الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
The establishment of the biological identity of human remains is an incredibly challenging task for forensic anthropologists involved in the mission of identification. Forensic anthropologists examine all the skeletal remains for ―age, sex, ethnic group, and stature‖. Each of these features narrows the number of possible matches substantially. Age estimation has been long performed for medico-legal purposes. One of the most important steps in age estimation is tracking the appearance and fusion of epiphyseal unions which may show obvious variances depending on geographical distribution, sex, hormonal imbalances, nutritional status, and race. Determining the sex of the individual is a serious phase in the process of identification. It narrows down the potential list of individuals by eliminating the members of the opposite sex. It also increases the accuracy of the methods used for identifying other biological features like sex-specific age and stature standards. The evolution in the field of radio-diagnosis has greatly affected the identification procedures because these modalities are efficient, easy, and accurate. The use of CT scans appears to be more fitting for studying bones than USG, MRI, and X-ray. It takes multiple sectional images of the subjected body part in the same session. It can also archive the raw images which can be further studied in both 2- dimensional images as well as in 3- dimensional images. It provides an easier method for locating the required landmarks and taking measurements which makes it very useful for sex, ethnic group, and stature determination. The shoulder region was chosen for this study as it seems to be understudied for age and sex determination, despite the fact that this region has some bones with promising predictive results for both age and sex. Also, CT chest database has expanded in the last few years due to the pandemic which facilitates studying them for purposes of identification. The first bone studied was the clavicle which gained great attention in this particular field. Investigating the medial clavicular epiphyseal has been crucial in forensic age estimation. Most structures will have completed their growth by age 18, but not the medial clavicular epiphysis which completes its growth at a later age. The clavicle also appears to exhibit sexual dimorphism next to the pelvis and the skull. It also shows great restraint to environmental factors. The other bone studied was the humerus which is the largest bone of the upper limb and it has been found to remain in a good condition after death. Unlike the clavicle, there was a great shortage of studies done on the humerus for identification especially using CT on the Egyptian population. The proximal humeral epiphysis shows excellent results and offers a priceless tool for estimating bone age. In addition, the measurements of the humerus have shown high reliability when determining the sex of the individual. This study aimed to estimate the age from the epiphyseal unions of the right proximal humeral epiphysis and the right medial clavicular epiphysis and to determine the sex from humeral and clavicular measurements using Multi-Detector Computed Tomography scanning of these bones in a sample of the Egyptian population. It is a cross-sectional study conducted on 139 Egyptian participants (68 males and 71 females). Their age ranged between 10 and 35 years. They were subjected to thoracic Multi-Detector Computed Tomography scans taken at the department of Radio-diagnosis and Medical Imaging at Tanta University Hospitals after recording their sex and ages. The duration of the study was six months, from the start of November 2021 to the end of April 2022. The participants of this study were divided into five age groups: group 1 consisted of 22 participants from the age of 10 years up to the age of 15 years. group 2 consisted of 25 participants above the age of 15 years up to 20 years and was composed of 35 participants. group 3 consisted of 32 participants with ages above 20 years up to 25 years. group 4 was composed of 30 participants with an age range above 25 years up to 30 years. Lastly, group 5 participants were above 30 years up to 35 years and consisted of 30 participants. The participants’ age and sex were recorded and each scan was evaluated. The stages of fusion of the right proximal humeral epiphysis and the right medial clavicular epiphysis were observed and recorded, and the right vertical diameter of humeral head and the right clavicular length were measured. All four indices were subjected to statistical analysis to evaluate the correlation with age and sex. As for sex determination, both the right vertical diameter of humeral head and the right clavicular length showed statistically significant differences between male and female participants. The two measurements also showed statistically significant differences between the median of the different age groups in males and females. Males’ measurements were higher than females’ measurements. Both the right vertical diameter of humeral head and the right clavicular length measurements were significantly valid for sex prediction. The highest AUC was reported for the right vertical diameter of humeral head. The right vertical diameter of humeral head can predict males when it is more than 40.1 mm with 78.4% accuracy while the right clavicular length can predict males when it is more than 139.15 mm with 76.9% accuracy. Both of the two measurements contributed significantly to the univariate regression models in males, females, and both sexes. The univariate linear regression models were also statistically significant. Both of the two measurements contributed significantly to the multivariate binomial logistic regression analysis for the prediction of the male sex giving rise to a statistically significant model. The model showed a sensitivity of 82.4%, specificity of 84.5%, and overall accuracy of 83.5%. Equation from both the right vertical diameter of humeral head and the right clavicular length: Logit (p) = -20.560 + (0.172 × right vertical diameter of humeral head in mm) + (0.096 × right clavicular length in mm). Logit (p) can be transformed to p (probability of being male) by the following formula: Regarding age estimation from the fusion stages of the right proximal humeral and right medial clavicular epiphyses, it was observed that the medians of the chronological age consistently increase with increasing stages. Moreover, all stages of fusion appeared to happen earlier in female participants than in male ones ―except for stage 3 of the right vertical diameter of humeral head, both males and females had a median of 18 years old‖. A statistically significant difference between males and females was found only in stage 4 in the right vertical diameter of humeral head. As for the right medial clavicular epiphysis, both stages 3 and 4 showed statistically significant differences between males and females. It was also observed that stage 3 and the stages onward are indicators that the participant is definitely 18 years old or older for both males and females. A strong positive correlation between age and the fusion stages of the two studied epiphyses was found in males and females and both sexes. Spearman’s correlation was calculated between the stages of fusion of each of the right medial clavicular epiphysis and the right proximal humeral epiphysis and the chronological age. It was statistically significant in males, females, and both sexes. Regarding the right medial clavicular epiphysis, spearman correlations were 0.874, 0.901, and 0.86 in males, females, and both sexes respectively. While, the right proximal humeral epiphysis showed spearman correlations as 0.762, 0.816, and 0.789 in males, females, and both sexes respectively. Both of the two epiphyses contributed significantly to the univariate regression models in males, females, and both sexes. The univariate linear regression models were also statistically significant. Backward elimination multiple regression analysis was also done to predict age using the two parameters ―the right humeral and clavicular stages‖ and the models were statistically significant to predict age ―except for the humeral stage which does not significantly predict the age in females in the multiple regression model, so we can use the univariate model equation instead‖. Equations for age prediction were generated from the backward elimination multiple regression analysis as follows: Age in males = 7.750 + (1.425 × humeral stage) + (4.017 × clavicular stage). Age in all participants = 7.740 + (1.237 × humeral stage) + (3.809× clavicular stage).