Accuracy of Artificial Intelligence Models in Dental Implant Fixture Identification and Classification from Radiographs: A Systematic Review.

Background and Objectives: The availability of multiple dental implant systems makes it difficult for the treating dentist to identify and classify the implant in case of inaccessibility or loss of previous records. Artificial intelligence (AI) is reported to have a high success rate in medical image classification and is effectively used in this area. Studies have reported improved implant classification and identification accuracy when AI is used with trained dental professionals. This systematic review aims to analyze various studies discussing the accuracy of AI tools in implant identification and classification. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed, and the study was registered with the International Prospective Register of Systematic Reviews (PROSPERO). The focused PICO question for the current study was "What is the accuracy (outcome) of artificial intelligence tools (Intervention) in detecting and/or classifying the type of dental implant (Participant/population) using X-ray images?" Web of Science, Scopus, MEDLINE-PubMed, and Cochrane were searched systematically to collect the relevant published literature. The search strings were based on the formulated PICO question. The article search was conducted in January 2024 using the Boolean operators and truncation. The search was limited to articles published in English in the last 15 years (January 2008 to December 2023). The quality of all the selected articles was critically analyzed using the Quality Assessment and Diagnostic Accuracy Tool (QUADAS-2). Results: Twenty-one articles were selected for qualitative analysis based on predetermined selection criteria. Study characteristics were tabulated in a self-designed table. Out of the 21 studies evaluated, 14 were found to be at risk of bias, with high or unclear risk in one or more domains. The remaining seven studies, however, had a low risk of bias. The overall accuracy of AI models in implant detection and identification ranged from a low of 67% to as high as 98.5%. Most included studies reported mean accuracy levels above 90%. Conclusions: The articles in the present review provide considerable evidence to validate that AI tools have high accuracy in identifying and classifying dental implant systems using 2-dimensional X-ray images. These outcomes are vital for clinical diagnosis and treatment planning by trained dental professionals to enhance patient treatment outcomes.

Association between asthma and periodontitis.

The association between asthma and periodontitis is of interest. 20 periodontitis patients with asthma (asthma group) and 20 patients without asthma (non-asthma group) were included based on inclusion and inclusion criteria. Periodontitis was classified according to 2017 periodontal classification and periodontal parameters such as tooth loss, pocket depth, clinical attachment loss, alveolar bone loss, bone reduction index, plaque index, bleeding index and periodontal risk were assessed. Effect of anti-asthmatic drugs and asthma control on periodontal parameters was also assessed. Inter-group comparison of all the continuous variables was done using independent "t" test. Comparison of categorical variables was done using Chi-square test. P value <0.05 was considered statistically significant. Results showed greater severity and higher grade of periodontitis with asthma group as well as with patients on anti-asthmatic drugs and patients with poor controlled asthma. Hence, there is an association between asthma and periodontitis.

Accuracy Comparison between Robot-Assisted Dental Implant Placement and Static/Dynamic Computer-Assisted Implant Surgery: A Systematic Review and Meta-Analysis of In Vitro Studies.

Background and Objectives: The present systematic review and meta-analysis undertake a comparison of studies that examine the accuracy of robot-assisted dental implant placement in relation to static computer-assisted implant surgery (SCAIS), dynamic computer-assisted implant surgery (DCAIS), and freehand procedures. This study aims to provide a comprehensive understanding of the precision of robot-assisted dental implant placement and its comparative efficacy in relation to other placement techniques. Methods: The guidelines recommended by Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) were used to organize and compose this review. Four electronic databases (PubMed, Web of Science, Scopus, and Cochrane) were systematically searched for pertinent articles. Articles were selected following the inclusion and exclusion criteria. Qualitative and quantitative analyses of the selected articles were performed. Results: The initial electronic search resulted in 1087 hits. Based on the inclusion and exclusion criteria, five articles were selected for qualitative analysis, out of which three were considered for quantitative analysis. Three parameters were considered for accuracy evaluation (angular, coronal, and apical deviation). The mean angular deviation was -1.22 degrees (95% CI, -1.06--1.39), the mean coronal deviation was -0.15 mm (95% CI, -0.24--0.07), and the mean apical deviation was -0.19 mm (95% CI, -0.27--0.10). Conclusions: The robotic implant system was found to have significantly lower angular deviations and insignificantly lower coronal and apical deviations compared to DCAIS. Within the limitations of this review, it can be concluded that robot-assisted implant placement in resin models permits higher accuracy compared to DCAIS and SCAIS systems. However, due to the limited number of comparative studies with high heterogeneity, the findings of this review should be interpreted with caution. Further research is necessary to confirm the clinical application of robotics in implant surgery.

Evaluating Soft Tissue Healing after Implant Placement Using Two Different Mouthwashes (Myrrh and Chlorhexidine Gluconate): A Randomized Control Trial.

