Hasil untuk "Dentistry"

A. Dawood, B. Marti, V. Sauret-Jackson et al.

R. Miron, G. Zucchelli, M. Pikos et al.

Abdullah Barazanchi, Kai Chun Li, Basil Al-Amleh et al.

Alejandra Alvarado-Orozco, Rim Bourgi, Rim Bourgi et al.

AimThis systematic review and meta-analysis aimed to evaluate the fracture resistance of permanent teeth restored with polyethylene fiber-reinforced composite resin restoration.Material and methodsThe following PICOS framework used was: Population, permanent teeth requiring restorative treatment; Intervention, polyethylene fiber use; Control, composite resin restorations without fiber reinforcement, or conventional fiber posts; Outcome, fracture resistance (in Newtons); Study design, in vitro studies. A literature search was conducted independently by two reviewers up to May 18, 2025, using electronic databases (PubMed, ISI Web of Science, SciELO, Scopus, and Embase). In vitro studies examining the fracture resistance of permanent teeth restored with polyethylene fiber-reinforced resin composite restorations were included. Meta analyses were performed by comparing the standardized mean differences in the fracture resistance of teeth restored using polyethylene fibers and the teeth restored only with resin composite. Additional analysis was performed comparing the risk difference of the number of unfavorable fractures. Separate analyses were performed when fiber posts were used. A p-value of less than 0.05 was considered statistically significant.ResultsThe fracture resistance of polyethylene fiber-reinforced restorations was higher compared to non-fiber reinforced composite restorations (p < 0.001). Also, the number of unfavorable fractures were significant lower when polyethylene fibers were used (p < 0.001).ConclusionThe findings suggest that the fracture resistance of permanent teeth may be improved with the use of polyethylene fibers. However, clinical performance outcomes are necessary to validate these in vitro results.Systematic Review RegistrationThe protocol for the systematic review was developed a priori and can be accessed at: https://doi.org/10.17605/OSF.IO/5K8XB.

Y. O. Crystal, R. Niederman

This article reviews current evidence on the effectiveness of silver diamine fluoride (SDF) as a caries arresting and preventive agent. It provides clinical recommendations around SDF's appropriate use as part of a comprehensive caries management program. Systematic reviews confirm that SDF is effective for caries arrest on cavitated lesions in primary teeth and root caries in the elderly. It may also prevent new lesions. Application is easy, noninvasive, affordable, and safe. Although it stains the lesions dark as it arrests them, it provides clinicians with an additional tool for caries management when esthetics are not a primary concern.

T. Hanawa

This review scientifically compares the properties of zirconia and titanium, but does not identify the best among them as an implant material. Surface treatment and modification to improve tissue bonding and inhibit bacterial adhesion are not considered in this review. The mechanical properties of titanium are superior to those of zirconia; some studies have shown that zirconia can be used as a dental implant, especially as an abutment. Extensive surface treatment research is ongoing to inhibit bacterial adhesion and improve osseointegration and soft tissue adhesion phenomena which make it difficult to evaluate properties of the materials themselves without surface treatment. Osseointegration of titanium is superior to that of zirconia itself without surface treatment; after surface treatment, both materials show comparable osseointegration. The surface morphology is more important for osseointegration than the surface composition. To inhibit bacterial adhesion, zirconia is superior to titanium, and hence, more suitable for abutments. Both materials show similar capability for soft tissue adhesion.

R. M. Mizumoto, B. Yılmaz

Statement of problem. Intraoral scan body (ISB) design is highly variable and its role in the digital workflow and accuracy of digital scans is not well understood. Purpose. The purpose of this systematic review was to determine the relevant reports pertaining to ISBs with regard to design and accuracy and to describe their evolution and role in the digital dentistry workflow. Special attention was placed on their key features in relation to intraoral scanning technology and the digitization process. Materials and methods. A MEDLINE/PubMed search was performed to identify relevant reports pertaining to ISB usage in dentistry. This search included but was not limited to scan body features and design, scan body accuracy, and scan body techniques and the role of ISBs in computer‐aided design and computer‐aided manufacturing (CAD‐CAM) processes. Commercially available scan bodies were examined, and a patient situation was shown highlighting the use of ISBs in the digital workflow. Results. Deficiencies in the reports were found regarding various scan body topics, including ISB features/design, accuracy, and the role of ISBs in CAD‐CAM processes. Conclusions. ISBs are complex implant‐positioning‐transfer devices that play an essential role in the digital workflow and fabrication of accurately fitting implant‐supported restorations. With scanner technology rapidly evolving and becoming more widespread, future studies are needed and should be directed toward all parts of the digital workflow when using ISBs. By understanding the basic components of ISBs and how they relate to digital scanning and CAD‐CAM technology, more emphasis may be placed on their importance and usage in the digital workflow to ensure accurate transfer of implant position to the virtual and analog definitive cast. Efforts should be made by clinicians to identify an optimal ISB design in relation to the specific intraoral scanning technology being used.

