SUCCESS OF ARTIFICIAL INTELLIGENCE SYSTEM IN DETERMINING ALVEOLAR BONE LOSS FROM DENTAL PANORAMIC RADIOGRAPHY IMAGES

Objectives: The aim of this study was to detect alveolar bone loss from dental panoramic radiographic images using artificial intelligence systems. Material and Methods: A total of 2276 panoramic radiographic images were used in this study. While 1137 of them belong to cases with bone destruction, 1139 were periodontally healthy. The dataset is divided into three parts as training (n=1856) , validation (n=210) and testing set (n= 210). All images in the data set were resized to 1472x718 pixels before training. A random sequence was created using the open-source python programming language and OpenCV, NumPy, Pandas, and Matplotlib libraries effectively. A pre-trained Google Net Inception v3 CNN network was used for preprocessing and data sets were trained using transfer learning. Diagnostic performance was evaluated with the confusion matrix using sensivitiy, specificity, precision, accuracy and F1 score. Results: Of the 105 cases with bone loss, 99 were detected by the AI system. Sensitivity was 0.94, specificity 0.88, precision 0.89, accuracy 0.91 and F1 score 0.91. Conclusion: The convolutional neural network model is successful in determining periodontal bone losses. It can be used as a system to facilitate the work of physicians in diagnosis and treatment planning in the future

The Use Of Finite Element Analysis In Implant Dentistry

Son yıllarda, implant tedavisi memnun edici fonksiyon ve estetik sonuçları sebebiyle tam veya kısmi dişsiz ark rehabilitasyonu için en çok tercih edilen tedavi seçeneği haline gelmiştir. İmplant uygulamalarının başarılı bir tedavi seçeneği olarak bilinmesine rağmen; uygun yükleme, geometri ve lokasyon seçilmemesi durumunda başarısız da olabilirler. İmplant başarısızlığından kaçınmak için, fonksiyondaki olası stres seviyelerini değerlendirmek ve dental implant planlamasında ideal implant konumunu seçmek gerekmektedir. İmplantların biyomekanik performansını test etmek veya kanıtlamak, implantın stabilitesinin veya osseoentegrasyonunun oral koşullarda değerlendirilmesindeki zorluklar nedeniyle çok güçtür. Bu nedenle oral biyomekanik koşulların değerlendirilmesi için invitro çalışmalar gerekli olmuştur. Sonlu elemanlar analizi; diş materyalleri, dişler ve implantların mekanik davranışlarını değerlendirmenin bir yolu olarak kullanımı son on yılda katlanarak artan ve biyomekanik bilim alanlarında kullanılabilen bir analiz tekniğidir. Sonlu elemanlar analizi, biyomekanik problemleri küçük parçalara bölerek çözen ve bilgisayar destekli tasarım modellerinde stres ve gerilmeleri hesaplayan cebir tabanlı bir simülasyon tekniğidir. Oral rehabilitasyondan önce faydalı biyomekanik bulgular sunmaktadır ve implant dişhekimliğindeki önemli bir analiz tekniğidir. Bu derleme, sonlu elemanlar analiz yöntemi hakkında ayrıntılı bilgi vermektedir ve araştırmacılara bilgi sağlamak amacıyla implant dişhekimliğinde kullanılabilir.In recent years, implant therapy has become the most preferred treatment choice for completely or partially edentulous arch rehabilitation due to its satisfactory functional and aesthetic results. Although implant therapy is known as a successful treatment procedure, it also known that failure is possible if appropriate loading, geometry or location is not selected for implant carefully. To aviod implant failure, it is necessarry to assess possible stress levels under function and to select the ideal implant configurations during dental implant planning. It is so difficult to prove or test the biomechanical performance of implants due to difficulties in assessing the stability or osseointegration of the implant in intraoral conditions. Therefore in-vitro studies became necessary for assessing intraoral biomechanical conditions. Finite element analysis is an analyse technique that can be used in biomechanical fields of science and have grown exponentially in the last decade as a way to assess the mechanical behavior of dental materials, teeth and implants. Finite element analysis is algebra based simulation technique that solves the biomechanical problems by dividing them into small pieces and calculates stresses and strains in computer-aided design models. It has been known that Finite element analysis is an essential analyse technique in implant dentistry and it offers useful biomechanical results before intraoral rehabilitation. This compilation gives detailed information about finite element method and it can use in in implant dentistry to provide information for researchers

Reply to letter to the editor

KURT, Sevda/0000-0002-3711-6520; BAYRAKDAR, Ibrahim Sevki/0000-0001-5036-9867; Guneri, Pelin/0000-0001-9423-9191WOS: 000545762700001PubMed: 32521569[No abstract available

Comparison of gingival crevicular fluid and serum human beta-defensin-2 levels between periodontal health and disease

