Abstract
Average facial soft-tissue thickness (FSTT) databanks are continuously developed and applied within craniofacial identification. This study considered and tested a subject-specific regression model alternative for estimating the FSTT values for oral midline landmarks using skeletal projection measurements. Measurements were taken from cone-beam computed tomography scans of 100 South African individuals (60 male, 40 female; Mage = 35 years). Regression equations incorporating sex categories were generated. This significantly improved the goodness-of-fit (r2-value). Validation tests compared the constructed regression models with mean FSTT data collected from this study, existing South African FSTT data, a universal total weighted mean approach with pooled demographic data and collection techniques and a regression model approach that uses bizygomatic width and maximum cranial breadth dimensions. The generated regression equations demonstrated individualised results, presenting a total mean inaccuracy (TMI) of 1.53 mm using dental projection measurements and 1.55 mm using cemento-enamel junction projection measurements. These slightly outperformed most tested mean models (TMI ranged from 1.42 to 4.43 mm), and substantially outperformed the pre-existing regression model approach (TMI = 5.12 mm). The newly devised regressions offer a subject-specific solution to FSTT estimation within a South African population. A continued development in sample size and validation testing may help substantiate its application within craniofacial identification.
Original language | English |
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Pages (from-to) | 170-179 |
Number of pages | 10 |
Journal | Medicine, Science and the Law |
Volume | 61 |
Issue number | 3 |
DOIs | |
Publication status | Published - Jul 2021 |
Keywords
- craniofacial approximation
- Craniofacial identification
- craniofacial superimposition
- mouth
- soft-tissue depth
- soft-tissue thickness
ASJC Scopus subject areas
- Issues, Ethics and Legal Aspects
- Health Policy
- Law