Franciele Floriani, Bayaan Jabr, Silvia Rojas-Rueda et al.

Background: This study evaluated the effect of charcoal-containing toothpaste on the surface roughness of CAD/CAM lithium disilicate ceramic (e.max CAD) after simulated toothbrushing. Methods: Forty-eight e.max CAD ceramic specimens were divided into four groups (n = 12) and subjected to 18,000 brushing cycles using a toothbrushing simulator. The groups included Crest 3D White Charcoal, Colgate Optic White with Charcoal, Arm & Hammer Charcoal White, and a control group (conventional toothpaste). Surface roughness was measured with a profilometer before and after brushing, and scanning electron microscopy (SEM) was used for topographical analysis. Statistical analysis was performed using the Kruskal–Wallis test and post hoc comparisons. Results: Significant differences in surface roughness were found among the groups (<i>p</i> < 0.001). The mean roughness values were 540.70 ± 21.68 µm (Control), 294.88 ± 11.49 µm (Crest 3D White Charcoal), 1157.00 ± 52.85 µm (Colgate Optic White with Charcoal), and 593.37 ± 37.69 µm (Arm & Hammer Charcoal White). Post hoc analysis showed that Colgate Optic White with Charcoal had the highest roughness, which was significantly different from all other groups (<i>p</i> < 0.001). SEM analysis revealed severe surface degradation with Colgate Optic White with Charcoal, while Crest 3D White Charcoal caused minimal changes. Conclusions: Charcoal-containing toothpastes vary in abrasiveness, with Colgate Optic White with Charcoal causing the most significant surface roughness and damage to lithium disilicate ceramics.

Aida Meto

Bearing in mind the expression, “<i>The art challenges the technology, and the technology inspires the art</i>”, we say that oral surgery is changing rapidly due to the introduction of new technologies that improve the way surgical treatments are planned and performed [...]

Zijie Meng, Jin Hao, Xiwei Dai et al.

Diagnosing and managing oral diseases necessitate advanced visual interpretation across diverse imaging modalities and integrated information synthesis. While current AI models excel at isolated tasks, they often fall short in addressing the complex, multimodal requirements of comprehensive clinical dental practice. Here we introduce DentVLM, a multimodal vision-language model engineered for expert-level oral disease diagnosis. DentVLM was developed using a comprehensive, large-scale, bilingual dataset of 110,447 images and 2.46 million visual question-answering (VQA) pairs. The model is capable of interpreting seven 2D oral imaging modalities across 36 diagnostic tasks, significantly outperforming leading proprietary and open-source models by 19.6% higher accuracy for oral diseases and 27.9% for malocclusions. In a clinical study involving 25 dentists, evaluating 1,946 patients and encompassing 3,105 QA pairs, DentVLM surpassed the diagnostic performance of 13 junior dentists on 21 of 36 tasks and exceeded that of 12 senior dentists on 12 of 36 tasks. When integrated into a collaborative workflow, DentVLM elevated junior dentists' performance to senior levels and reduced diagnostic time for all practitioners by 15-22%. Furthermore, DentVLM exhibited promising performance across three practical utility scenarios, including home-based dental health management, hospital-based intelligent diagnosis and multi-agent collaborative interaction. These findings establish DentVLM as a robust clinical decision support tool, poised to enhance primary dental care, mitigate provider-patient imbalances, and democratize access to specialized medical expertise within the field of dentistry.

Yaqi Wang, Zhi Li, Chengyu Wu et al.

