Explore the vast range of titles available.

Background Virtual reality is the science of creating a virtual environment for the assessment of various anatomical regions of the body for the diagnosis, planning and surgical training. Augmented reality is the superimposition of a 3D real environment specific to individual patient onto the surgical filed using semi-transparent glasses to augment the virtual scene.. The aim of this study is to provide an over view of the literature on the application of virtual and augmented reality in oral & maxillofacial surgery. Methods We reviewed the literature and the existing database using Ovid MEDLINE search, Cochran Library and PubMed. All the studies in the English literature in the last 10 years, from 2009 to 2019 were included. Results We identified 101 articles related the broad application of virtual reality in oral & maxillofacial surgery. These included the following: Eight systematic reviews, 4 expert reviews, 9 case reports, 5 retrospective surveys, 2 historical perspectives, 13 manuscripts on virtual education and training, 5 on haptic technology, 4 on augmented reality, 10 on image fusion, 41 articles on the prediction planning for orthognathic surgery and maxillofacial reconstruction. Dental implantology and orthognathic surgery are the most frequent applications of virtual reality and augmented reality. Virtual planning improved the accuracy of inserting dental implants using either a statistic guidance or dynamic navigation. In orthognathic surgery, prediction planning and intraoperative navigation are the main applications of virtual reality. Virtual reality has been utilised to improve the delivery of education and the quality of training in oral & maxillofacial surgery by creating a virtual environment of the surgical procedure. Haptic feedback provided an additional immersive reality to improve manual dexterity and improve clinical training. Conclusion Virtual and augmented reality have contributed to the planning of maxillofacial procedures and surgery training. Few articles highlighted the importance of this technology in improving the quality of patients’ care. There are limited prospective randomized studies comparing the impact of virtual reality with the standard methods in delivering oral surgery education.

Background This retrospective clinical study aims to present results of experience with a novel guided surgery system with a sleeveless, open-frame structure, in which the surgical handpiece (not the drills used for preparation) is guided. Methods This study was based on an evaluation of the records of partially edentulous patients who had been treated with a sleeveless open-frame guided surgery system (TWIN-Guide®, 2Ingis, Brussels, Belgium), between January 2015 and December 2017. Inclusion criteria were patients with good systemic/oral health and a minimum follow-up of 1 year. Exclusion criteria were patients who had been treated without a guide, or with a guide with sleeves, patients with systemic/oral diseases and who did not have a follow-up of 1 year. The main outcomes were surgical (fit and stability of the surgical guide, duration of the intervention, implant stability, and any intra-operative or immediate post-operative complication), biologic, and prosthetic. Results Thirty-eight patients (24 males, 14 females; mean age 56.5 ± 14.0 years) were included in the study. These patients had been treated with 110 implants inserted by means of 40 sleeveless, open-frame guides. With regard to fit and stability, 34 guides were excellent, 4 acceptable, and 2 inadequate for use. The mean duration of the intervention was 23.7 (± 6.7) minutes. Immediately after placement, 2 fixtures were not stable and had to be removed. Two patients experienced pain/swelling after surgery. The 108 surviving implants were restored with 36 single crowns and 32 fixed partial prostheses (24 two-unit and 8 three-unit bridges); these restorations survived until the 1-year follow-up, with a low incidence of biologic and prosthetic complications. Conclusions Within the limits of this study, this novel guided surgery system with sleeveless, open frame–structure guides seems to be clinically reliable; further studies on a larger sample of patients are needed to confirm these outcomes.

When taking the final impression for a three-unit fixed partial denture (FPD), the intaglio surface of the pontic of provisional restoration cannot be transferred accurately to that of definitive restoration. The intra- and extra-oral scanning (IEOS) technique, a method for accurately reproducing the submucosal morphology of the superstructure of an implant, has been reported using an intraoral scanner. In the present study, we evaluated the difference between the conventional impression method using impression material and the IEOS technique in reproducing the morphology of the surface of the pontic of a definitive FPD. There was a significant difference in the trueness of the intaglio surface morphology of the pontic between the conventional method and the IEOS technique; however, no significant difference in precision was observed. As a result, the intaglio surface of the pontic of the three-unit FPD could be transferred to definitive restorations more accurately with the IEOS technique than with the conventional method. These results suggest that the IEOS technique can duplicate the intaglio surface of the pontic more reproducibly to the definitive restorations compared with the conventional method.

