Purpose This study developed a convolutional neural network (CNN) model to diagnose maxillary sinusitis on panoramic radiographs (PRs) and cone-beam computed tomographic (CBCT) images and evaluated its performance. Materials and Methods A CNN model, which is an artificial intelligence method, was utilized. The model was trained and tested by applying 5-fold cross-validation to a dataset of 148 healthy and 148 inflamed sinus images. The CNN model was implemented using the PyTorch library of the Python programming language. A receiver operating characteristic curve was plotted, and the area under the curve, accuracy, sensitivity, specificity, positive predictive value, and negative predictive values for both imaging techniques were calculated to evaluate the model. Results The average accuracy, sensitivity, and specificity of the model in diagnosing sinusitis from PRs were 75.7%, 75.7%, and 75.7%, respectively. The accuracy, sensitivity, and specificity of the deep-learning system in diagnosing sinusitis from CBCT images were 99.7%, 100%, and 99.3%, respectively. Conclusion The diagnostic performance of the CNN for maxillary sinusitis from PRs was moderately high, whereas it was clearly higher with CBCT images. Three-dimensional images are accepted as the “gold standard” for diagnosis; therefore, this was not an unexpected result. Based on these results, deep-learning systems could be used as an effective guide in assisting with diagnoses, especially for less experienced practitioners.

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Purpose: The purpose of the study is to evaluate the effects of osteoporosis (OP) using panoramic mandibular index (PMI) and mandibular cortical index (MCI) in panoramic radiographic and cone-beam computed tomographic (CBCT) images and to demonstrate any advantages of CBCT versus panoramic imaging in those indexes. Materials & Methods: 36 female patients (18 with osteoporosis and 18 with no systemic disease) who had panoramic radiographic and CBCT indication due to dental problems were involved in the study. PMI and MCI are evaluated on both panoramic and CBCT images. Differences between patient groups are analyzed by the Kruskal Wallis test, and differences between imaging techniques are analyzed by impaired t-tests ignoring patient groups in confidence interval 95%. Results: In CBCT images, PMIs were significantly lower in patients with osteoporosis than in the control group (p=0.004), and there was no significant difference between the patient and control group in panoramic images (p=0.085). In both imaging techniques, MCIs were significantly higher in the osteoporosis group than in the control group (p=0.000). CBCT showed a significant advantage on PMI to panoramic images (p=0.05). Conclusion: Systemic diseases affect bone tissue in different levels, and to evaluate these effects, cortical and trabecular bone parts must be investigated separately, and findings must be combined with patients’ clinical symptoms. CBCT has advantages in PMI evaluations to panoramic radiography.

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Purpose: Aim of the study is to determine the activity of masseter muscle formed by mastication of different foods in individuals with multiple sclerosis (MS). Material and Methods: 12 women with MS and 12 healthy women were included in the study. 3 grams of hazelnut and chewing gum were given to individuals 20 separate times. Activities of the left and the right masseter muscles during mastication were recorded by using surface electromyography (EMG) device. Results: Values obtained from healthy women were higher than those obtained from patients with MS for both foods and both sides. Conclusion: The changes in the central and peripheral nervous systems of the patients affect chewing function.

Purpose: This study aims to assess the effect of voxel size on trabecular microstructural evaluation onhuman cadaver mandiblesusing cone beam computed tomography (CBCT) images. Methods: Twenty two Volumes of Interest were obtained from to human cadaver mandibles which were scanned in three different voxel sizes using CBCT. Scanning performed in 0.125 mm (Group 1), 0.2 mm (Group 2) and 0.3 mm (Group 3) voxel sizes. Regions of interest are calculated in both mandibles for both voxel sizes which are adjusted from apical third of all interdental alveolar trabecular bone from anterior and posterior mandible. Trabecular thickness (Tb. Th); trabecular separation (Tb. Sp); Bone Volume/Total Volume (BV/TV) values were obtained using plug in BoneJ of the software ImageJ. The results were evaluated statistically in software IBM SPSS Statistics 21. Results: Trabecular thickness and trabecular separation showed significant difference between first and the third and the second and the third groups (p=0.000), while first and second group did not. BV/TV values showed no significant difference between whole groups. Conclusion: Beside microstructural analysis is not their first purpose CBCT images carry knowledge about trabecular bone microstructure could be a valuable bone quality assessment tool. High correlation between values with 0.125 mm and 0.2 mm and low correlation between values with 0.125 mm and 0.3 mm voxel sizes suggest that; this knowledge is clinically more valuable when voxel size is 0.2 mm or thinner.

Vasküler ve nöral yapıların zarar görmemesi için ağız cerrahisi operasyonlarından önce radyolojik değerlendirme yapmak esastır. 1,2 İmplant yerleştirilmesi gibi kemik dokuyu ilgilendiren tüm cerrahi operasyonlar öncesinde konik ışınlı bilgisayarlı tomografi (KIBT) ile kemiğin anatomik yapısının ve boyutları-