L.M. Gavrikova’s research while affiliated with Volgograd State Medical University and other places

Introduction. Psychoemotional stress is currently recognized as one of the significant risk factors affecting human health. Recent studies have highlighted its role in the development of various dental pathologies, in particular disorders of occlusive relationships. The purpose of this study is to determine the frequency and severity of psychoemotional stress in patients with occlusion disorders, as well as to identify key symptoms of psychological stress that affect dental health. Material and methods: The study was conducted at the Department of Dentistry of Volgograd State Medical University and included 120 patients aged 18 to 44 years with various disorders of occlusive relationships. The patients were divided into three groups depending on the degree of tooth abrasion. The PSM-25 questionnaire (Lemyr-Tessier-Fillion), adapted for the Russian-speaking audience, was used to assess the level of psychoemotional stress. The data were subjected to statistical analysis, including correlation analysis, to identify the relationship between stress levels and the severity of occlusive disorders. Results and their discussion: The results of the study showed that all patients included in the study experienced psychoemotional stress. The most common indicators of psychological stress have been identified: bruxism, clenching, physical malaise, fatigue and sleep disorders. Correlation analysis has demonstrated the presence of a direct relationship between the level of psychoemotional stress and the severity of occlusive disorders. Patients with more pronounced clinical manifestations of occlusal imbalance also had higher stress levels. Conclusion: The study confirmed the significant influence of psychoemotional stress on the development and course of disorders of occlusive relationships. The identification of key symptoms of psychological stress in patients with occlusive disorders is important for practical dentistry, as it allows to improve the diagnosis and treatment of these conditions. However, for a more accurate and differentiated approach to diagnosis, it is necessary to take into account many risk factors and hidden relationships, which requires further research.

The development of neural networks is an urgent task in the modern practice of a dentist due to the need to achieve high rates of interpretation of X-ray images, reduce the time for processing primary medical documentation, and reduce subjective assessment in the diagnosis of dental diseases. The aim of the work is to evaluate the diagnostic possibilities of interpreting X-ray images in dentistry using a trained neural network model. Materials and methods. The study included 300 OPTG patients who had at least 5 teeth without taking into account their group affiliation. The images were randomly divided into 3 groups: I — 200 images for training the neural network model, II — 50 images for monitoring the model during training, III — 50 images for manual marking by dentists (comparison group). Five available “You Only Look Once” v8 neural network models with open source code and different floating-point operation speeds were selected for training: 12, 42, 110, 220 and 344 Gflops. Each model was trained for 5,000 epochs with the registration of intermediate variants of the trained model every 100 epochs. Results. The use of neural networks in the tasks of determining various X-ray contrast structures at the optical imaging laboratory identifies objects with an accuracy of 0.98, provided there are a sufficient number of objects in the training sample. An increase in the number of training epochs increases the quality of detection of each object (0.875) and its segmentation (0.947) to peak values by 2500 epochs and becomes almost unchanged with further training. An increase in the model’s performance parameter is advisable to values of 42 Gflops, a further increase in the indicator did not reveal diagnostic value. In comparison with dentists, the neural network showed a significant increase in the processing speed of a single image, about 25 times faster than a human, and the quality of detection by doctors is 1% better, but a greater contribution to the error was made by objects requiring an increase in the training sample, which once again confirms the need for proper formation of the training dataset. Conclusion. The use of a neural network with a trained model for the detection and interpretation of X-ray images in dentistry has shown high diagnostic value. For the conditions for defining and segmenting objects, it is advisable to use models of such sizes that allow processing objects with a high degree of confidence. A prerequisite for achieving high results is a sufficient training sample, which contributes to improving the quality of detection of objects and their boundaries in X-ray studies.

