中华口腔医学杂志最新文献

The correct working posture of dentists is not only the premise of clinical diagnosis, treatment quality and safety but also an important guarantee for the occupational health of dentists. Presently, research on the working posture of dental professionals and related influencing factors is relatively mature internationally. Still, the dental curriculums in our country have not systematically introduced theoretical knowledge and standards related to working posture. This review analyzes and summarizes previous literature on the importance of dental working posture, criteria, assessment methods, and influencing factors, in hopes of providing references and theoretical supports for future guidelines and standards.

Maxillary sinus is located in the maxilla bone with the largest volume in all sinuses and is closest to the roots of maxillary posterior teeth, especially the mesiobuccal root of the maxillary second molar. The thickness of the normal maxillary sinus mucosa is about 1 mm. When stimulated or infected, it shows thickening of the mucosa. Periodontitis is one of the most common oral diseases in human beings, and the complex root anatomy of the maxillary molars aggravates the difficulty of inflammation control. Severe periodontitis of maxillary molars without effective treatment can affect the maxillary sinus, increasing the possibility of the mucosa thickening, and is also one of the reasons for the occurrence of odontogenic maxillary sinusitis (OMS). There are many different schemes for the treatment of OMS caused by severe periodontitis of maxillary molars. Extraction of teeth with severe periodontal disease without retention value or successful periodontal treatment can significantly reduce the thickness of maxillary sinus mucosa. For the patients with uncontrollable sinusitis by using drug treatment and eliminating odontogenic causes, or ones with severe symptoms, periodontal treatment and endoscopic sinus surgery can be combined to effectively control the periodontitis related maxillary sinusitis.

Objective: To explore and evaluate the feasibility and accuracy of using optical coherence tomography and optical coherence microscope (OCT/OCM) for diagnosis of oral cancer. Methods: In this study, OCT/OCM was utilized to image the oral mucosa specimens. A total of 289 ex vivo oral mucosa specimens were collected from 68 patients with oral cancer who were hospitalized at Department of Oral and Maxillofacial Head and Neck Tumors, Capital Medical University School of Stomatology, between January 2021 and February 2023, resulting in a dataset of 1 445 OCT/OCM images. By observing the characteristic patterns in the OCT/OCM images, including normal oral mucosa, epithelial abnormal proliferation (mild, moderate, severe), and oral cancer, these patterns were matched with corresponding pathological images. A diagnostic study was conducted, employing pathological diagnosis as the gold standard and utilizing a double-blind experimental design involving three diagnostic evaluators who participated in the analysis and diagnosis of OCT/OCM images. Results: The OCT/OCM images demonstrated good correlation with the corresponding pathological images, and diagnostic criteria were established based on the comparative results. In the diagnostic study involving three investigators, the accuracy was 82%, sensitivity was 84% (95%CI: 80%-88%), and specificity was 81% (95%CI: 77%-85%). There was a high level of agreement among the observers (kappa=0.614), indicating substantial concordance in the diagnostic results among the three investigators. Conclusions: This study demonstrates the potential of OCT/OCM for diagnosis of oral cancer. The technology accurately distinguishes between normal oral mucosa, epithelial abnormal proliferation and oral cancer.

The treatment of craniomaxillofacial (CMF) defects and deformities is highly challenging due to the complex anatomical structures, significant individual variations and high demands for personalized reconstruction. In recent decades, the integration of cutting-edge technologies from fields such as computer science, mechanical engineering, and material science into medicine has greatly facilitated the transformation of CMF surgery from traditional, experience-based approaches to digitalized and intelligent methods. This review thoroughly analyzes the development and application areas of digital technology in CMF surgery including virtual surgical planning and facial prediction, three-dimensional printing, computer-assisted navigation and robotic surgery, virtual and mixed reality, as well as big data and artificial intelligence technologies. The aim is to offer comprehensive and in-depth reference information for the clinical practice in digital CMF surgery.

