Peripheral calcifying odontogenic cyst: a case report and comprehensive review of 60 years of literature.

Peripheral Calcifying Odontogenic Cyst (PCOC) is the extraosseous form of calcifying odontogenic cyst that is limited to peripheral soft tissue without bony involvement. This case report presents a case of PCOC manifested as a progressive growth of gingival mass in a young male treated with excisional biopsy. Histological examination confirmed diagnosis of PCOC with presence of characteristic ghost cells and sporadic calcifications. No recurrence of the lesion and no complication were noted at three-year follow-up. Review of available literature on PCOC noted a predilection of occurrence in the mandible (61%) and in the anterior area of the jaws (58%). Mean age of patients was 41.7 ± SD25.43 (7-83) and 95% CI [33.6, 49.8] yrs. Mean size of the lesions was 1.38 ± SD1.1 (0.5-4.3) and 95% CI [0.93, 1.83] cm. Gender distribution was noted to be 51.3% male and 48.7% female.

Identification of microbiological factors associated with periodontal health disparities.

The present study aimed at identifying risk factors associated with periodontitis development and periodontal health disparities with emphasis on differential oral microbiota. The prevalence of periodontitis is recently rising dentate adults in the US, which presents a challenge to oral health and overall health. The risk of developing periodontitis is higher in African Americans (AAs), and Hispanic Americans (HAs) than in Caucasian Americans (CAs). To identify potentially microbiological determinations of periodontal health disparities, we examined the distribution of several potentially beneficial and pathogenic bacteria in the oral cavities of AA, CA, and HA study participants. Dental plaque samples from 340 individuals with intact periodontium were collected prior to any dental treatment, and levels of some key oral bacteria were quantitated using qPCR, and the medical and dental histories of participants were obtained retrospectively from axiUm. Data were analyzed statistically using SAS 9.4, IBM SPSS version 28, and R/RStudio version 4.1.2. Amongst racial/ethnic groups: 1) neighborhood medium incomes were significantly higher in the CA participants than the AA and the HA participants; 2) levels of bleeding on probing (BOP) were higher in the AAs than in the CAs and HAs; 3) Porphyromonas gingivalis levels were higher in the HAs compared to that in the CAs; 4) most P. gingivalis detected in the AAs were the fimA genotype II strain that was significantly associated with higher BOP indexes along with the fimA type IV strain. Our results suggest that socioeconomic disadvantages, higher level of P. gingivalis, and specific types of P. gingivalis fimbriae, particularly type II FimA, contribute to risks for development of periodontitis and periodontal health disparities.

Application of deep machine learning for the radiographic diagnosis of periodontitis.

OBJECTIVE: Successful application of deep machine learning could reduce time-consuming and labor-intensive clinical work of calculating the amount of radiographic bone loss (RBL) in diagnosing and treatment planning for periodontitis. This study aimed to test the accuracy of RBL classification by machine learning. MATERIALS AND METHODS: A total of 236 patients with standardized full mouth radiographs were included. Each tooth from the periapical films was evaluated by three calibrated periodontists for categorization of RBL and radiographic defect morphology. Each image was pre-processed and augmented to ensure proper data balancing without data pollution, then a novel multitasking InceptionV3 model was applied. RESULTS: The model demonstrated an average accuracy of 0.87 ± 0.01 in the categorization of mild (< 15%) or severe (≥ 15%) bone loss with fivefold cross-validation. Sensitivity, specificity, positive predictive, and negative predictive values of the model were 0.86 ± 0.03, 0.88 ± 0.03, 0.88 ± 0.03, and 0.86 ± 0.02, respectively. CONCLUSIONS: Application of deep machine learning for the detection of alveolar bone loss yielded promising results in this study. Additional data would be beneficial to enhance model construction and enable better machine learning performance for clinical implementation. CLINICAL RELEVANCE: Higher accuracy of radiographic bone loss classification by machine learning can be achieved with more clinical data and proper model construction for valuable clinical application.

Use of the deep learning approach to measure alveolar bone level.

AIM: The goal was to use a deep convolutional neural network to measure the radiographic alveolar bone level to aid periodontal diagnosis. MATERIALS AND METHODS: A deep learning (DL) model was developed by integrating three segmentation networks (bone area, tooth, cemento-enamel junction) and image analysis to measure the radiographic bone level and assign radiographic bone loss (RBL) stages. The percentage of RBL was calculated to determine the stage of RBL for each tooth. A provisional periodontal diagnosis was assigned using the 2018 periodontitis classification. RBL percentage, staging, and presumptive diagnosis were compared with the measurements and diagnoses made by the independent examiners. RESULTS: The average Dice Similarity Coefficient (DSC) for segmentation was over 0.91. There was no significant difference in the RBL percentage measurements determined by DL and examiners ( p=.65 ). The area under the receiver operating characteristics curve of RBL stage assignment for stages I, II, and III was 0.89, 0.90, and 0.90, respectively. The accuracy of the case diagnosis was 0.85. CONCLUSIONS: The proposed DL model provides reliable RBL measurements and image-based periodontal diagnosis using periapical radiographic images. However, this model has to be further optimized and validated by a larger number of images to facilitate its application.

Potential Microbiological Risk Factors Associated With Periodontitis and Periodontal Health Disparities.