Introduction. In recent years, there has been a growing interest in digital methods for diagnosing occlusive imbalance both in Russia and abroad. The development of technologies in this area opens up new prospects for improving the diagnosis and treatment of dental diseases. The purpose of this study is to analyze existing digital methods and devices for diagnosing occlusive imbalance, identify their advantages and disadvantages, and assess the prospects for their implementation in clinical practice. Materials and methods: To achieve this goal, a systematic review of 40 scientific publications covering the period from 2016 to 2024 was conducted. The study includes both domestic and international sources from leading scientific electronic libraries and databases. Data on various types of digital devices such as strain gauges, piezoresistive and piezoelectric transducers, pressure sensors and fiber optic sensors are analyzed. Methods of index evaluation of occlusal contacts have also been studied. Results and discussion: The analysis showed that existing digital technologies for the diagnosis of occlusive imbalance have significant potential to improve the accuracy and effectiveness of diagnosis. Load cells, piezoresistive and piezoelectric transducers, as well as pressure sensors and fiber optic sensors provide various approaches to measuring the occlusion force. Despite their high sensitivity and accuracy, the implementation of these technologies faces challenges such as the complexity of equipping clinics and the insufficient level of digital competencies among doctors. Conclusion: Digital diagnostic technologies for occlusal imbalance have significant potential to improve dental practice. However, for the successful implementation of these methods, it is necessary to overcome the existing difficulties associated with equipment and training of specialists. Further efforts in the field of digital technology development, process automation and advanced training of dentists can contribute to more effective diagnosis and treatment of occlusion disorders.

The article presents the experience of developing and applying an expert system based on artificial neural networks to predict the risk of violations of occlusive relationships. The relevance of the study is due to the high prevalence of occlusive disorders and the need for an individual approach in their diagnosis and treatment. The system, based on machine learning methods, analyzes patient data and provides dentists with accurate forecasts and recommendations. A randomized controlled trial involving 150 patients confirmed the effectiveness of the model, demonstrating the accuracy of risk classification with an accuracy of more than 93% for each study. The results confirm the expediency of introducing such technologies into clinical practice to improve the accuracy of diagnosis, optimize treatment processes and prevent complications. The study was conducted as part of the scientific work on the development of a methodology for neural network analysis and forecasting the risk of developing violations of occlusive relationships within the framework of the implementation of the Russian Science Foundation grant dated 12.04.2024 No. 24-25-20098 and the Agreement on the provision from the regional budget (Volgograd region) subsidies dated 31.05.2024 No. 10.

The article examines the current state and development of artificial intelligence (AI) technologies in practical dentistry. The review is devoted to the analysis of existing research and publications, identifying key applications of AI in the diagnosis, treatment and prognosis of dental diseases. The main focus is on neural networks and their use for image analysis, including X-ray images, computed tomography and 3D models of jaws. The importance of using AI for the diagnosis of caries, identification of teeth, visualization of pathological processes, assessment of the morphology of teeth and bone structures, as well as predicting treatment is emphasized. The article presents the results of the authors’ own research, as well as an analysis of the effectiveness of various technologies such as convolutional neural networks (CNN), artificial neural networks (ANN), and discusses achievements in the field of deep learning. The findings confirm that the use of AI can significantly improve diagnostic accuracy, facilitate treatment planning and improve clinical decisions, as well as optimize workflows in dental practice. The study was conducted as part of the scientific work on the development of a methodology for neural network analysis and forecasting the risk of developing violations of occlusive relationships within the framework of the implementation of the Russian Science Foundation grant dated 12.04.2024 No. 24-25-20098 and the Agreement on the provision from the regional budget (Volgograd region) subsidies dated 31.05.2024 No. 10.

Introduction: Violations of occlusive relationships are an urgent problem in dental practice due to the high prevalence, complexity of diagnosis and treatment, as well as the connection with common somatic diseases. These pathologies reduce the quality of life of patients and complicate the process of medical rehabilitation. Prevention aimed at early detection of risk factors is especially important. The purpose of this study is to identify the main risk factors for the development of disorders of occlusive relationships. Materials and methods: A randomized controlled trial was conducted with 120 patients aged 18 to 44 years. The study did not include patients with acute infectious diseases, decompensated chronic diseases, oncology, mental disorders and periodontal inflammation. The assessment included clinical examination, cone beam computed tomography (CBCT), electromyography (EMG), ultrasound examination of the temporomandibular joint (TMJ) and occlusion analysis. Methods of 3D modeling and analysis of the symmetry of the skull were used, as well as the Hamburg test to assess the functional state of the TMJ. The results of the clinical examination were subjected to a hierarchical cluster analysis. Results and discussion: Based on the results of the survey, a group of key risk factors affecting the development of occlusive disorders was identified. The analysis of the data showed that the most significant components are the muscular, articular and jaw complexes, including electromyographic parameters, the size of the articular gap and occlusal contacts. The average value of the Hamburg test among patients was 3.79±0.73 points, which indicates a high prevalence of TMJ dysfunction. Cluster analysis made it possible to identify three main groups of risk factors, including muscle, joint and dental signs. Conclusion: The identification of risk factors for the development of occlusive disorders plays a key role in improving the diagnosis and treatment of patients. The use of cluster analysis and modern technologies, such as 3D modeling and artificial intelligence, makes it possible to increase the effectiveness of prevention and treatment of this pathology.

