Innovative Trends in Implant Dentistry Training and Education: A Narrative Review

Three-dimensional replica of the temporal bone in the teaching of human anatomy

PURPOSE

The current study proposes the comparison of the visualization and identification of anatomical details between natural human temporal bone, its respective copy from three-dimensional printing, and the virtual model obtained from CBCT.

METHODS

The sample consisted of undergraduate students in Dentistry (Group UE, n = 22), Postgraduate students in Radiology and Imaging (Group P-RI, n = 20), and Postgraduate students in Forensic Odontology (Group P-FO, n = 24). All participants attended a theoretical class on specialized anatomy of the temporal bone and subsequently performed the markings of 10 determined structures.

RESULTS

The number of correct identifications was similar in natural bone and printed three-dimensional models in all groups (p > 0.05). The virtual model showed a significantly lower number of correct structures (p < 0.05) in the 3 groups. In general, there were significantly higher percentages of accurate answers among postgraduate students compared to undergraduate students. Most graduate students believed that the printed three-dimensional model could be used to teach anatomy in place of natural bone, while undergraduate students disagreed or were unsure (p < 0.05). Regarding the virtual tomographic image, in all groups, students disagreed or were not sure that its use would be beneficial in replacing natural bone.

CONCLUSION

Three-dimensional and virtual models can be used as auxiliary tools in teaching anatomy, complementing practical learning with natural bones.

Effectiveness of a flipped classroom for undergraduate in implant dentistry hands-on course

PURPOSE

The purpose of this study was to compare the learning in the implant dentistry hands-on course to that of the flipped classroom (FC) and the traditional lecture cohorts (control).

MATERIALS AND METHODS

In this study,80 students were enrolled for the first time in an implant dentistry program. Subsequently, they were divided into two groups. The first, the FC group, which had free access to a video with a PowerPoint presentation on the Chaoxing-WHU-MOOC platform about the implant placement on first molar sites before class. The second, the control group, which attended a didactic lecture describing implant practice on the first molar site via a bidirectional multimedia interactive teaching demonstration and then operated on a simulation model. Cone beam computed tomography (CBCT) and the deviation gauge were utilized to analyze the accuracy of the implant placement in the students' models. An online satisfaction questionnaire was distributed to both groups one week after the class.

RESULTS

The linear deviation of the CBCT examination did not show any statistical difference between the two groups concerning cervical, apex, and angular. A significant buccal deviation was observed in the control group compared with the FC group (mean: 0.7436 mm vs. 0.2875 mm, p = 0.0035), according to the restoration-level deviation gauge. A total of 74.36% of students in the FC group placed implant within 0.5 mm buccal-to-lingual deviations, but only 41.03% of students in the control group reached within 0.5 mm buccal-to-lingual deviation ranges. Additionally, 91.67% of the students in the FC group and 97.5% of the students in the control group were satisfied with the practical implant class.

CONCLUSION

FC was more effective than a didactic lecture for implant dentistry practical skill acquisition.

WhatsApp as a Tool in Blended Learning in Dental Education

Background and Objective

Dental education is unique, with clinical/practical learning much different from other professionals. In dentistry, students are exposed much earlier in their curriculum to patients, performing procedures under direct/indirect supervision. Hence, the present review attempted to assess the standing position of dentistry in blended learning worldwide.

Materials and Methods

E-learning modality was at its primitive stage as food for thought among educational task force committees, with only a handful of developed and developing countries equipped with it. During this pandemic, "WhatsApp" became a savior, as it was a widely used educational device among dental teachers and students. Furthermore, it was easily applicable in places where there was difficulty in obtaining regular internet bandwidth, especially in remote/rural areas. It is noteworthy that blended learning/e-learning, when complemented with the conventional teaching method, upskill critical thinking and problem-solving capabilities. Blended learning or virtual reality education should be made feasible without disparity, worldwide. Mind training, both students and staff in hybrid e-learning, is the need of the hour not only to keep pace with digitalized dentistry but to prepare the students to face real-world situations.

Conclusion

The sustainability of dental education should be rethought by dental schools with "Complimented Digital learning" wherever feasible, not only to cope with current trends but also to face unforeseen future challenges.

Developing an Artificial Intelligence Solution to Autosegment the Edentulous Mandibular Bone for Implant Planning

OBJECTIVE

 Dental implants are considered the optimum solution to replace missing teeth and restore the mouth's function and aesthetics. Surgical planning of the implant position is critical to avoid damage to vital anatomical structures; however, the manual measurement of the edentulous (toothless) bone on cone beam computed tomography (CBCT) images is time-consuming and is subject to human error. An automated process has the potential to reduce human errors and save time and costs. This study developed an artificial intelligence (AI) solution to identify and delineate edentulous alveolar bone on CBCT images before implant placement.

MATERIALS AND METHODS

 After obtaining the ethical approval, CBCT images were extracted from the database of the University Dental Hospital Sharjah based on predefined selection criteria. Manual segmentation of the edentulous span was done by three operators using ITK-SNAP software. A supervised machine learning approach was undertaken to develop a segmentation model on a "U-Net" convolutional neural network (CNN) in the Medical Open Network for Artificial Intelligence (MONAI) framework. Out of the 43 labeled cases, 33 were utilized to train the model, and 10 were used for testing the model's performance.