The use of mouthwash is often recommended by dental experts for dental healing. A double-blind, randomized clinical study was conducted to evaluate the efficacy of two mouthwashes (myrrh and chlorhexidine gluconate) on postoperative pain and their effects on tissues after dental implant placement in 35 patients (18 in the myrrh group and 17 in the chlorhexidine gluconate group). Soft tissue healing was evaluated in terms of wound closure, soft tissue swelling, and the color of the gingiva at 1 week postoperative. To decrease the chances for error, only the participants who did not show preoperative symptoms of infection and those who committed to practicing better oral hygiene were included in the study. The samples were evaluated for the infiltration of inflammatory cells (using inflammatory extent and inflammatory cellularity grades), maturation of collagen (osteoblast activity), and arrangement of cells (for detecting the remodeling phase). A questionnaire pertaining to mouthwash satisfaction, the duration of postoperative pain after the procedure, the time of stoppage of bleeding at the surgical site, and any sensitivity at the surgical site was given to the patients. The Chi-square test and Mann-Whitney U-test were used to analyze the data. The difference in postoperative surgical swelling, pain, bleeding, and redness in the patients was not statistically significant between the myrrh and chlorhexidine gluconate mouthwash groups. However, in the acute phase, the myrrh mouthwash showed a positive impact on the process of wound healing after implant placement. The small sample size and inability to compare wound healing in different anatomical areas of the oral cavity were the study limitations.

Nano-Hydroxyapatite (nHAp) in the Remineralization of Early Dental Caries: A Scoping Review.

(1) Background: Nano-hydroxyapatite (nHAp) has been reported to have a remineralizing effect on early carious lesions. The objective of this scoping review was to analyze the remineralization potential of nano-hydroxyapatite (nHAp)-containing dentifrices, by mapping the existing literature. (2) Methods: This review was performed using the PRISMA-ScR Checklist, which is an extension of the PRISMA Checklist for Systematic Reviews and Meta-Analyses. In this study, the population, concept, and context (PCC) framework was used to find relevant papers published between 2010 and 2021. Nano-hydroxyapatite (nHAp) and dentifrices containing nHAp as one of the ingredients were the two main concepts of the research question. MeSH phrases, keywords, and other free terms relevant to nano-hydroxyapatite and dentifrices were used to search the literature databases. (3) Results: Preliminary searches yielded 59 studies; the title and abstract screening results excluded 11 studies. The remaining studies were thoroughly reviewed by two reviewers on the basis of the inclusion and exclusion criteria. Finally, 28 studies were included, and 20 studies were excluded. Most of the studies that were included reported that when nHAp was used alone, it had many different effects, such as remineralization, caries prevention, less demineralization, brighter teeth, less pain, and remineralization of enamel after orthodontic debonding. (4) Conclusions: Dentifrices that contain nHAp offer a variety of therapeutic and preventative effects. Currently, there is insufficient evidence to support the efficacy of nHAp dentifrices in primary teeth. Additional long-term investigations using standardized protocols are required to reach decisive conclusions about the effects of nHAp dentifrices on primary and permanent dentitions.

Effect of tongue piercing on periodontal and peri-implant health: A cross-sectional case-control study in adults.

OBJECTIVES: The authors hypothesize that periodontal and peri-implant inflammatory parameters are poorer in adult patients with tongue piercing compared with controls. The aim was to assess the influence of tongue piercing on periodontal and peri-implant health status in adults. METHODS: Test and control groups comprised of individuals with and without tongue piercing, respectively. A questionnaire was used to collect information about gender, age, duration of tongue piercing and implants in function, jaw location of the implant, reasoning for wearing the tongue ornament, and oral hygiene and ornament cleaning habits. Full-mouth and peri-implant plaque index (PI), gingival index (GI), clinical attachment loss (CAL), probing depth (PD) and marginal/crestal bone loss (MBL and CBL, respectively) on mesial and distal surfaces of teeth/implants were recorded. The material (plastic or metal) from which, the bar and ball-ends of the ornament were fabricated was also recorded. A p < 0.01 was considered statistically significant. RESULTS: Forty-eight and 49 individuals were included in the test and control groups, respectively. There was no difference in PI, GI, PD, CAL and MBL (mesial and distal) among individuals in the test and control groups. In the test group, peri-implant PI (p < 0.01), GI (p < 0.01), PD (p < 0.01) and mesial (p < 0.01) and distal (p < 0.01) CBL were significantly higher in the anterior mandible compared with implants in other jaw locations. In the control group, there was no difference in peri-implant PI, GI, PD and CBL around implants placed in both jaws. CONCLUSION: Wearing tongue piercings could increase the risks of periodontal and peri-implant diseases particularly in the mandibular anterior segment.