Objective: To analyze the influence of operator's experience on the quality and success rate of root canal treatment with new nickel-titanium instruments, providing support for improving the success rate of root canal treatment with new nickel-titanium instruments in clinic. Methods: Cases of root canal treatment and non-surgical root canal retreatment with 6-12 months recall performed by residents (resident group) with experience of 1-3 years and endodontic specialists (specialist group) with experience of 5-7 years were collected from the electronic medical system of the Department of Endodontics, School of Stomatology, Capital Medical University, from September 2020 to August 2021. All cases were prepared by engine-driven glide path files and controlled memory nickel-titanium finishing files. Chi-square test and logistic regression were used to analyze the differences and influencing factors of complications, filling quality and success rate of root canal treatment between the two groups. Results: A total of 277 cases performed by 24 residents and 3 specialists were included, 169 in the resident group and 108 in the specialist group. The clinical incidence of flare-ups was significantly higher in the resident group [3.6% (6/169)] than in the specialist group [0(0/108)] (P=0.048). There were no significant differences in ledges, root canal transportations, perforations, or instrument separations between the two groups (P>0.05). The prevalence of satisfactory fillings was 62.7% (106/169) in the resident group, which was significantly lower than that in the specialist group [86.1% (93/108)] (P<0.05). The success rate of root canal treatment was 91.7% (155/169) and 94.4% (102/108) in the resident group and the specialist group, respectively, with no significant differences (χ²=0.73,P=0.392). Multivariate analysis showed that the success rate of root canal treatment was related to complications and quality of root fillings (P<0.05). Conclusions: Higher success rate of root canal treatment could be achieved by residents and endodontic specialists with engine-driven glide path files and controlled memory nickel-titanium files.

In recent years, robots have been gradually applied in the field of oral implantation. Compared with static guide and dynamic navigation, robot-assisted implant surgery has the characteristics of high precision, high stability and high safety, but there are still various factors affecting the accuracy of implantation in the operation process. Existing studies focus on the accuracy of robot-assisted oral implant surgery, while there are few studies on the image factors affecting the accuracy of robot-assisted oral implant surgery. Therefore, this paper analyzes the factors affecting the accuracy of robot-assisted oral implant surgery from the aspects of the type and operation of the implant robot, in order to provide evidence for the application of the implant robot in the field of oral implant.

The oral implant surgery robot could achieved basic "surgical operation intelligence"; however, "decision-making artificial intelligence" has not yet been achieved. The author previously discussed the specific concept of decision-making artificial intelligence. During our exploration of decision-making artificial intelligence, our team further integrated the clinical diagnosis and treatment process of oral implantation, along with the data characteristics of decision indicators and the distribution characteristics of demographic information. As a result, we identified five key scientific and technological issues in the process of decision-making artificial intelligence, namely the construction of a specialized annotation database for oral implantation, the prediction of quantitative indicators, the application of three-dimensional imaging, the solution of data imbalance within indicators, and the joint output of multi-property and multimodal indicators in clinical pathways. This paper will review artificial intelligence research in oral implantology and our team's research progress, elaborating on the aforementioned challenges in intelligentization. It aims to provide references for addressing the mentioned scientific issues and guiding future research directions in the construction of decision-making artificial intelligence in oral medicine.

Periodontal disease is a common and frequently-occurring disease in China. Early detection, diagnosis, and treatment of periodontal disease are of great significance for achieving universal oral health and even systemic health. Artificial intelligence endows machines with the ability to mimic human intelligent behavior, and is commonly used in medical field with both physical and virtual forms. Virtual artificial intelligence empowers traditional experience in the application of periodontal disease risk assessment and diagnosis, with the potential to develop a variety of oral health screening tools. It helps to provide new evidence for the prognosis of periodontal disease, improve the accuracy and efficiency of diagnosis, reduce technical sensitivity and further promote the periodontal treatment transformation from "treatment-oriented" to "prevention-oriented". This paper reviews the current applications and progresses of virtual artificial intelligence in periodontal risk assessment and diagnosis, as well as its limitations, providing ideas for future researches on the application of virtual artificial intelligence in this field.