AIMS: to determine the frequency of occurrence and severity of psycho-emotional stress in patients with disorders of occlusal relationships. MATERIALS AND METHODS: The level of psycho-emotional stress was studied in 120 patients with disorders of occlusal relationships. After a clinical examination, all patients were divided into 3 groups depending on the level of abrasion of hard dental tissues. To determine the level of psycho-emotional stress of the examined patients, a questionnaire was conducted according to the PSM-25 psychological stress scale (Lemyr-Tessier-Fillion) in adaptation of the Russian version of the method according to N.E. Vodopyanova. RESULTS: The patients were divided into 3 groups, where 42 people had abrasion of teeth within the enamel (group 1), 49 patients had damage to hard tissues within the enamel and partially dentin (group 2), while 29 patients had abrasion within dentin (group 3). It was revealed that all respondents are exposed to psycho-emotional stress in everyday life to varying degrees. The severity of stress increases depending on the clinical manifestations of occlusion disorders. It was revealed that the frequency of occurrence of psychological tension of varying degrees of severity is 100%. The most common indicators of psychological stress in patients with disorders of occlusal relationships are bruxism, clenching (average level in group 1 - 3.08±0.099, in group 2 - 4.87±0.185, in group 3 - 6.08±0.122), physical malaise (average level for groups is 4.02±0.072, 5.62±0.107, 6.02±0.12, respectively), fatigue (group 1 - 4.31±0.103, group 2 - 5.92±0.124, group 3 - 7.31±0.263), sleep disorders (average intensity by group: 5.28±0.121 in group 1, 5.69±0.165 in group 2, 6.28±0.151 in group 3, respectively). CONCLUSIONS: The identified level of stress serves as a quantitative integral indicator for the implementation of an interdisciplinary approach in the management of these patients and, as a consequence, the need for consulting support from specialists for the purpose of psychological correction.

Relevance. Occlusal disorders are not only predictors of oral diseases but are also associated with systemic conditions such as endocrine, cardiovascular, and cognitive disorders, highlighting their broader significance in medicine. The digitization of diagnostic processes and the integration of computer technologies into traditional methods offer promising advancements in assessing occlusal status. This makes the analysis of digital methods for diagnosing occlusal relationship disorders particularly relevant. Purpose. To evaluate digital methods and devices used for diagnosing occlusal relationship disorders. Material and methods. A systematic review was conducted, analyzing 40 scientific publications from 2016 to 2024 that focus on digital methods for diagnosing occlusal imbalance. The study assessed electronic devices that measure occlusal force by converting mechanical force into electrical signals using various sensors. These digital methods are employed to evaluate the functional state of the masticatory system, including the detection of temporomandibular joint disorders, mandibular fractures, and occlusal deformities, as well as to monitor occlusal force dynamics during treatment. Recent advancements in portable electronic sensors suggest potential applications for their integration with control chips into dental prostheses or occlusal stabilization splints, allowing real-time monitoring of tooth compression forces, potentially enhanced by artificial intelligence. Results. The development of new diagnostic methods and devices equipped with highly sensitive sensors for measuring masticatory pressure opens new avenues for identifying clinical parameters that were previously difficult to analyze. Recent advances in hardware technology, particularly those utilizing neural network analysis, have the potential to expedite accurate diagnosis and predict the risk of complications. Conclusion. Both in Russia and internationally, significant progress is being made in the development of digital methods for diagnosing occlusal imbalance. These methods are poised to become a priority in the future of dental practice. However, the adoption of digital occlusal methods into routine dental practice is currently hindered by challenges related to the availability of digital equipment in clinics and the insufficient digital skills of many dentists. Addressing these challenges is crucial for improving the quality of dental care for patients with occlusal disorders.

