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    Analysis of the effects of hypothalamic-pituitary-adrenal axis activity in menstrual cycle on ankle proprioception, dynamic balance scores and visual-auditory reaction times in healthy young women
    (International Society of Musculoskeletal and Neuronal Interactions, 2021) Senol, D.; Uçar, C.; Toy, S.; Kisaoglu, A.; Özbag, D.; Ersoy, Y.; Yildiz, S.
    Objectives: Menstrual cycle (MC) can affect not only the female reproductive system, but also functions such as neuromuscular performance. For this reason, the aim of this study is to investigate the effect of hypothalamic-pituitary-adrenal axis (HPA) activity in MC on proprioception, balance and reaction times. Methods: For cortisol analysis, saliva samples were taken from the same women (n=43) in the four phases of MC. While State Trait Anxiety Inventory-I (STAI-I) was applied in each phase to support cortisol analysis, pain was measured with visual analogue scale (VAS). Proprioception, dynamic balance, visual and auditory reaction times (VRT-ART) measurements were made in the four phases of MC. Results: Cortisol, STAI-I and VAS scores, angular deviations in proprioception measurements, dynamic balance scores, VRT and ART measurements were found to show statistically significant difference between MC phases (p<0.05). As a result of the post hoc test conducted to find out which MC phase the statistical difference resulted from, it was found that statistically significant difference was caused by the mensturation (M) phase (p<0.05). Conclusions: It was found that neuromuscular performance and postural control was negatively affected by HPA axis activity in M phase of MC and by pain, which is a significant menstrual symptom. © 2021, International Society of Musculoskeletal and Neuronal Interactions. All rights reserved.
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    Comparison of Anthropometric and Conic Beam Computed Tomography Measurements of Patients with and without Difficult Intubation Risk According to Modified Mallampati Score: New Markers for Difficult Intubation
    (Wolters Kluwer Medknow Publications, 2021) Senol, D.; Ozbag, D.; Dedeoglu, N.; Cevirgen, F.; Toy, S.; Ogeturk, M.; Kose, E.
    Background: The aim of this study was to compare the anthropometric and cone beam computed tomography (CBCT) measurements taken from risk-free and risky groups by using the modified Mallampati score (MMS). Patients and Methods: A total of 176 volunteers between the ages of 18 and 65 in four different MMS classes were included in the study. The patients in classes MMS I and MMS II were accepted as risk-free and the patients in classes MMS III and MMS IV were accepted as risky for intubation. The Mann-Whitney U test was performed on the data to compare the anthropometric and radiological measurements taken from the risk-free and risky groups. A receiver operating characteristic (ROC) analysis was applied to the parameters that had a statistically significant difference. Results: According to the analysis results, statistically significant differences were found in the neck circumference (NC), maximum interincisal distance (MID), thyromental distance (TMD) and sternomental distance (SMD) of the anthropometric measurements of men and women between the risk-free and risky groups (P < 0.05). In terms of CBCT measurements, the thickness of the tongue (TT), distance between the uvula and posterior wall of pharynx (U-Ph), distance between posterior nasal spine and nasopharvnx (Snp-Nph) and length of the epiglottis (LE) were found to have statistically significant differences between the risk-free and risky groups of men and women (P < 0.05). Conclusion: The NC, MID, TMD and SMD anthropometric measurements and TT, U-Ph, Snp-Nph and LE radiologic measurements were found to support MMS, which is one of the most widely used bedside intubation prediction tests. In addition to the inclusion of CBCT for intubation prediction, U-Ph and Snp-Nph radiologic measurements were added as difficult intubation markers.
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    Comparison of the effects of the somatotype on the physical activity, kinesiophobia, and fatigue levels of obstructive sleep apnea syndrome patients and healthy individuals
    (Iranian Journal of Public Health, 2021) Toy, S.; Çiftçi, R.; Senol, D.; Kizilay, F.; Ermis, H.
