ABSTRACT
BACKGROUND: Sex determination from the bones is of great importance for forensic medicine and anthropology. The mandible is highly valued because it is the strongest, largest and most dimorphic bone in the skull. AIM: Our aim in this study is gender estimation with morphometric measurements taken from mandibular lingula, an important structure on the mandible, by using machine learning algorithms and artificial neural networks. METHODS: Cone beam computed tomography images of the mandibular lingula were obtained by retrospective scanning from the Picture Archiving Communication Systems of the Department of Oral, Dental and Maxillofacial Radiology, Faculty of Dentistry, Inönü University. Images scanned in Digital Imaging and Communications in Medicine (DICOM) format were transferred to RadiAnt DICOM Viewer (Version: 2020.2). The images were converted to 3-D format by using the 3D Volume Rendering console of the program. Eight anthropometric parameters were measured bilaterally from these 3-D images based on the mandibular lingula. RESULTS: The results of the machine learning algorithms analyzed showed that the highest accuracy was 0.88 with Random Forest and Gaussian Naive Bayes algorithm. Accuracy rates of other parameters ranged between 0.78 and 0.88. CONCLUSIONS: As a result of the study, it is thought that mandibular lingula-centered morphometric measurements can be used for gender determination as well as bones such as the pelvis and skull as they were found to be highly accurate. This study also provides information on the anatomical position of the lingula according to gender in Turkish society. The results can be important for oral-dental surgeons, anthropologists, and forensic experts.
Subject(s)
Machine Learning , Mandible , Neural Networks, Computer , Humans , Male , Female , Mandible/anatomy & histology , Mandible/diagnostic imaging , Retrospective Studies , Adult , Cone-Beam Computed Tomography/methods , Sex Determination by Skeleton/methods , Imaging, Three-Dimensional/methods , Algorithms , Young Adult , Adolescent , Middle AgedABSTRACT
OBJECTIVE: The relation of diffuse idiopathic skeletal hyperostosis (DISH) and diabetes mellitus (DM) has been frequently reported. However, there is little knowledge about its prevalence in DM. The purpose of this study was to determine that prevalence and whether it differs from that of controls. METHODS: The prevalence of DISH was investigated in 133 patients with DM and 133 nondiabetic controls matched for sex, age, and weight. Radiologic criteria were used for diagnosis. Erythrocyte sedimentation rate, fasting blood glucose levels, glycolized hemoglobin, triglyceride, very low-density lipoprotein, low-density lipoprotein, high-density lipoprotein, calcium, uric acid, alkaline phosphatase, phosphorus, insulin, and insulin-like growth factor-1 (IGF1) levels of both groups were compared. RESULTS: The prevalence of DISH (12%) was higher in patients with DM than the control group (6.8%), but there was no statistically significant difference. The average age of the patients diagnosed with DISH (63.36 +/- 9.27) was significantly higher than that of the others (54.21 +/- 12.12) (P < 0.05). There was no significant difference between the DISH patients and the others in other parameters examined. CONCLUSION: We found no statistically significant difference in the prevalence of DISH between patients with DM and controls. We suggest that the factors thought to be responsible for the etiopathogenesis of DISH such as DM, insulin, and insulin-like growth factor-1 be investigated further.