Background The aim of this study was to evaluate the levels of serum and gingival crevicular fluid (GCF) human beta-defensin-2 (hBD-2), an antimicrobial peptide that takes roles in inflammatory diseases, in patients with chronic periodontitis (CP). Subjects and Methods A total of one hundred and one individuals, 59 controls and 42 patients with CP, participated in this study. Clinical index measurements were recorded during the periodontal examination, and radiographic evaluation was also performed. The serum and gingival crevicular fluid (GCF) samples were taken from all of the participants, and the hBD-2 levels were determined biochemically by enzyme-linked immunosorbent assay (ELISA). Results In our study, hBD-2 GCF levels in CP (stages II-IV periodontitis based on the new 2018 classification of periodontal diseases) group (2.77 ng/30 s) were higher than in the periodontally healthy (2.51 ng/30 s;p = .047) individuals. In contrast, serum hBD-2 levels in CP (2.92 ng/ml) were lower compared with those in healthy controls (7.75 ng/ml,p < .001). Conclusion Interestingly, our results showed that while higher hBD-2 GCF levels are associated with CP, lower serum hBD-2 levels were detected in CP

DEFB4A Promoter Polymorphism Is Associated with Chronic Periodontitis: A Case-Control Study

Background: Human beta-defensin-2 is an antimicrobial weapon peptide with antibiotic properties secreted by the oral cavity to protect the host against microbial attack. The interindividual differences of defensin expression profiles due to genetic variation might be partly responsible for differences in disease susceptibility

Assessing the Effectiveness of Artificial Intelligence Models for Detecting Alveolar Bone Loss in Periodontal Disease: A Panoramic Radiograph Study

The assessment of alveolar bone loss, a crucial element of the periodontium, plays a vital role in the diagnosis of periodontitis and the prognosis of the disease. In dentistry, artificial intelligence (AI) applications have demonstrated practical and efficient diagnostic capabilities, leveraging machine learning and cognitive problem-solving functions that mimic human abilities. This study aims to evaluate the effectiveness of AI models in identifying alveolar bone loss as present or absent across different regions. To achieve this goal, alveolar bone loss models were generated using the PyTorch-based YOLO-v5 model implemented via CranioCatch software, detecting periodontal bone loss areas and labeling them using the segmentation method on 685 panoramic radiographs. Besides general evaluation, models were grouped according to subregions (incisors, canines, premolars, and molars) to provide a targeted evaluation. Our findings reveal that the lowest sensitivity and F1 score values were associated with total alveolar bone loss, while the highest values were observed in the maxillary incisor region. It shows that artificial intelligence has a high potential in analytical studies evaluating periodontal bone loss situations. Considering the limited amount of data, it is predicted that this success will increase with the provision of machine learning by using a more comprehensive data set in further studies

Is sexual dysfunction associated with periodontal status in perimenopausal women?: A pilot study

Objective The current study aimed to investigate the possible relationship between periodontal status and sexual dysfunction in perimenopausal women. Materials and Methods This study was conducted on 106 participants. After the evaluation of the sexual functioning of participants with the Female Sexual Function Index (FSFI), their periodontal status and decayed-missing-filled teeth (DMFT) were assessed using appropriate indexes and obtained results were recorded for comparisons. Participants were divided into two groups by the periodontal status. Patients with periodontitis were grouped by the stage and the extent of the disease. Besides, participants were grouped according to the bleeding on probing (BOP) ratios for more detailed analyses. Results A negative significant correlation was observed between total FSFI scores and each of the clinical periodontal parameters. Total FSFI scores and the scores of arousal, lubrication, orgasm, satisfaction, and pain domains were significantly lower in periodontitis patients (p .05). Conclusion Periodontal status in perimenopausal women may be associated with sexual dysfunction

Comparison of gingival crevicular fluid and serum human beta‐defensin‐2 levels between periodontal health and disease

Background The aim of this study was to evaluate the levels of serum and gingival crevicular fluid (GCF) human beta-defensin-2 (hBD-2), an antimicrobial peptide that takes roles in inflammatory diseases, in patients with chronic periodontitis (CP). Subjects and Methods A total of one hundred and one individuals, 59 controls and 42 patients with CP, participated in this study. Clinical index measurements were recorded during the periodontal examination, and radiographic evaluation was also performed. The serum and gingival crevicular fluid (GCF) samples were taken from all of the participants, and the hBD-2 levels were determined biochemically by enzyme-linked immunosorbent assay (ELISA). Results In our study, hBD-2 GCF levels in CP (stages II-IV periodontitis based on the new 2018 classification of periodontal diseases) group (2.77 ng/30 s) were higher than in the periodontally healthy (2.51 ng/30 s;p = .047) individuals. In contrast, serum hBD-2 levels in CP (2.92 ng/ml) were lower compared with those in healthy controls (7.75 ng/ml,p < .001). Conclusion Interestingly, our results showed that while higher hBD-2 GCF levels are associated with CP, lower serum hBD-2 levels were detected in CP