Background. Effective treatment of oral candidiasis is especially relevant due to the increase in patients with recurrent fungal lesions of the oral cavity caused by the growing number of Candidaspp. strains refractory to antimycotic drugs. The paper presents the results of the study on the clinical efficacy of etiotropic therapy in patients with chronic recurrent course of oral candidiasis. Objective. To assess the effectiveness of etiotropic therapy in patients with chronic recurrent oral candidiasis. Methods. A randomized controlled clinical trial was conducted in 56 patients with chronic recurrent oral candidiasis aged 45 to 74 years. Examination and treatment of patients was performed at the Department of Dentistry of Volgograd State Medical University and at Volgograd Regional Clinical Dental Polyclinic (Volgograd, Russia). Study timeline: September 2020 — November 2022. Patients were divided into 2 groups depending on the antimycotic drug used: in the main group, patients took voriconazole, in the control group — fluconazole. In addition to etiotropic therapy, patients of both groups were prescribed complex treatment aimed at stimulating the immune protection of the body, restoring vitamin and mineral deficiency, and correcting the imbalance of the oral ecosystem. The patients underwent local symptomatic therapy: antiseptic treatment with 0.06% chlorhexidine bigluconate solution, anesthesia with 15% lidocaine gel, and 3.44% retinol oil solution to stimulate epithelization. Oral sanitation and professional hygiene were recommended for patients to prevent oral candidiasis. In order to restore chewing function, patients were referred to prosthodontic treatment. The main reference point of the study was to assess the effectiveness of the therapy, both by clinical criteria and by evaluating the results of bacterial culture test in order to record the quantitative, species and susceptibility profile of Candidaspp. strains in 3 weeks, 6 and 12 months after the end of treatment. Analysis and statistical processing of the obtained data were performed using Excel program to MS Windows 10 (Microsoft Corp., USA). Results. The most common pathogenic agent of chronic recurrent forms of oral candidiasis is C. albicans (69.6%), followed by C. non-albicans species — C. krusei (10.7%), C. tropicalis (10.7%) and C. glabrata (8.9%). Analysis of the quantitative characteristics of Candidaspp. using bacterial culture test revealed a high and moderate number of Candidaspp. CFU in most clinical isolates before treatment, and no such cases in patients of the main group after treatment. The susceptibility test of yeast fungi to fluconazole and itraconazole showed the presence of isolates with dose-dependent susceptibility, and the resistance of individual samples C. krusei to fluconazole and C. glabrata (16.7% and 60%, respectively) and to itraconazole (33.3% and 100%, respectively). All Candidaspp. isolates were found to be highly susceptible to voriconazole. The efficacy of the combined treatment of an episode with voriconazole is 95.4%. Continued suppressive therapy with voriconazole resulted in relapse prevention in 98.3% of patients. Etiotropic therapy with voriconazole provided a stable clinical effect (92.7%) after a year of follow-up. Conclusion. The results of the study confirm the effectiveness of etiotropic therapy with voriconazole for chronic oral candidiasis complicated by a recurrent course, especially in case of detected C. non-albicans or fluconazole- and itraconazole-resistant C. albicans , or if it is impossible to identify the pathogenic agent.

Relevance. Currently, a significant increase in diseases of the oral mucosa, manifested by inflammatory and destructive lesions, has been revealed. To determine the correct tactics for the treatment of inflammatory and destructive lesions in lichen planus, it is necessary to comprehensively assess the situation in the oral cavity, taking into account planimetry data, the size of the inflammatory background, the presence of exudate, the severity of pain syndrome, and also include criteria for the stages of the lesion in the evaluation system, which requires a personalized and differentiated approach to patient management tactics. The purpose of this work was to develop and substantiate a hardware and software complex for the diagnosis of diseases of the oral mucosa. Materials and methods. The study involved 34 patients with erosive and ulcerative form of lichen planus. The patients were diagnosed with pathological elements of the oral mucosa using the developed hardware and soft-ware complex. Pain was determined (in points), the area of inflammation, the area of fibrinous plaque, the total area of the lesion for 14 days. Assessment of the stages of the pathological process contributed to the differentiated appointment of pharmaceuticals. According to the results of the clinical examination, the effectiveness of the hardware and software complex for the diagnosis of diseases of the oral mucosa has been proved and justified. Conclusion. During the study, it was reliably proved that the use of a hardware and software complex is advisable to include in the algorithm of examination of patients with diseases of the oral mucosa. No side effects and complications were detected. When drawing up a treatment plan, it is necessary to approach each patient individually, depending on the clinical situation.