Abstract
Forensic facial approximation and superimposition methods rely on understanding soft and hard tissue anatomical correlations. Guyomarc’h and Stephan analysed eight existing ear prediction methods, revealing inadequate support from computed tomography scans of 78 living adults. They subsequently proposed four newly validated prediction protocols, driven by correlations between ear features, sex, age, and facial height. This study aimed to re-examine the available protocols utilising an independent sample and trail newly proposed regression equations.
This study used 37 computed tomography scans from the New Mexico Decedent Database (deceased) and the University of Science and Technology Hospital Yemen database (living). Observations were performed in 3D Slicer. Skull placement and measurement definitions were standardised via Python scripting. All statistical tests were performed using SPSS, including testing for sexual dimorphism, asymmetry, effects of population-affinity and age.
This project largely supported Guyomarc’h and Stephan’s findings. In contrast, guidelines proposing only slight differences between the height of the nose and height of the ear (c.2 mm) was found to be unreliable (explains only 13.47% of variation); no correlation was found between the supramastoid crest and auricle (p=0.149), and that
lobe morphology correlated (r=0.487) with mastoid lateral angle.
Comparably high standard errors of the estimates for in-sample regression equations established in this study (especially for ear height) were comparable to those of Guyomarc’h and Stephan. Future research should focus on expanding ear approximation guidelines, potentially incorporating additional landmarks, investigating interlandmark distances and semilandmarks, or adopting a geometric-morphometric approach to enhance reliability. Furthermore, the wider implementation of deep learning in forensic anthropology could prove beneficial in identifying associations between hard and soft tissue features in the auriculotemporal region.
This study used 37 computed tomography scans from the New Mexico Decedent Database (deceased) and the University of Science and Technology Hospital Yemen database (living). Observations were performed in 3D Slicer. Skull placement and measurement definitions were standardised via Python scripting. All statistical tests were performed using SPSS, including testing for sexual dimorphism, asymmetry, effects of population-affinity and age.
This project largely supported Guyomarc’h and Stephan’s findings. In contrast, guidelines proposing only slight differences between the height of the nose and height of the ear (c.2 mm) was found to be unreliable (explains only 13.47% of variation); no correlation was found between the supramastoid crest and auricle (p=0.149), and that
lobe morphology correlated (r=0.487) with mastoid lateral angle.
Comparably high standard errors of the estimates for in-sample regression equations established in this study (especially for ear height) were comparable to those of Guyomarc’h and Stephan. Future research should focus on expanding ear approximation guidelines, potentially incorporating additional landmarks, investigating interlandmark distances and semilandmarks, or adopting a geometric-morphometric approach to enhance reliability. Furthermore, the wider implementation of deep learning in forensic anthropology could prove beneficial in identifying associations between hard and soft tissue features in the auriculotemporal region.
| Original language | English |
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| Publication status | Published - Oct 2024 |
| Event | 20th Meeting of the International Association for Craniofacial Identification - University of Grenada, Grenada, Spain Duration: 2 Oct 2024 → 6 Oct 2024 https://iaci2024.com/ |
Conference
| Conference | 20th Meeting of the International Association for Craniofacial Identification |
|---|---|
| Abbreviated title | IACI |
| Country/Territory | Spain |
| City | Grenada |
| Period | 2/10/24 → 6/10/24 |
| Internet address |