Based on the hypothesis that the fabrication of dental models using fused deposition modeling and poly-lactic acid (PLA), followed by recycling and reusing, would reduce industrial waste, we aimed to compare the accuracies of virgin and recycled PLA models. The PLA models were recycled using a crusher and a filament-manufacturing machine. Virgin PLA was labeled R, and the first, second, and third recycles were labeled R1, R2, and R3, respectively. To determine the accuracies of the virgin and reused PLA models, identical provisional crowns were fitted, and marginal fits were obtained using micro-computed tomography. A marginal fit of 120 µm was deemed acceptable based on previous literature. The mesial, distal, buccal, and palatal centers were set at M, D, B, and P, respectively. The mean value of each measurement point was considered as the result. When comparing the accuracies of R and R1, R2, and R3, significant differences were noted between R and R3 at B, R and R2, R3 at P, and R and R3 at D (p < 0.05). No significant difference was observed at M. This study demonstrates that PLA can be recycled only once owing to accuracy limitations.

Purpose of Review 3D printing, or additive manufacturing, is an emerging technology in the dental field. As it continues to advance beyond diagnostic purposes, it shifts towards the fabrication of permanent prostheses utilizing existing and novel biomaterials. A review and comparison of the current research on materials, techniques, and applications of 3D printing available for restorative use was conducted. Recent Findings Currently, 3D printing used across the field of restorative dentistry, includes laboratory models and casting patterns, interim full and partial coverage restorations, surgical guides, occlusal splints, maxillofacial prosthetics, removable prostheses, and implants. Resins are most often used while ceramic and hybrid materials are currently under investigation and development. Summary While the current research available highlights 3D printing’s potential in the dental field, more research is needed on the existing and developing materials and printers, thus allowing for an exponential increase of this technology’s applications in restorative dentistry.

Background Intraoral scanners (IOS) are devices for capturing direct optical impressions in dentistry. The purpose of this narrative review on the use of IOS was to: (1) identify the advantages/disadvantages of using optical impressions compared to conventional impressions; (2) investigate if optical impressions are as accurate as conventional impressions; (3) evaluate the differences between the IOS currently available commercially; (4) determine the current clinical applications/limitations in the use of IOS. Methods Electronic database searches were performed using specific keywords and MeSH terms. The searches were confined to full-text articles written in English and published in peer-reviewed journals between January 2007 and June 2017. Results One hundred thirty-two studies were included in the present review; among them, 20 were previous literature reviews, 78 were in vivo clinical studies (6 randomized controlled/crossover trials, 31 controlled/comparative studies; 24 cohort studies/case series; 17 case reports) and 34 were in vitro comparative studies. Conclusions Optical impressions reduce patient discomfort; IOS are time-efficient and simplify clinical procedures for the dentist, eliminating plaster models and allowing better communication with the dental technician and with patients; however, with IOS, it can be difficult to detect deep margin lines in prepared teeth and/or in case of bleeding, there is a learning curve, and there are purchasing and managing costs. The current IOS are sufficiently accurate for capturing impressions for fabricating a whole series of prosthetic restorations (inlays/onlays, copings and frameworks, single crowns and fixed partial dentures) on both natural teeth and implants; in addition, they can be used for smile design, and to fabricate posts and cores, removable partial prostheses and obturators. The literature to date does not support the use of IOS in long-span restorations with natural teeth or implants. Finally, IOS can be integrated in implant dentistry for guided surgery and in orthodontics for fabricating aligners and custom-made devices.

