Re-evaluation of Dental Morphology Methods and their Applicability in Virtual Anthropology

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Vlemincq-Mendieta, Tatiana

Issue Date

2023

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Dissertation

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ASUDAS , biological anthropology , CT scans , dental morphology , nonmetric dental traits , virtual anthropology

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Abstract

The utility of dental morphology has been demonstrated on numerous occasions in population studies. Nevertheless, the potential of nonmetric dental traits has been limited by missing data issues, which is linked to access to collections, taphonomy, dental wear and diseases, and underrepresented populations. With the advent of virtual anthropology, computed tomography (CT) images can increase the understanding of human variation by accessing larger samples with less missing data and allowing the visualization of roots. Nonmetric dental traits were collected from and/or used from four main collections: (1) the Subadult Virtual Anthropology Database (SVAD) (n=799), (2) the Christy G. Turner database (n=2,018), (3) the University of Tennessee Knoxville (UTK) Donated Skeletal Collection (n=252), and (4) the Texas State (TS) University Donated Skeletal Collection (n=106; n=25). Nonmetric dental traits were collected from dry specimens at UTK and TS under the NIJ 2017-DN-BX-0143 award and from virtual images from the SVAD. Twenty-five individuals from TS were also scanned (i.e., CT scans). Data were collected from all over the world from dry specimens for the Turner database. This multi-database of 3,200 individuals permits the re-evaluation of methods used in dental morphology and allows their translation into virtual imaging. For the first Aim, the Arizona State University Dental Anthropology System (ASUDAS) was used on dry teeth and the same virtual teeth of 25 individuals from TS. For the second Aim, crown traits were compared to root traits in biodistance analyses. Special attention was given to the importance of modality in root performance, and in doing so, Turner, SVAD, UTK and TS were used. The third Aim explored root morphology via CT scans in a way not previously conducted. Root fusion patterns were highlighted in conjunction with root number using the SVAD. The results for the first Aim showed that 52% of 38 nonmetric dental traits scored on all teeth (total of 101 variables) are interchangeable between dry teeth to CT scans. Dichotomization does not necessarily improve the results, and levels of agreement of one specific trait vary depending on the tooth being scored. The results of the second Aim show that crown and root trait performances in biodistance analyses are dependent on trait selection, sample size and number, provenance, and the quantity of missing data. Biodistance outcomes from the virtual database SVAD had more consistent results independent of trait selection, while outcomes using dry teeth (Turner, UTK, and TS), varied in their results depending on trait selection. Finally, the third aim added new information on root fusion patterns to the established molar root number using the SVAD CT scans from four U.S. populations. Results were aligned with previous population histories, with the Native American group showing more variation than the American Black group, while the American white and Hispanic groups were intermediate. New patterns also emerged, with higher frequencies of three-rooted LM1 in the American white group, and fusion patterns being associated with specific groups. This dissertation is the first attempt to demonstrate the potential of using CT scans as a tool in the study of dental morphology. The implementation of CT scans as a data source brings larger samples and less missing data, and also opens a door to stronger statistics.

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