IDENTIFICATION OF SEX FROM PALATAL BONES USING MULTI-SLICE COMPUTED TOMOGRAPHY SCAN IN A SAMPLE OF ADULT EGYPTIAN POPULATION | ||||
| The Egyptian Journal of Forensic Sciences and Applied Toxicology | ||||
| Volume 23, Issue 1, March 2023, Page 15-26 PDF (642.09 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/ejfsat.2022.115747.1238 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Rasha Khedr  1; Hanan Mohamed Khattab2
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| 1lecturer of forensic medicine and toxicology Faculty of Medicine , Alexandria University, Egypt | ||||
| 2Lecturer of diagnostic and interventional radiology, Faculty of Medicine, University of Alexandria | ||||
| Abstract | ||||
| Background: Identification is the cornerstone in forensic medicine. Accurate sex identification from fragmented bones is a challenging medicolegal task. The hard palate is a well-protected part in the skull base with sexually dimorphic characters. Objectives: This current research aimed to predict sex from palatine bones in a sample of Egyptians using 3D Computed Tomography. Subjects and methods: The study included 100 adult Egyptians (47 males, 53 females) who performed skull CT. The studied palatine measurements were Maxillo-Alveolar Breadth (MAB), Maxillo-Alveolar Length (MAL), Incisive foramen - greater palatine foramen (IF-RGPF, IF-LGPF), Incisive Foramen-Basion (IF-B), and Incisive Foramen- mastoid Notch (IF-RMN, IF-LMN). Maxillo-Alveolar Index (MAI) and size of the palate were also calculated. Result: Most palatine measurements were higher among males. However, a significant difference was observed among MAB, MAL, IF- RMN, and IF-LMN. These significant measurements were included in regression analysis for sex prediction. The highest accuracy was obtained by an equation including MAL, MAB, IF- RMN, and IF- LMN together (68%) followed by MAL (64%) followed by IF- RMN, IF- LMN and MAB 63%, 61%, 60% respectively. Moreover, Receiver operator characteristic (ROC) curve analysis revealed that the combined parameters (MAL, MAB, IF- RMN, and IF- LMN) were the best sex discriminator (accuracy 68%), followed by MAL (64%) followed by MAB (62%) and IF- LMN (61%). | ||||
| Keywords | ||||
| Identification; Sex prediction; Computed Tomography; Palatine bones; Egyptian | ||||
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