Computed tomography as a tool in the analysis of dentomaxillofacial characteristics for human identification: A bibliometric analysis of the most cited publications.

Abstract

Computed tomography has become an important tool in human identification, supporting comparative and reconstructive approaches. This study aimed to analyze the scientific literature on the use of computed tomography in human identification, focusing on publication trends, collaboration networks, and key themes to understand the field's evolution. A bibliometric review was conducted following the Guideline for Reporting Bibliometric Reviews of the Biomedical Literature (BIBLIO). An electronic search was conducted in the Web of Science Core Collection. Records were ranked by citation count, and the most-cited articles were screened. Extracted data comprised authorship, country, publication year, journal, impact factor, study design, institution, keywords, citations, and research topic. Reviewer agreement was assessed with the Kappa coefficient (κ ≥ 0.81). Bibliometric analyses were performed in Power BI, and Spearman's correlation was used to test associations between citation counts, journal impact factor, and year of publication. Scientific production increased from 2015 onwards. Most studies were observational, concentrating on age and sex estimation. A methodological shift was observed with the progressive introduction of artificial intelligence. Japan had the highest citation impact. Gifu University showed the highest citations per article, and Unicamp was the most productive institution. No significant association was identified between impact factor and citations. The results confirmed computed tomography as a strategic tool in forensic sciences, especially when combined with artificial intelligence. This study offers insights into the interface between radiology and forensics and paves the way for expanding the applicability of image-based human identification.