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Pitfalls of Computed Tomography 3D Reconstruction Models in Cranial Nonmetric Analysis*.
- Source :
-
Journal of Forensic Sciences . Nov2020, Vol. 65 Issue 6, p2098-2107. 10p. - Publication Year :
- 2020
-
Abstract
- Many studies in the literature have highlighted the utility of virtual 3D databanks as a substitute for real skeletal collections and the important application of radiological records in personal identification. However, none have investigated the accuracy of virtual material compared to skeletal remains in nonmetric variant analysis using 3D models. The present study investigates the accuracy of 20 computed tomography (CT) 3D reconstruction models compared to the real crania, focusing on the quality of the reproduction of the real crania and the possibility to detect 29 dental/cranial morphological variations in 3D images. An interobserver analysis was performed to evaluate trait identification, number, position, and shape. Results demonstrate a false bone loss in 3D models in some cranial regions, specifically the maxillary and occipital bones in 85% and 20% of the samples. Additional analyses revealed several difficulties in the detection of cranial nonmetric traits in 3D models, resulting in incorrect identification in circa 70% of the traits. In particular, pitfalls included the detection of erroneous position, error in presence/absence rates, in number, and in shape. The lowest percentages of correct evaluations were found in traits localized in the lateral side of the cranium and for the infraorbital suture, mastoid foramen, and crenulation. The present study highlights important pitfalls in CT scan when compared with the real crania for nonmetric analysis. This may have crucial consequences in cases where 3D databanks are used as a source of reference population data for nonmetric traits and pathologies and during bone‐CT comparisons for identification purposes. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00221198
- Volume :
- 65
- Issue :
- 6
- Database :
- Academic Search Index
- Journal :
- Journal of Forensic Sciences
- Publication Type :
- Academic Journal
- Accession number :
- 146830323
- Full Text :
- https://doi.org/10.1111/1556-4029.14535