    Background: We aimed to compare the physical activity, kinesiophobia, and fatigue levels of obstructive sleep apnea syndrome (OSAS) patients and healthy individuals in terms their somatotypes. Methods: A total of 165 individuals were enrolled referred to the Department of Chest Diseases Sleep Disorders Center Outpatient Clinic of Inonu University, Malatya, Turkey in 2018. The somatotype analysis was conducted using the Heath-Carter method, the fatigue level was assessed using the Functional Assessment of Chronic Illness Therapy (FACIT) fatigue scale, the kinesiophobia level was assessed using the Tampa Scale for Kinesiophobia (TSK), and the physical activity level was assessed using the International Physical Activity Questionnaire (IPAQ). Results: The results of the somatotype analysis revealed 3 different somatotypes in the healthy individuals and the OSAS patients’ mesomorph endomorph, endomorphic mesomorph, and mesomorphic endomorph. When comparing the somatotypes of the healthy individuals and the OSAS patients, statistically significant differences were found in the FACIT scores of the mesomorph endomorphs, the IPAQ and FACIT scores of the endomorphic mesomorphs, and the TSK and FACIT scores of the mesomorphic endomorphs (P<0.05). Conclusion: In all three somatotypes of the OSAS patients, the fatigue index scores were higher when compared to those of the healthy individuals. Moreover, when compared with the healthy individuals, the physical activity levels of the endomorphic mesomorphs with OSAS were low, while the kinesiophobia scores of the mesomorphic endomorphs with OSAS were high. Based on the results of this study, in OSAS patients, the endomorphic mesomorph somatotype could be a risk factor for reduced physical activity, while the mesomorphic endomorph somatotype could be a risk factor for increased kinesiophobia. © 2021 Toy et al.
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    Gender Estimation from Morphometric Measurements of Mandibular Lingula by Using Machine Learning Algorithms and Artificial Neural Networks
    (Wolters Kluwer Medknow Publications, 2024) Senol, D.; Bodur, F.; Secgin, Y.; Sencan, D.; Duman, Sb; Oner, Z.
    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, & Idot;n & ouml;n & uuml; 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.
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    Morphometry of the Middle Cerebral Arteries: A Radio-Anatomical Study Based on Computed Tomography Angiography Findings
    (Universidad de la Frontera, 2023) Çiftçi, R.; Toy, S.; Ulubaba, H.E.; Senol, D.; Çinarli, F.S.; Sigirci, A.
    Middle cerebral artery (MCA), which has the largest irrigation area of the arteries that feed the brain, is an important artery whose microanatomy should be well known because of its vascular variation. In pathologies which are known to affect the cerebrovascular system such as type 2 diabetes mellitus (T2DM) and hypertension, morphometric characteristics of MCA gain importance. The aim of this study is to compare the morphometric characteristics of M1 segment of MCA in T2DM and hypertensive patients with those of healthy control group by using computed tomographic angiography (CTA). The study was carried out with retrospective morphometric analysis of CTA images of 200 individuals between 40 and 65 years of age. The individuals were grouped in four as hypertensive patients (group 1), patients with T2DM (group 2), patients with hypertension and T2DM (group 3) and healthy control group (group 4). Length and diameter measurements of M1 segment were performed and recorded by using 3D CTA images. While statistically significant difference was found between bilateral M1 segment diameters of both women and men (p<0.05), no statistically significant difference was found between segment lengths (p>0.05). As a result of the post hoc analysis performed, it was concluded that right and left M1 segment diameter of group 1, group 2 and group 3 was found to be different from group 4 in both sexes (p<0.05). We believe that this study will both be a guide in radio-anatomic assessments to be performed and also increase microanatomic level of information in the surgical treatment of the artery by showing the morphometric changes that occur in M1 segment of MCA in T2DM diseases. © 2023, Universidad de la Frontera. All rights reserved.
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    Sex prediction with morphometric measurements of first and fifth metatarsal and phalanx obtained from X-ray images by using machine learning algorithms
    (Via Medica, 2023) Senol, D.; Bodur, F.; Secgin, Y.; Bakici, R. S.; Sahin, N. E.; Toy, S.; Oner, S.
    Background: The aim of this study is to predict sex with machine learning (ML) algorithms by making morphometric measurements on radiological images of the first and fifth metatarsal and phalanx bones.Materials and methods: In this study, radiologic images of 263 individuals (135 female, 128 male) between the ages of 27 and 60 were analysed retrospectively. The images in digital imaging and communications in medicine (DICOM) format were transferred to personal workstation Radiant DICOM Viewer programme. Length and width measurements of the first and fifth metatarsal and foot phalanx bones were performed on the transferred images. In addition, the ratios of the total length of the first proximal and distal phalanx and length of the first metatarsal and total length of fifth proximal, middle, and distal phalanx and maximum length of fifth metatarsal were calculated.Results: As a result of machine learning algorithms, highest accuracy, specificity, sensitivity, and Matthews correlation coefficient values were found as 0.85, 0.86, 0.85, and 0.71, respectively with decision tree algorithm. It was found that accu racy rates of other algorithms varied between 0.74 and 0.83. Conclusions: As a result of our study, it was found that sex estimation was made with high accuracy rate by using machine learning algorithms on X-ray images of the first and fifth metatarsal and foot phalanx. We think that in cases when pelvis, cranium and long bones are harmed and examination is difficult, bones of the first and fifth metatarsal and foot phalanx can be used for sex estimation. (Folia Morphol 2023; 82, 3: 704-711)