Determinations of Cranial Dimorphism in Sagittal Section in CT Scans

• Autor(a) principal: Hamilton Mendonça
• Data de Publicação: 2019
• Outros Autores: Cristhiane Martins Schmidt, Viviane Ulbricht, Stéfany de Lima Gomes, João Sarmento Pereira Neto, Deborah Queiroz de Freitas França, Daruge Júnior, Luiz Francesquini Junior
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Brazilian Journal of Forensic Sciences, Medical Law and Bioethics
• Texto Completo: https://www.ipebj.com.br/bjfs/index.php/bjfs/article/view/762
• topic: Forensic dentistry; Sex characteristics; Forensic anthropology and computed tomography

The objective of this study was to analyze if the linear measurements performed on 206 CT scans are dimorphic and can be used as an auxiliary method for forensic identification as a secondary method according to INTERPOL 2014. A logistic regression model was developed to determine the sex of the individual analyzed. The measurements were performed on computed tomography of the Osteological Biobank and tomography of FOP_UNICAMP, in 117 male and 89 female CT scans with known age, ancestry and cause of death. OnDemand3D® software was used for the following measures: sella turcica (center) to nasal suture, sella turcica (center) to anterior nasal spine, sella turcica to ENP, sella turcica (center) to start; Nasal suture to ENA; Nasal suture to the ENP, in the median sagittal section. The Kolmogorov-Smirnov test was used to establish the distribution and equality of variances (homoscedasticity) of the variables under study. The unpaired t-test and the Pearson correlation coefficient were conducted, resulting in a logistic regression using the Stepwise-Forward method for sex. This study was approved by CAAE 54171916.0.0000.5418. It was verified that all measures studied are dimorphic, but the ß of the measures PPST-ENA; SNRE-ENA; SNRE-ENP; ENA-ENP were the most statistically significant, being selected to determine the multiple model. The logistic regression model was created: [Logit: -19.909 + 0.177 (SNRE-ENA) + 0.231 (ENA-P)]. The model obtained in this study, presented a 77.2% accuracy, being a good result to be used as a coadjuvant method to other sex estimation methods in mixed populations, such as Brazil.