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    The analysis of sacrum and coccyx length measured with computerized tomography images depending on sex
    (Int Assoc Law & Forensic Sciences, 2021) Bakici, Rukiye Sumeyye; Oner, Zulal; Oner, Serkan
    Background: Sex estimation is vital in establishing an accurate biological profile from the human skeleton, as sex influences the analysis of other elements in both Physical and Forensic Anthropology and Legal Medicine. The present study was conducted to analyze the sex differences between the sacrum and coccyx length based on the measurements calculated with computed tomography (CT) images. One hundred case images (50 females, 50 males) who were between the ages of 25 and 50 and admitted by the emergency department between September 2018 and June 2019 and underwent CT were included in the study. Eighteen lengths, 4 curvature lengths, and 2 regions were measured in sagittal, coronal and transverse planes with orthogonal adjustment for three times. Results: It was stated that the mean anterior and posterior sacral length, anterior and posterior sacrococcygeal length, anterior and posterior sacral curvature length, anterior coccygeal curvature length, sacral area, lengths of transverse lines 1, 2, 3 and 4, sacral first vertebra transverse and sagittal length measurements were longer in males when compared to females (p < 0.05). It was noted that the parameter with the highest discrimination value in the receiver operating characteristic (ROC) analysis was the sacral area (AUC = 0.88/Acc = 0.82). Based on Fisher's linear discriminant analysis findings, the discrimination rate was 96% for males, 92% for females and the overall discrimination rate was 94%. Conclusions: It was concluded that the fourteen parameters that were indicated as significant in the present study could be used in anthropology, Forensic Medicine and Anatomy to predict sex.
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    Estimation of sex from femoral bone using radiological imaging methods in Turkish population
    (E Schweizerbartsche Verlagsbuchhandlung, 2024) Bakici, Rukiye Sumeyye; Ocal, Zeynep Ayvat; Meral, Orhan; Oner, Zulal; Oner, Serkan
    Sex estimation is leading to determine the biological profile in forensic medicine. The aim of this study is to research the effectiveness of logistic regression (LogR) and discriminant function analysis (DFA) to create sex estimation models on femur images obtained with Computed Tomography (CT) angiography and to address the differences of femur, which show sexual dimorphism, among populations. All parameters were measured on three planes by adjusting the 300 CT angiography images from 150 women and 150 men that focused on the left femur to the orthogonal plane with standard magnification. The subgroup, which included 30 images randomly generated from these images, was measured twice with an interval of 3 weeks by the first radiologist and once by the second radiologist. According to the Fisher's Linear Discriminant analysis, which was evaluated with ten parameters in the study, it was concluded that the power of discriminating women was 96.7%, the power of discriminating men was 98.7%, and the total discrimination power was 97.7%; these results were 98%, 99.3%, and 98.7%, respectively according to LogR. In this study, DFA and LogR analysis showed that femur provided a very good rate of sexual dimorphism. A database belonging to the Turkish population was created for the femur, allowing for comparison between populations.
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    Evaluation of Hand Morphometry in Healthy Young Individuals from Different Countries
    (Soc Chilena Anatomia, 2024) Sahin, Necati Emre; Bakici, Rukiye Sumeyye; Toy, Seyma; Oner, Zulal
    This study aims to examine the hand morphometry of healthy young individuals from different countries and investigate the differences between countries in typing of hand based on the morphometric values obtained. In the study, 16 different parameters, including two surface areas and 14 lengths, were measured from the right hand of 579 volunteers (250 females, 329 males) from 7 different countries (Turkey, Chad, Morocco, Gabon, Kazakhstan, Senegal and Syria). Factor analysis was performed on the parameters, cluster analysis was performed according to the factor score obtained, and the hand types in the study were determined. As a result of the study, four different hand types were defined, and the distribution of these types according to countries was analyzed. All parameters showed significant differences between countries in both genders (p<0.05). According to the results of the study, there was a difference between male and female hand types between countries. In females, the type 1 hand type was found only in Gabon, the type 2 hand type was found only in Senegal, the type 3 hand type was found in Turkey, Morocco and Kazakhstan, while the type 4 hand type was significantly distributed in Senegal and Gabon (X-2 =104.62; df=18, p<0.05). In males, type 1 hand type was found in Turkey, type 2 hand type in Senegal and Gabon, type 3 hand type in Turkey, while type 4 hand type was significantly distributed in Morocco and Kazakhstan (X-2 =76.964; df=18, p<0.05).