Orthopantomogram (OPGs) and Cone-Beam Computed Tomography (CBCT) are vital for dentistry, but creating large datasets for automated tooth segmentation is hindered by the labor-intensive process of manual instance-level annotation. This research aimed to benchmark and advance semi-supervised learning (SSL) as a solution for this data scarcity problem. We organized the 2nd Semi-supervised Teeth Segmentation (STS 2024) Challenge at MICCAI 2024. We provided a large-scale dataset comprising over 90,000 2D images and 3D axial slices, which includes 2,380 OPG images and 330 CBCT scans, all featuring detailed instance-level FDI annotations on part of the data. The challenge attracted 114 (OPG) and 106 (CBCT) registered teams. To ensure algorithmic excellence and full transparency, we rigorously evaluated the valid, open-source submissions from the top 10 (OPG) and top 5 (CBCT) teams, respectively. All successful submissions were deep learning-based SSL methods. The winning semi-supervised models demonstrated impressive performance gains over a fully-supervised nnU-Net baseline trained only on the labeled data. For the 2D OPG track, the top method improved the Instance Affinity (IA) score by over 44 percentage points. For the 3D CBCT track, the winning approach boosted the Instance Dice score by 61 percentage points. This challenge confirms the substantial benefit of SSL for complex, instance-level medical image segmentation tasks where labeled data is scarce. The most effective approaches consistently leveraged hybrid semi-supervised frameworks that combined knowledge from foundational models like SAM with multi-stage, coarse-to-fine refinement pipelines. Both the challenge dataset and the participants' submitted code have been made publicly available on GitHub (https://github.com/ricoleehduu/STS-Challenge-2024), ensuring transparency and reproducibility.

G. Oberoi, S. Nitsch, M. Edelmayer et al.

This narrative review presents an overview on the currently available 3D printing technologies and their utilization in experimental, clinical and educational facets, from the perspective of different specialties of dentistry, including oral and maxillofacial surgery, orthodontics, endodontics, prosthodontics, and periodontics. It covers research and innovation, treatment modalities, education and training, employing the rapidly developing 3D printing process. Research-oriented advancement in 3D printing in dentistry is witnessed by the rising number of publications on this topic. Visualization of treatment outcomes makes it a promising clinical tool. Educational programs utilizing 3D-printed models stimulate training of dental skills in students and trainees. 3D printing has enormous potential to ameliorate oral health care in research, clinical treatment, and education in dentistry.

D. Tandon, J. Rajawat, M. Banerjee

The last decennary has marked as the breakthrough in the advancement of technology with evolution of artificial intelligence, which is rapidly gaining the attention of researchers across the globe. Every field opted artificial intelligence with huge enthusiasm and so the field of dental science is no exception. With huge increases in patient documented information and data this is the need of the hour to use intelligent software to compile and save this data. From the basic step of taking a patient's history to data processing and then to extract the information from the data for diagnosis, artificial intelligence has many applications in dental and medical science. While in no case artificial intelligence can replace the role of a dental surgeon but it is important to be acquainted with the scope to amalgamate this advancement of technology in future for betterment of dental practice.

Mikel Armentia, Mikel Abasolo, Ibai Coria et al.

Statement of problem. Dental implant geometry affects the mechanical performance and fatigue behavior of butt-joint implant-supported restorations. However, failure of the implant component has been generally studied by ignoring the prosthetic screw, which is frequently the critical restoration component Purpose. Evaluate the effect of 3 main implant geometric parameters: the implant body diameter, the platform diameter, and the implant-abutment connection type (external versus internal butt-joint) on the fatigue life of the prosthetic screw. The experimental values were further compared with the theoretical ones obtained by using a previously published methodology M&M. 4 different designs of direct-to-implant dental restorations from the manufacturer BTI were tested. Forty-eight fatigue tests were performed in an axial fatigue testing machine according to ISO 14801. Linear regression models, 95% interval confidence bands for the linear regression, and 95% prediction intervals of the fatigue load-life results were obtained and compared through an analysis of covariance to determine the influence of the 3 parameters under study on the fatigue behavior Results. Linear regression models showed a statistical difference when the implant body diameter was increased by 1 mm; an average 3.5-fold increase in fatigue life was observed. Increasing the implant abutment connection diameter by 1.4 mm also showed a significant difference, leading to 7-fold longer fatigue life on average. No significant statistical evidence was found to demonstrate a difference in fatigue life between internal and external connections Conclusions. Increasing the implant platform and body diameter significantly improved the fatigue life of the screw, whereas external and internal connections provided similar results. In addition, experimental results proved the accuracy of the fatigue life prediction methodology