Background Dental plaque causes many common oral diseases (e.g., caries, gingivitis, and periodontitis). Therefore, plaque detection and control are extremely important for children’s oral health. The objectives of this study were to design a deep learning-based artificial intelligence (AI) model to detect plaque on primary teeth and to evaluate the diagnostic accuracy of the model. Methods A conventional neural network (CNN) framework was adopted, and 886 intraoral photos of primary teeth were used for training. To validate clinical feasibility, 98 intraoral photos of primary teeth were assessed by the AI model. Additionally, tooth photos were acquired using a digital camera. One experienced pediatric dentist examined the photos and marked the regions containing plaque. Then, a plaque-disclosing agent was applied, and the areas with plaque were identified. After 1 week, the dentist drew the plaque area on the 98 photos taken by the digital camera again to evaluate the consistency of manual diagnosis. Additionally, 102 intraoral photos of primary teeth were marked to denote the plaque areas obtained by the AI model and the dentist to evaluate the diagnostic capacity of each approach based on lower-resolution photos. The mean intersection-over-union (MIoU) metric was employed to indicate detection accuracy. Results The MIoU for detecting plaque on the tested tooth photos was 0.726 ± 0.165. The dentist’s MIoU was 0.695 ± 0.269 when first diagnosing the 98 photos taken by the digital camera and 0.689 ± 0.253 after 1 week. Compared to the dentist, the AI model demonstrated a higher MIoU (0.736 ± 0.174), and the results did not change after 1 week. When the dentist and the AI model assessed the 102 intraoral photos, the MIoU was 0.652 ± 0.195 for the dentist and 0.724 ± 0.159 for the model. The results of a paired t-test found no significant difference between the AI model and human specialist ( P  > .05) in diagnosing dental plaque on primary teeth. Conclusions The AI model showed clinically acceptable performance in detecting dental plaque on primary teeth compared with an experienced pediatric dentist. This finding illustrates the potential of such AI technology to help improve pediatric oral health.

Background The introduction of the new generation of particle-filled and high strength ceramics, hybrid composites and technopolymers in the last decade has offered an extensive palette of dental materials broadening the clinical indications in fixed prosthodontics, in the light of minimally invasive dentistry dictates. Moreover, last years have seen a dramatic increase in the patients’ demand for non-metallic materials, sometimes induced by metal-phobia or alleged allergies. Therefore, the attention of scientific research has been progressively focusing on such materials, particularly on lithium disilicate and zirconia, in order to shed light on properties, indications and limitations of the new protagonists of the prosthetic scene. Methods This article is aimed at providing a narrative review regarding the state-of-the-art in the field of these popular ceramic materials, as to their physical-chemical, mechanical and optical properties, as well as to the proper dental applications, by means of scientific literature analysis and with reference to the authors’ clinical experience. Results A huge amount of data, sometimes conflicting, is available today. Both in vitro and in vivo studies pointed out the outstanding peculiarities of lithium disilicate and zirconia: unparalleled optical and esthetic properties, together with high biocompatibility, high mechanical resistance, reduced thickness and favorable wear behavior have been increasingly orientating the clinicians’ choice toward such ceramics. Conclusions The noticeable properties and versatility make lithium disilicate and zirconia materials of choice for modern prosthetic dentistry, requiring high esthetic and mechanical performances combined with a minimal invasive approach, so that the utilization of such metal-free ceramics has become more and more widespread over time.

Artificial Intelligence (AI) technologies play a significant role and significantly impact various sectors, including healthcare, engineering, sciences, and smart cities. AI has the potential to improve the quality of patient care and treatment outcomes while minimizing the risk of human error. Artificial Intelligence (AI) is transforming the dental industry, just like it is revolutionizing other sectors. It is used in dentistry to diagnose dental diseases and provide treatment recommendations. Dental professionals are increasingly relying on AI technology to assist in diagnosis, clinical decision-making, treatment planning, and prognosis prediction across ten dental specialties. One of the most significant advantages of AI in dentistry is its ability to analyze vast amounts of data quickly and accurately, providing dental professionals with valuable insights to enhance their decision-making processes. The purpose of this paper is to identify the advancement of artificial intelligence algorithms that have been frequently used in dentistry and assess how well they perform in terms of diagnosis, clinical decision-making, treatment, and prognosis prediction in ten dental specialties; dental public health, endodontics, oral and maxillofacial surgery, oral medicine and pathology, oral & maxillofacial radiology, orthodontics and dentofacial orthopedics, pediatric dentistry, periodontics, prosthodontics, and digital dentistry in general. We will also show the pros and cons of using AI in all dental specialties in different ways. Finally, we will present the limitations of using AI in dentistry, which made it incapable of replacing dental personnel, and dentists, who should consider AI a complimentary benefit and not a threat.

