Three-dimensional dental analysis for sex estimation in the italian population: A pilot study based on a geometric morphometric and artificial neural network approach

Dental dimorphism can be used for discriminating sex in forensic contexts. Geometric morphometric analysis (GMA) allows the evaluation of the shape and size, separately, of uneven 3D objects. This study presents experiments using a novel combination of GMA and an artificial neural network (ANN) for sex classification, applied to premolars of Caucasian Italian adults (50 females and 50 males). General Procrustes superimposition (GPS) and the partial least square (PLS) method were performed, respectively, to study the shape variance between sexes and to eliminate landmark variations. The “set-aside” approach was used to assess the accuracy of the proposed neural networks. As the main findings of the pilot study, the proposed method applied to the first upper premolar correctly classified 90% of females and 73% of males of the test sample. The accuracy was 0.84 and 0.80 for the training and test samples, respectively. The sexual dimorphism resulting from GMA was low, although statistically significant. GMA combined with the ANN demonstrated better sex classification ability than previous odontometric or dental morphometric methods. Future research could overcome some limitations by considering a larger sample of subjects and other kinds of teeth and experimenting with the use of computer vision for automatic landmark positioning

Combining dental and skeletal evidence in age classification: Pilot study in a sample of Italian sub-adults

Background: Dental and skeletal maturation have proved to be reliable evidence for estimating age of children and prior studies and internationally accredited guidelines recommend to evaluate both evidence in the same subject to reduce error in age prediction. Nevertheless the ethical and legal justification of procedures that imply a double exposition of children stands as a relevant issue. This study aims to evaluate the accuracy of age estimation provided by a combination of skeletal and dental methods applied in the same sample of children. / Materials and methods: The sample consisted of 274 orthopantomographies and left hand-wrist X-rays of Italian children, (aged between 6 and 17 years) taken on the same day. Greulich and Pyle’s (GP), Tanner-Whitehouse’s version 3 (TW3) and Willems’ (W) and the Demirjian’s (D) methods were respectively applied for estimating skeletal and dental age. A combination of skeletal and dental age estimates through Linear Discriminant Analysis (LDA) is proposed to obtain a classifier respect to an age threshold. / Results: The combination of D and TW3 obtained an improvement of accuracy in classifying female subjects respect to the 12 years threshold respect to the original methods (from about 77% using either original methods to 83.3% combining TW3 + D) as well as a consistent reduction of false positives rate (from 17% to 21% for original methods to 5.6% with TW3 + D). For males the LDA classifier (based on TW3 and W) enable a small improvement in accuracy, whilst the decreasing of false positives was as noticeable as for females (from 17.6 to 14.1% for original methods to 6.2% combining TW3 + W). / Conclusions: Although the study is influenced by the limited size and the uneven age distribution of the sample, the present findings support the conclusion that age assessment procedures based on both dental and skeletal age estimation can improve the accuracy and reduce the occurrence of false positives

A Semi-Automatic Method on a Small Italian Sample for Estimating Sex Based on the Shape of the Crown of the Maxillary Posterior Teeth

Teeth are known to be reliable substrates for human identification and are endowed with significant sexual dimorphism not only in the size but also in the shape of the crowns. In the preliminary phase of our study (already published in 2021), a novel sex estimation method based on dental morphometric geometric (GMA) analysis combined with the artificial neural network (ANN) was developed and validated on a single dental element (first upper premolar) with an accuracy rate of 80%. This study aims to experiment and validate the combination of GMA-ANN on the upper first and second left premolars and the upper left first molar to obtain a reliable classification model based on the sexual dimorphic traits of multiple maxillary teeth of Caucasian Italian adults (115 males and 115 females). A general procrustes superimposition (GPS) and principal component analysis (PCA) were performed to study the shape variance between the sexes and to reduce the data variations. The "set-aside" approach was used to validate the accuracy of the proposed ANN. As the main findings, the proposed method correctly classified 94% of females and 68% of males from the test sample and the overall accuracy gained was 82%, higher than the odontometric methods that similarly consider multiple teeth. The shape variation between male and female premolars represents the best dimorphic feature compared with the first upper molar. Future research could overcome some limitations by considering a larger sample of subjects and experimenting with the use of computer vision for automatic landmark positioning and should verify the present evidence in samples with different ancestry

Structural Heart Alterations in Brugada Syndrome: Is it Really a Channelopathy? A Systematic Review