Hanieh Ahmadi, A. Ebrahimi, F. Ahmadi

Dental caries, pulpal necrosis, trauma, and periodontal diseases can result in dental infections which could have severe consequences that affect both soft and hard tissues of the oral cavity. Dental infections commonly present with symptoms of pain, fever, and swelling. Surgical and endodontic treatments are the early management of infected teeth, followed by antibiotic therapy. Some alternative methods also exist for treating infection such as low-level laser therapy and photodynamic therapy. Antibiotics are generally used in dental procedures to treat odontogenic infections, nonodontogenic infections, local infection, focal infection, and prophylaxis. Antibiotic prophylaxis is prescribed for patients with immunosuppressed conditions, infective endocarditis, metabolic disorders, and patients with prosthetic joints. To reduce the complications of unnecessary antibiotic prescriptions especially bacterial resistance, comprehensive guidelines should be established. It has been noted that only about 12% of dentists adequately and correctly prescribe antibiotics, which shows the importance of comprehensive guidelines. Antibiotics prescription may result in some adverse effects such as hypersensitivity reactions and dermatological and allergic disorders. Furthermore, unnecessary prescription of antibiotics could result in several serious sequelae, for example, bacterial resistance, gastric and hematological problems, and diversion of bacterial microbiota. The present review attempts to summarize the indications of antibiotic therapy in dentistry and discuss the common types of antibiotics that are routinely used in dental practice based on pharmacologic classes. Moreover, types of antibiotics that are considered safe during pregnancy and childhood are also reviewed.

M. Revilla‐León, Miguel Gómez-Polo, S. Vyas et al.

STATEMENT OF PROBLEM Artificial intelligence (AI) applications are increasing in restorative procedures. However, the current development and performance of AI in restorative dentistry applications has not yet been systematically documented and analyzed. PURPOSE The purpose of this systematic review was to identify and evaluate the ability of AI models in restorative dentistry to diagnose dental caries and vertical tooth fracture, detect tooth preparation margins, and predict restoration failure. MATERIAL AND METHODS An electronic systematic review was performed in 5 databases: MEDLINE/PubMed, EMBASE, World of Science, Cochrane, and Scopus. A manual search was also conducted. Studies with AI models were selected based on 4 criteria: diagnosis of dental caries, diagnosis of vertical tooth fracture, detection of the tooth preparation finishing line, and prediction of restoration failure. Two investigators independently evaluated the quality assessment of the studies by applying the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Quasi-Experimental Studies (nonrandomized experimental studies). A third investigator was consulted to resolve lack of consensus. RESULTS A total of 34 articles were included in the review: 29 studies included AI techniques for the diagnosis of dental caries or the elaboration of caries and postsensitivity prediction models, 2 for the diagnosis of vertical tooth fracture, 1 for the tooth preparation finishing line location, and 2 for the prediction of the restoration failure. Among the studies reviewed, the AI models tested obtained a caries diagnosis accuracy ranging from 76% to 88.3%, sensitivity ranging from 73% to 90%, and specificity ranging from 61.5% to 93%. The caries prediction accuracy among the studies ranged from 83.6% to 97.1%. The studies reported an accuracy for the vertical tooth fracture diagnosis ranging from 88.3% to 95.7%. The article using AI models to locate the finishing line reported an accuracy ranging from 90.6% to 97.4%. CONCLUSIONS AI models have the potential to provide a powerful tool for assisting in the diagnosis of caries and vertical tooth fracture, detecting the tooth preparation margin, and predicting restoration failure. However, the dental applications of AI models are still in development. Further studies are required to assess the clinical performance of AI models in restorative dentistry.

R. Bapat, Chaitanya Joshi, P. Bapat et al.

Maintenance of oral health is a major challenge in dentistry. Different materials have been used to treat various dental diseases, although treatment success is limited by features of the biomaterials used. To overcome these limitations, materials incorporated with nanoparticles (NPs) can be used in dental applications including endodontics, periodontics, tissue engineering, oral surgery, and imaging. The unique properties of NPs, including their surface:volume ratio, antibacterial action, physical, mechanical, and biological characteristics, and unique particle size have rendered them effective vehicles for dental applications. In this review, we provide insights into the various applications of NPs in dentistry, including their benefits, limitations, properties, actions and future potential.

