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      3D-printed Surgical Training Model Based on Real Patient Situations for Dental Education

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          Abstract

          Background: Most simulation models used at university dental clinics are typodonts. Usually, models show idealized eugnathic situations, which are rarely encountered in everyday practice. The aim of this study was to use 3D printing technology to manufacture individualized surgical training models for root tip resection (apicoectomy) on the basis of real patient data and to compare their suitability for dental education against a commercial typodont model. Methods: The training model was designed using CAD/CAM (computer-aided design/computer-aided manufacturing) technology. The printer used to manufacture the models employed the PolyJet technique. Dental students, about one year before their final examinations, acted as test persons and evaluated the simulation models on a visual analogue scale (VAS) with four questions (Q1–Q4). Results: A training model for root tip resection was constructed and printed employing two different materials (hard and soft) to differentiate anatomical structures within the model. The exercise was rated by 35 participants for the typodont model and 33 students for the 3D-printed model. Wilcoxon rank sum tests were carried out to identify differences in the assessments of the two model types. The alternative hypothesis for each test was: “The rating for the typodont model is higher than that for the 3D-printed model”. As the p-values reveal, the alternative hypothesis has to be rejected in all cases. For both models, the gingiva mask was criticized. Conclusions: Individual 3D-printed surgical training models based on real patient data offer a realistic alternative to industrially manufactured typodont models. However, there is still room for improvement with respect to the gingiva mask for learning surgical incision and flap formation.

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          Most cited references19

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          Polymers for 3D Printing and Customized Additive Manufacturing

          Additive manufacturing (AM) alias 3D printing translates computer-aided design (CAD) virtual 3D models into physical objects. By digital slicing of CAD, 3D scan, or tomography data, AM builds objects layer by layer without the need for molds or machining. AM enables decentralized fabrication of customized objects on demand by exploiting digital information storage and retrieval via the Internet. The ongoing transition from rapid prototyping to rapid manufacturing prompts new challenges for mechanical engineers and materials scientists alike. Because polymers are by far the most utilized class of materials for AM, this Review focuses on polymer processing and the development of polymers and advanced polymer systems specifically for AM. AM techniques covered include vat photopolymerization (stereolithography), powder bed fusion (SLS), material and binder jetting (inkjet and aerosol 3D printing), sheet lamination (LOM), extrusion (FDM, 3D dispensing, 3D fiber deposition, and 3D plotting), and 3D bioprinting. The range of polymers used in AM encompasses thermoplastics, thermosets, elastomers, hydrogels, functional polymers, polymer blends, composites, and biological systems. Aspects of polymer design, additives, and processing parameters as they relate to enhancing build speed and improving accuracy, functionality, surface finish, stability, mechanical properties, and porosity are addressed. Selected applications demonstrate how polymer-based AM is being exploited in lightweight engineering, architecture, food processing, optics, energy technology, dentistry, drug delivery, and personalized medicine. Unparalleled by metals and ceramics, polymer-based AM plays a key role in the emerging AM of advanced multifunctional and multimaterial systems including living biological systems as well as life-like synthetic systems.
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            The complete digital workflow in fixed prosthodontics: a systematic review

            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. Electronic supplementary material The online version of this article (10.1186/s12903-017-0415-0) contains supplementary material, which is available to authorized users.
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              Current status and applications of additive manufacturing in dentistry: A literature-based review

              Objective To study the current status and applications of additive manufacturing (AM) in dentistry along with various technologies, benefits and future scope. Methods A significant number of relevant research papers on the additive manufacturing application in dentistry are identified through Scopus and studied using bibliometric analysis that shows an increasing trend of research in this field. This paper briefly describes various types of AM technologies with their accuracy, pros and cons along with different dental materials. Paper also discusses various benefits of AM in dentistry and steps used to create 3D printed dental model using this technology. Further, ten major AM applications in dentistry are identified along with primary references and objectives. Results Additive manufacturing is an innovative technique moving towards the customised production of dental implants and other dental tools using computer-aided design (CAD) data. This technology is used to manufacture elaborate dental crowns, bridges, orthodontic braces and can also various other models, devices and instruments with lesser time and cost. With the help of this disruptive innovation, dental implants are fabricated accurately as per patient data captured by the dental 3D scanner. The application of this technology is also being explored for the precise manufacturing of removal prosthetics, aligners, surgical templates for implants and produce models that for the planning of treatment and preoperative positioning of the jaws.
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                Author and article information

                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                22 April 2020
                April 2020
                : 17
                : 8
                : 2901
                Affiliations
                [1 ]Department of Cranio-Maxillofacial Surgery, University Hospital Münster, Albert-Schweitzer-Campus 1, Building W 30, D-48149 Münster, Germany; maximilian.timme@ 123456ukmuenster.de (M.T.); johannes.kleinheinz@ 123456ukmuenster.de (J.K.)
                [2 ]Department of Cranio-Maxillofacial Surgery, Klinikum Osnabrück, Am Finkenhügel 1, 49076 Osnabrück, Germany; kroeger.elke@ 123456gmx.de
                [3 ]Department of Prosthetic Dentistry and Biomaterials, University Hospital Münster, Albert-Schweitzer Campus 1, D-48149 Münster, Germany; markus.dekiff@ 123456uni-muenster.de (M.D.); dirksdi@ 123456uni-muenster.de (D.D.)
                Author notes
                [* ]Correspondence: marcel.hanisch@ 123456ukmuenster.de ; Tel.: +49-(0)-2-51/83-4-70-02; Fax: +49-(0)-2-51/83-4-71-84
                [†]

                The two authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-7717-3378
                Article
                ijerph-17-02901
                10.3390/ijerph17082901
                7215302
                32331445
                ff13d28a-406a-4fe7-8dc2-015061d3c9b4
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 17 March 2020
                : 21 April 2020
                Categories
                Article

                Public health
                3d printing,surgical training model,3d rapid prototyping,root resection,cad/cam,dental education

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