Periodontitis disproportionately affects different racial and ethnic populations. In this study, we used qPCR to determine and compare oral microbial profiles in dental plaque samples from 191 periodontitis patients of different ethnic/racial backgrounds. We also obtained the periodontal parameters of these patients retrospectively using axiUm and performed statistical analysis using SAS 9.4. We found that in this patient cohort, neighborhood median incomes were significantly higher among Caucasians Americans (CAs) than among African Americans (AAs) and Hispanic Americans (HAs). Levels of total bacteria and Porphyromonas gingivalis, a keystone periodontal pathogen, were not evenly distributed among the three groups. We confirmed our previous findings that Streptococcus cristatus reduces P. gingivalis virulence potential and likely serves as a beneficial bacterium. We also showed the ratio of S. cristatus to P. gingivalis to be significantly higher in CAs than in HAs and AAs. Our results suggest that higher levels of P. gingivalis and lower ratios of S. cristatus to P. gingivalis may contribute to periodontal health disparities.

Immediate Implant Placement and Provisionalization in the Esthetic Zone: A 6.5-Year Follow-Up and Literature Review.

The success of dental implant therapy in the esthetic zone requires not only functional osseointegration but also a satisfactory esthetic outcome. To establish harmony, balance, and continuity of gingival architecture between an implant restoration and the adjacent natural dentition is challenging. Immediate implant placement and provisionalization following tooth extraction have been documented as a predictable treatment modality, with fewer surgical interventions needed, to replace a missing tooth in the esthetic zone. This case report illustrates immediate implant placement and provisionalization to replace a failing maxillary right central incisor while maintaining optimal gingival esthetics. The maxillary right central incisor was extracted without flap elevation to minimize soft and hard tissue trauma. Immediately afterwards, the implant was installed using a surgical stent and restored with a provisional crown that had no occlusal contacts. During healing, no significant adverse effects were observed clinically or radiographically. This proposed treatment modality provided the patient with immediate esthetics, function, and comfort without any complications during a follow-up period of 6.5 years.

The impact of smoking on non-surgical periodontal therapy: A systematic review and meta-analysis.

AIM: Smoking is a risk factor for periodontitis. This study aimed to evaluate the impact of smoking on clinical outcomes of non-surgical periodontal therapy. MATERIALS AND METHODS: Electronic databases were searched to screen studies published before May 2020. The included studies had to have two groups: smokers (S) and non-smokers (NS) with periodontitis. The outcomes evaluated were differences between groups in probing depth (PD) reduction and clinical attachment level (CAL) gain after non-surgical periodontal therapy. Meta-regressions were conducted to evaluate correlations between outcomes and other contributing factors. RESULTS: Seventeen studies were included. The post-treatment PD reduction in the S group was smaller than in the NS group (weighted mean difference in PD reduction: -0.33 mm, 95% confidence interval (CI): [-0.49, -0.17], p < .01). The CAL gain in the S group was also smaller than in the NS group (weighted mean difference in CAL gain: -0.20 mm, CI: [-0.39, -0.02], p < .01). Additionally, baseline PD significantly affected the difference in PD reduction between two groups. CONCLUSIONS: Smoking negatively impacts clinical responses to non-surgical periodontal therapy. Smokers with periodontitis have significantly less PD reduction and CAL gain than non-smokers.

Dental implant bioactive surface modifications and their effects on osseointegration: a review.

BACKGROUND: The purpose of this article is to review and update the current developments of biologically active dental implant surfaces and their effect on osseointegration. METHODS: PubMed was searched for entries from January 2006 to January 2016. Only in-vivo studies that evaluated the effects of biomolecular coatings on titanium dental implants inserted into the bone of animals or humans were included. RESULTS: Thirty four non-review studies provided data and observations were included in this review. Within the criteria, four categories of biomolecular coatings were evaluated. The potential biomolecules include bone morphogenetic proteins in 8 articles, other growth factors in 8 articles, peptides in 5 articles, and extracellular matrix in 13 articles. Most articles had a healing period of 1 to 3 months and the longest time of study was 6 months. In addition, all studies comprised of implants inserted in animals except for one, which evaluated implants placed in both animals and humans. The results indicate that dental implant surface modification with biological molecules seem to improve performance as demonstrated by histomorphometric analysis (such as percentage of bone-to-implant contact and peri-implant bone density) and biomechanical testing (such as removal torque, push-out/pull-out tests, and resonance frequency analysis). CONCLUSIONS: Bioactive surface modifications on implant surfaces do not always offer a beneficial effect on osseointegration. Nevertheless, surface modifications of titanium dental implants with biomolecular coatings seem to promote peri-implant bone formation, resulting in enhanced osseointegration during the early stages of healing. However, long-term clinical studies are needed to validate this result. In addition, clinicians must keep in mind that results from animal experiments need not necessarily reflect the human clinical reality.

The Effect of Platform Switching on Periimplant Crevicular Fluid Content During Early Wound Healing.

PURPOSE: The objective of this study was to investigate the soft tissue response and periimplant crevicular fluid (PICF) content around platform-switched (PS) and platform-matched (PM) implants during early healing. MATERIALS AND METHODS: Nonsmokers treatment planned to receive a single implant in 2 quadrants were recruited. Two-stage implant placement protocol with 1 PM and 1 PS implant was implemented. Periimplant probing depths (PDs), modified sulcus bleeding index, and plaque indices were recorded, and PICF was collected at 1, 2, 4, and 6 weeks after abutment connection. RESULTS: PD readings were higher at week 1 than at week 6 for both groups (P = 0.0005). PD was statistically deeper in PM than in PS at week 1 (P = 0.03). There was a time-dependent decrease in total PICF volume for both groups. This decrease was statistically significant for PS (P = 0.0005), with no differences between the 2 groups at any time (P > 0.05). The decrease observed in both PM and PS for PICF interleukin 6 and macrophage inflammatory protein-1ß, and in PS for tumor necrosis factor-α (TNF-α) was statistically significant (P ≤ 0.03). TNF-α was statistically higher in PS than in PM at week 1 (P = 0.005). CONCLUSION: Within the limits of this study, it seems that periimplant soft tissue response around PM and PS implants is mostly similar during the early healing period.