Simone Marques, Paulo Ribeiro, C. Falcão et al.

Introduction. Digital impressions in implant dentistry rely on many variables, and their accuracy, particularly in complete edentulous patients, is not well understood. Aim. The purpose of this literature review was to determine which factors may influence the accuracy of digital impressions in implant dentistry. Emphasized attention was given to the design of the intra-oral scan body (ISB) and scanning techniques. Materials and methods. A Medline, PubMed and EBSCO Host databases search, complemented by a hand search, was performed in order to select relevant reports regarding the appliance of digital impressions in implant dentistry. The search subject included but was not limited to accuracy of digital impressions in implant dentistry, digital scanning techniques, the design and material of the ISBs, and the depth and angulation of the implant. The related titles and abstracts were screened, and the remaining articles that fulfilled the inclusion criteria were selected for full-text readings. Results. The literature search conducted for this review initially resulted in 108 articles, among which only 21 articles fulfilled the criteria for inclusion. Studies were evaluated according to five subjects: accuracy of digital impressions in implant dentistry; the design and material of the intra-oral scan bodies; scanning technique; the influence of implants depth/angulations on the digital impression and accuracy of different intra-oral scanner devices. Conclusions. The accuracy of digital impressions in implant dentistry depends on several aspects. The depth/angulation of the implant, the experience of the operator, the intra-oral scanner used, and environmental conditions may influence the accuracy of digital impressions in implant dentistry. However, it seems that ISBs’ design and material, as well as scanning technique, have a major impact on the trueness and precision of digital impressions in implant dentistry. Future research is suggested for the better understanding of this subject, focusing on the optimization of the ISB design and scanning protocols.

Shweta Kajjari, R. Joshi, S. Hugar et al.

Abstract Essential oils have been known to have many medicinal properties. They have been utilized by medical practitioners since the medieval ages. Lavender essential oil is known to be rich in medicinal properties like antimicrobial activity, anxiolytic, anti-inflammatory, antinociceptive, and antioxidant properties. Utilization of herbal products like lavender essential oils will benefit the patients in many ways. Incorporation of these properties in the field of dentistry has ample advantages. The purpose of this review article is to enlist the current and prospective uses of lavender essential oils in the field of dentistry and to identify the lacunae using which research regarding this topic can be taken one step closer to clinical practice. How to cite this article Kajjari S, Joshi RS, Hugar SM, et al. The Effects of Lavender Essential Oil and its Clinical Implications in Dentistry: A Review. Int J Clin Pediatr Dent 2022;15(3):385-388.

Lena Katharina Müller-Heupt, Anja Eckelt, John Eckelt et al.

Periodontitis is a common global disease caused by bacterial dysbiosis leading to tissue destruction, and it is strongly associated with anaerobic bacterial colonization. Therapeutic strategies such as oxygen therapy have been developed to positively influence the dysbiotic microbiota, and the use of oxygen-releasing substances may offer an added benefit of avoiding systemic effects commonly associated with antibiotics taken orally or hyperbaric oxygen therapy. Therefore, the oxygen release of calcium peroxide (CaO₂) was measured using a dissolved oxygen meter, and CaO₂ solutions were prepared by dissolving autoclaved CaO₂ in sterile filtered and deionized water. The effects of CaO₂ on planktonic bacterial growth and metabolic activity, as well as on biofilms of <i>Streptococcus oralis</i> and <i>Porphyromonas gingivalis</i>, were investigated through experiments conducted under anaerobic conditions. The objective of this study was to investigate the potential of CaO₂ as an antimicrobial agent for the treatment of periodontitis. Results showed that CaO₂ selectively inhibited the growth and viability of <i>P. gingivalis</i> (<i>p</i> < 0.001) but had little effect on <i>S. oralis</i> (<i>p</i> < 0.01), indicating that CaO₂ has the potential to selectively affect both planktonic bacteria and mono-species biofilms of <i>P. gingivalis</i>. The results of this study suggest that CaO₂ could be a promising antimicrobial agent with selective activity for the treatment of periodontitis.