CT-based hard-tissue craniofacial landmarks and paranasal sinuses for biological profile estimation (sex, age and stature) in human populations: a scoping review

Abstract Background Sex, age, and stature estimation are core tasks in forensic and biological anthropology. Computed tomography (CT)- and cone-beam computed tomography (CBCT)-based imaging now allows detailed measurement of craniofacial hard tissue and the paranasal sinuses for this purpose, but findings are scattered across different populations, imaging protocols, and analytic methods. Craniofacial landmarks are discrete, reproducible bony reference points on the skull used for standardised measurement, such as nasion, zygion, gonion, glabella, and porion. This scoping review mapped that evidence base using the Population, Concept, Context (PCC) framework: human subjects undergoing cranial or paranasal CT-based imaging (Population), CT-based craniofacial and sinus measurements (Concept), and forensic estimation of sex, age, or stature (Context). Main body Searches of PubMed, Scopus, and Web of Science, from inception to 7 May 2026, identified 76 eligible studies from 18 countries, led by India (24), Brazil (11), and Iran (8). Screening was performed independently by two reviewers. The maxillary sinus was the most studied structure (55 studies), followed by the frontal (33) and sphenoid (14) sinuses; the ethmoid sinus appeared in only one study. Sex estimation dominated the literature (72 studies), age estimation was addressed in 16, and no study examined stature. Discriminant function analysis (DFA) remained the standard statistical approach, though machine learning (ML) methods performed comparably or better where tested. Sex-classification accuracy ranged from about 60% to over 96%, and external validation across populations was rare. Conclusion The evidence base for CT-based sex estimation is broad but fragmented by population-specific formulae and limited external validation. Evidence for age estimation is weaker, and stature estimation from these structures remains unstudied. Future work should prioritise standardised measurement protocols, cross-population validation, and research into stature estimation.