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- MakaleAçık Erişim2026Scopus SJRQ2Fully automated 3D volumetric analysis of masticatory muscles in a pediatric population: A CT-based normative morphometric study
Kanber Uzun, Özlem; Ertemoğlu Öksüz, Canan; Kalkışım, Şahi Nur; Palancı, Özgür; Yıldırım, Yusuf İslam
The masticatory muscles play a fundamental role in craniofacial growth and development, yet normative volumetric data encompassing all four muscles across the full pediatric age range remain poorly characterized. The aim of this study was to establish age- and sex-specific normative reference values for the volumetric development of masticatory muscles in a normal pediatric population (0–17 years) using a fully automated 3D segmentation method. This retrospective, cross-sectional study included 258 normal pediatric individuals stratified into four age groups based on biomechanical milestones (0–5, 6–9, 10–13, and 14–17 years). Bilateral volumes of the masticatory muscles were automatically calculated using TotalSegmentator in the 3D Slicer environment. Two-way analysis of variance and Bonferroni post-hoc tests were applied. All muscles showed significant volume increases with age (p < 0.001), with the masseter demonstrating the greatest increase (199%). No sex differences were observed in 0–5 years; significant male-favoring differentiation began from 6 to 9 years. The temporalis muscle exhibited a biphasic sex differentiation pattern, with no significant difference at 10–13 years despite significance at 6–9 and 14–17 years. The highest sex-related effect sizes were observed in the pterygoid muscles (medial pterygoid ηp² = 0.176; lateral pterygoid ηp² = 0.160). Bilateral asymmetry analyses revealed left-sided favoring in the masseter, a lateralization trend in the temporalis (exploratory), right-sided favoring in the medial pterygoid, and sex-specific lateralization in the lateral pterygoid. These findings provide a large-scale CT-based normative reference for pediatric masticatory muscles, demonstrating muscle-specific volumetric patterns and variable sex differentiation, with normative ranges supporting clinical decision-making in dentistry, craniofacial surgery, and pediatric radiology.
- MakaleAçık Erişim2025Scopus SJRQ1The Effect of Music on Fear and Anxiety of Children During Tomography: A Randomized Controlled Double-Blind Study
Kurudirek, Fatma; Demir Barbak, Zülbiye; Demir İmamoğlu, Zeynep; Çiftci, Kamile; Delice, Orhan
Aim: This study was conducted to determine the effect of a musical intervention during computed tomography (CT) on fear, anxiety and vital signs of children. Method: This randomized, double-blind controlled trial was conducted according to the Consolidated Standards of Reporting Studies (CONSORT) guidelines. The study sample included children aged between 6 and 10 years who met the inclusion criteria and underwent CT scan in the emergency department of a public hospital in eastern Turkey between 18 April and 20 May 2023. The research was completed with a total of 60 children, randomized to one of two groups. The nursing intervention of the study was playing music. Data were collected through face-to-face interviews using the Child and Family Information Form, the Children's Fear Scale (CFS), Children's Anxiety Meter-State (CAM-S) and the Vital Signs Monitoring Form (pulse, blood pressure and oxygen saturation). Ethical principles were followed in the research. Results: The level of fear, anxiety, pulse rate and respiratory rate of the children in the musical intervention group during CT scanning were lower than in the control group (p < 0.05). No difference was found between the groups in terms of oxygen saturation (p < 0.05). Conclusion and Recommendations for Implementation: The results of this study suggest that musical intervention during CT scanning in children is effective in reducing the level of fear and anxiety and stabilizing vital signs. By using such nonpharmacologic methods, nurses can provide support to children and alleviate emotional difficulties during procedures. Trial Registration: NCT06086509. Summary: What is already known about this topic? Music therapy is recognized as an effective nonpharmacologic intervention to reduce fear and anxiety in paediatric patients undergoing medical procedures. Previous studies have shown that musical intervention during CT scans can calm children, potentially reducing the need for sedation and improving compliance. Knowledge gaps remain regarding the specific effects of music on physiological parameters like pulse and respiratory rates during paediatric CT scans. What this paper adds? This study demonstrates that musical intervention during CT scans significantly reduces fear and anxiety levels in children aged 6–10 years. The research findings show that music intervention can also stabilize vital signs, such as pulse and respiratory rates, during CT scans, suggesting a relaxed physiological state. The results support the idea that incorporating music into paediatric imaging procedures can enhance patient comfort and improve the quality of the imaging process by encouraging children to remain still. The implications of this paper: Incorporating music therapy into routine paediatric imaging procedures can reduce anxiety, improve patient cooperation and potentially reduce the need for sedatives. Future research could explore the optimal types of music, volume levels and delivery methods to maximize the calming effects on children during various medical procedures. Training programs for paediatric healthcare providers can include education on the benefits of nonpharmacologic interventions, like music therapy, to reduce anxiety and improve patient outcomes in clinical settings.
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İncele - MakaleAçık Erişim2021Scopus SJRQ1A Two-Phase Approach using Mask R-CNN and 3D U-Net for High-Accuracy Automatic Segmentation of Pancreas in CT Imaging
Dogan, Ramazan Ozgur; Dogan, Hulya; Bayrak, Coskun; Kayikcioglu, Temel
Background and objective: The size, shape, and position of the pancreas are affected by the patient characteristics such as age, sex, adiposity. Owing to more complex anatomical structures (size, shape, and position) of the pancreas, specialists have some difficulties in the analysis of pancreatic diseases (diabetes, pancreatic cancer, pancreatitis). Therefore, the treatment of the disease requires enormous time and depends on the experience of specialists. In order to decrease the rate of pancreatic disease deaths and to assist the specialist in the analysis of pancreatic diseases, automatic pancreas segmentation techniques have been actively developed in the research article for many years. Methods: Although the rapid growth of deep learning and proving satisfactory performance in many medical image processing and computer vision applications, the maximum Dice Similarity Coefficients (DSC) value of these techniques related to automatic pancreas segmentation is only around 85% due to complex structure of the pancreas and other factors. Contrary to previous techniques which are required significantly higher computational power and memory, this paper suggests a novel two-phase approach for high-accuracy automatic pancreas segmentation in computed tomography (CT) imaging. The proposed approach consists of two phases; (1) Pancreas Localization, where the rough pancreas position is detected on the 2D CT slice by adopting Mask R-CNN model, (2) Pancreas Segmentation, where the segmented pancreas region is produced by refining the candidate pancreas region with 3D U-Net on the 2D sub-CT slices generated in the first phase. Both qualitative and quantitative assessments of the proposed approach are performed on the NIH data set. Results: In order to evaluate the achievement of the recommended approach, a total of 16 different automatic pancreas segmentation techniques reported in the literature are compared by utilizing performance assessment procedures which are Dice Similarity Coefficient (DSC), Jaccard Index (JI), Precision (PRE), Recall (REC), Pixel Accuracy (ACC), Specificity (SPE), Receiver Operating Characteristics (ROC) and Area under ROC curve (AUC). The average values of DSC, JI, REC and ACC are computed as 86.15%, 75.93%, 86.27%, 86.27% and 99.95% respectively, which are the best values among well-established studies for automatic pancreas segmentation. Conclusion: It is demonstrated with qualitative and quantitative results that our suggested two-phase approach creates more favorable results than other existing approaches.
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