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    Evaluation of palmar creases of healthy young individuals of different countries
    (Cukurova Univ, Fac Medicine, 2024) Sahin, Necati Emre; Bakici, Rukiye Sumeyye; Oner, Zulal; Toy, Seyma
    Purpose: This study aims to evaluate the potential effects of gender and country factors on palmar creases by examining the palmar creases of young adults from various countries. Materials and Methods: The study involved a total of 220 volunteers, including 120 males and 100 females aged 18-30, from seven different countries (Jordan, Sudan, Somalia, Iran, Iraq, Tanzania and Turkey), as well as students from Karabuk University. Hand types were evaluated based on palmar creases and the number of origins for both hands. Total Degree of Transversality (TDoT) values for palmar creases were calculated. Classification of palmar creases and comparison of T -DoT values for both hands were performed between genders and countries. Results: The study analyzed 440 hands from 220 individuals, identifying 1 Simian, 8 Suwon, and 5 Sydneytype hands, while categorizing the remaining 426 hands as normal type. Regarding the number of palmar crease origins, it was observed that there was a single origin in 3 hands, two origins in 309 hands and three origins in 119 hands. Significant associations were found between genders and countries in the number of palmar crease origins. In addition, significant differences in right hand TDoT values were found between genders and countries. Conclusion: In spite of limitations in sample selection and size, these results are important in providing a basis for future in-depth research on palmar creases at later stages, although generalizability to the specific countries represented in the sample may be limited. Consequently, this study highlights variations among countries concerning both the number of palm crease origins and right-hand T -DoT values.
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    Sex Prediction of Hyoid Bone from Computed Tomography Images Using the DenseNet121 Deep Learning Model
    (Soc Chilena Anatomia, 2024) Bakici, Rukiye Sumeyye; Cakmak, Muhammet; Oner, Zulal; Oner, Serkan
    The study aims to demonstrate the success of deep learning methods in sex prediction using hyoid bone. The images of people aged 15-94 years who underwent neck Computed Tomography (CT) were retrospectively scanned in the study. The neck CT images of the individuals were cleaned using the RadiAnt DICOM Viewer (version 2023.1) program, leaving only the hyoid bone. A total of 7 images in the anterior, posterior, superior, inferior, right, left, and right-anterior-upward directions were obtained from a patient's cut hyoid bone image. 2170 images were obtained from 310 hyoid bones of males, and 1820 images from 260 hyoid bones of females. 3990 images were completed to 5000 images by data enrichment. The dataset was divided into 80 % for training, 10 % for testing, and another 10 % for validation. It was compared with deep learning models DenseNet121, ResNet152, and VGG19. An accuracy rate of 87 % was achieved in the ResNet152 model and 80.2 % in the VGG19 model. The highest rate among the classified models was 89 % in the DenseNet121 model. This model had a specificity of 0.87, a sensitivity of 0.90, an F1 score of 0.89 in women, a specificity of 0.90, a sensitivity of 0.87, and an F1 score of 0.88 in men. It was observed that sex could be predicted from the hyoid bone using deep learning methods DenseNet121, ResNet152, and VGG19. Thus, a method that had not been tried on this bone before was used. This study also brings us one step closer to strengthening and perfecting the use of technologies, which will reduce the subjectivity of the methods and support the expert in the decision-making process of sex prediction.