Background The continuous development in dental processing ensures new opportunities in the field of fixed prosthodontics in a complete virtual environment without any physical model situations. The aim was to compare fully digitalized workflows to conventional and/or mixed analog-digital workflows for the treatment with tooth-borne or implant-supported fixed reconstructions. Methods A PICO strategy was executed using an electronic (MEDLINE, EMBASE, Google Scholar) plus manual search up to 2016–09-16 focusing on RCTs investigating complete digital workflows in fixed prosthodontics with regard to economics or esthetics or patient-centered outcomes with or without follow-up or survival/success rate analysis as well as complication assessment of at least 1 year under function. The search strategy was assembled from MeSH-Terms and unspecific free-text words: {((“Dental Prosthesis” [MeSH]) OR (“Crowns” [MeSH]) OR (“Dental Prosthesis, Implant-Supported” [MeSH])) OR ((crown) OR (fixed dental prosthesis) OR (fixed reconstruction) OR (dental bridge) OR (implant crown) OR (implant prosthesis) OR (implant restoration) OR (implant reconstruction))} AND {(“Computer-Aided Design” [MeSH]) OR ((digital workflow) OR (digital technology) OR (computerized dentistry) OR (intraoral scan) OR (digital impression) OR (scanbody) OR (virtual design) OR (digital design) OR (cad/cam) OR (rapid prototyping) OR (monolithic) OR (full-contour))} AND {(“Dental Technology” [MeSH) OR ((conventional workflow) OR (lost-wax-technique) OR (porcelain-fused-to-metal) OR (PFM) OR (implant impression) OR (hand-layering) OR (veneering) OR (framework))} AND {((“Study, Feasibility” [MeSH]) OR (“Survival” [MeSH]) OR (“Success” [MeSH]) OR (“Economics” [MeSH]) OR (“Costs, Cost Analysis” [MeSH]) OR (“Esthetics, Dental” [MeSH]) OR (“Patient Satisfaction” [MeSH])) OR ((feasibility) OR (efficiency) OR (patient-centered outcome))}. Assessment of risk of bias in selected studies was done at a ‘trial level’ including random sequence generation, allocation concealment, blinding, completeness of outcome data, selective reporting, and other bias using the Cochrane Collaboration tool. A judgment of risk of bias was assigned if one or more key domains had a high or unclear risk of bias. An official registration of the systematic review was not performed. Results The systematic search identified 67 titles, 32 abstracts thereof were screened, and subsequently, three full-texts included for data extraction. Analysed RCTs were heterogeneous without follow-up. One study demonstrated that fully digitally produced dental crowns revealed the feasibility of the process itself; however, the marginal precision was lower for lithium disilicate (LS2) restorations (113.8 μm) compared to conventional metal-ceramic (92.4 μm) and zirconium dioxide (ZrO2) crowns (68.5 μm) ( p  < 0.05). Another study showed that leucite-reinforced glass ceramic crowns were esthetically favoured by the patients (8/2 crowns) and clinicians (7/3 crowns) ( p  < 0.05). The third study investigated implant crowns. The complete digital workflow was more than twofold faster (75.3 min) in comparison to the mixed analog-digital workflow (156.6 min) (p < 0.05). No RCTs could be found investigating multi-unit fixed dental prostheses (FDP). Conclusions The number of RCTs testing complete digital workflows in fixed prosthodontics is low. Scientifically proven recommendations for clinical routine cannot be given at this time. Research with high-quality trials seems to be slower than the industrial progress of available digital applications. Future research with well-designed RCTs including follow-up observation is compellingly necessary in the field of complete digital processing.