Brugada syndrome (BrS) is classified as an inherited cardiac channelopathy attributed to dysfunctional ion channels and/or associated proteins in cardiomyocytes rather than to structural heart alterations. However, hearts of some BrS patients exhibit slight histologic abnormalities, suggesting that BrS could be a phenotypic variant of arrhythmogenic cardiomyopathy. We performed a systematic review of the literature following Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement (PRISMA) criteria. Our comprehensive analysis of structural findings did not reveal enough definitive evidence for reclassification of BrS as a cardiomyopathy. The collection and comprehensive analysis of new cases with a definitive BrS diagnosis are needed to clarify whether some of these structural features may have key roles in the pathophysiological pathways associated with malignant arrhythmogenic episodes

Management of Medico-Legal Risks in Digital Health Era: A Scoping Review

Artificial intelligence needs big data to develop reliable predictions. Therefore, storing and processing health data is essential for the new diagnostic and decisional technologies but, at the same time, represents a risk for privacy protection. This scoping review is aimed at underlying the medico-legal and ethical implications of the main artificial intelligence applications to healthcare, also focusing on the issues of the COVID-19 era. Starting from a summary of the United States (US) and European Union (EU) regulatory frameworks, the current medico-legal and ethical challenges are discussed in general terms before focusing on the specific issues regarding informed consent, medical malpractice/cognitive biases, automation and interconnectedness of medical devices, diagnostic algorithms and telemedicine. We aim at underlying that education of physicians on the management of this (new) kind of clinical risks can enhance compliance with regulations and avoid legal risks for the healthcare professionals and institutions

European Council of Legal Medicine (ECLM) on-site inspection forms for forensic pathology, anthropology, odontology, genetics, entomology and toxicology for forensic and medico-legal scene and corpse investigation: the Parma form

Further to a previous publication by the European Council of Legal Medicine (ECLM) concerning on-site forensic and medico-legal scene and corpse investigation, this publication provides guidance for forensic medical specialists, pathologists and, where present, coroners’ activity at a scene of death inspection and to harmonize the procedures for a correct search, detection, collection, sampling and storage of all elements which may be useful as evidence, and ensure documentation of all these steps. This ECLM’s inspection form provides a checklist to be used on-site for the investigation of a corpse present at a crime or suspicious death scene. It permits the collection of all relevant data not only for the pathologist, but also for forensic anthropologists, odontologists, geneticists, entomologists and toxicologists, thus supporting a collaborative work approach. Detailed instructions for the completion of forms are provided

Clinical and Metagenomic Characterization of Neurological Infections of People With Human Immunodeficiency Virus in the Peruvian Amazon.

BACKGROUND: Neurological opportunistic infections cause significant morbidity and mortality in people with human immunodeficiency virus (HIV) but are difficult to diagnose. METHODS: One hundred forty people with HIV with acute neurological symptoms from Iquitos, Peru, were evaluated for cerebral toxoplasmosis with quantitative polymerase chain reaction (qPCR) of cerebrospinal fluid (CSF) and for cryptococcal meningitis with cryptococcal antigen test (CrAg) in serum or CSF. Differences between groups were assessed with standard statistical methods. A subset of samples was evaluated by metagenomic next-generation sequencing (mNGS) of CSF to compare standard diagnostics and identify additional diagnoses. RESULTS: Twenty-seven participants were diagnosed with cerebral toxoplasmosis by qPCR and 13 with cryptococcal meningitis by CrAg. Compared to participants without cerebral toxoplasmosis, abnormal Glasgow Coma Scale score (P = .05), unilateral focal motor signs (P = .01), positive Babinski reflex (P = .01), and multiple lesions on head computed tomography (CT) (P = .002) were associated with cerebral toxoplasmosis. Photophobia (P = .03) and absence of lesions on head CT (P = .02) were associated with cryptococcal meningitis. mNGS of 42 samples identified 8 cases of cerebral toxoplasmosis, 7 cases of cryptococcal meningitis, 5 possible cases of tuberculous meningitis, and incidental detections of hepatitis B virus (n = 1) and pegivirus (n = 1). mNGS had a positive percentage agreement of 71% and a negative percentage agreement of 91% with qPCR for T gondii. mNGS had a sensitivity of 78% and specificity of 100% for Cryptococcus diagnosis. CONCLUSIONS: An infection was diagnosed by any method in only 34% of participants, demonstrating the challenges of diagnosing neurological opportunistic infections in this population and highlighting the need for broader, more sensitive diagnostic tests for central nervous system infections