superimposed to obtain 100 matches (when they belonged to the same person) and 100 mismatches (when they were extracted from different individuals), both from the right and left side. Average RMS (root mean square) point-to-point distance was then calculated for all the superimpositions; differences according to sex, side, and group (matches and mismatches) were assessed through three-way ANOVA test (p < 0.017). On average, RMS values were lower in matches (0.26 ± 0.19 mm in males, 0.24 ± 0.18 mm in females) than in mismatches (2.44 ± 0.87 mm in males, 2.20 ± 0.73 mm in females) with a significant difference (p < 0.001). No significant differences were found according to sex or side (p > 0.017). The study verified the potential of maxillary sinuses as reliable anatomical structures for personal identification in the forensic context.

Forensic anthropology (FA) has grown significantly as a well‐established and independent discipline dedicated to the examination and identification of human remains in medicolegal and humanitarian contexts. When soft tissues are highly decomposed, skeletal analysis often provides more reliable data for reconstructing biological profiles and determining identity. The increasing number of unidentified decedents in both domestic and humanitarian scenarios highlights the need for forensic anthropologists. In this context, molecular anthropology (MA) could support FA by offering additional tools for forensic identification, although collaboration between these two fields remains uncommon. Drawing from the authors’ experience, this review emphasizes the value of collaboration to enhance case resolution. This review shows that when FA encounters limitations, MA may provide critical insight to address unanswered questions. Although the full integration of FA and MA has yet to be realized, combining the strengths of both fields allows for the creation of more comprehensive biological profiles, thus significantly improving the chances of identifying unknown remains. This interdisciplinary approach broadens FA's scope and drives the development of innovative techniques and methodologies, advancing the pursuit of truth and justice.