STATISTICAL ANALYSIS

 The degree of 3D spatial overlap between the segmentation made by human investigators and the model's segmentation was measured by the dice similarity coefficient (DSC).

RESULTS

 The sample consisted mainly of lower molars and premolars. DSC yielded an average value of 0.89 for training and 0.78 for testing. Unilateral edentulous areas, comprising 75% of the sample, resulted in a better DSC (0.91) than bilateral cases (0.73).

CONCLUSION

 Segmentation of the edentulous spans on CBCT images was successfully conducted by machine learning with good accuracy compared to manual segmentation. Unlike traditional AI object detection models that identify objects present in the image, this model identifies missing objects. Finally, challenges in data collection and labeling are discussed, together with an outlook at the prospective stages of a larger project for a complete AI solution for automated implant planning.

Disruptive Technologies for Learning and Further Investigation of the Potential Toxicity Produced by Titanium in the Human Body during the COVID-19 Pandemic Period

Titanium is considered to be a biocompatible material and is used to a great extent in the pharmaceutical and oral implantology fields. While initially, specialists considered that its use does not cause adverse effects on the human body, as time has gone by, it has become clear that its use can lead to the development of certain diseases. The objective of this study was to identify the way in which digital technologies have the capacity to facilitate information regarding the potential long-term harm caused by titanium device toxicity during the COVID-19 pandemic. In this study, a regression model was developed to identify how a series of independent variables have the ability to influence the dependent variable (respondents' perceptions of how new web technologies have the ability to help future physicians to facilitate information absorption with regard to potential titanium toxicity). The results illustrated that new technologies have the potential to support both the learning process on this topic and the innovation activity by discovering new solutions that will gradually lead to the reduction of the side effects of titanium used in the pharmaceutical and oral implantology fields.

Influence of different education approaches on the implantation performance of dental practitioners in aesthetic zone

PURPOSE

To investigate the influence of different education approaches on the implantation performance (operation time, three-dimensional deviation) of inexperienced operators.

METHODS

Eighteen students who met the inclusion criteria were randomly assigned to traditional training group or digital training group. After training, the average operation time and implant deviation (platform deviation, apex deviation, and angle deviation) of the two groups were calculated by Student's t-test. A self-developed questionnaire was used to evaluate the students' grasp of clinical knowledge and skill.

RESULT

Compared with the traditional training group, the duration of implant installation and temporary prosthesis placement of the digital training group decreased significantly (p < 0.05). The implant deviation of the digital training group was lower than that of the traditional training group. The apex deviation (p = 0.015) and angle deviation (p = 0.015) significantly improved with digital training, but differences in platform deviation (p = 0.065) were not statistically significant. The questionnaire survey showed that the overall perception of the inexperienced operators in the digital training group was better than that in the traditional training group.

CONCLUSION

In the hands of inexperienced operators, digital training reduced the operation time and improved the implant accuracy in comparison with traditional training.

Modular Digital and 3D-Printed Dental Models with Applicability in Dental Education

Background and Objectives: The ever more complex modern dental education requires permanent adaptation to expanding medical knowledge and new advancements in digital technologies as well as intensification of interdisciplinary collaboration. Our study presents a newly developed computerized method allowing virtual case simulation on modular digital dental models and 3D-printing of the obtained digital models; additionally, undergraduate dental students' opinion on the advanced method is investigated in this paper. Materials and Methods: Based on the digitalization of didactic dental models, the proposed method generates modular digital dental models that can be easily converted into different types of partial edentulism scenarios, thus allowing the development of a digital library. Three-dimensionally printed simulated dental models can subsequently be manufactured based on the previously obtained digital models. The opinion of a group of undergraduate dental students (n = 205) on the proposed method was assessed via a questionnaire, administered as a Google form, sent via email. Results: The modular digital models allow students to perform repeated virtual simulations of any possible partial edentulism cases, to project 3D virtual treatment plans and to observe the subtle differences between diverse teeth preparations; the resulting 3D-printed models could be used in students' practical training. The proposed method received positive feedback from the undergraduate students. Conclusions: The advanced method is adequate for dental students' training, enabling the gradual design of modular digital dental models with partial edentulism, from simple to complex cases, and the hands-on training on corresponding 3D-printed dental models.

Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis

This literature research had two main objectives. The first objective was to quantify how frequently artificial intelligence (AI) was utilized in dental literature from 2011 until 2021. The second objective was to distinguish the focus of such publications; in particular, dental field and topic. The main inclusion criterium was an original article or review in English focused on dental utilization of AI. All other types of publications or non-dental or non-AI-focused were excluded. The information sources were Web of Science, PubMed, Scopus, and Google Scholar, queried on 19 April 2022. The search string was “artificial intelligence” AND (dental OR dentistry OR tooth OR teeth OR dentofacial OR maxillofacial OR orofacial OR orthodontics OR endodontics OR periodontics OR prosthodontics). Following the removal of duplicates, all remaining publications were returned by searches and were screened by three independent operators to minimize the risk of bias. The analysis of 2011–2021 publications identified 4413 records, from which 1497 were finally selected and calculated according to the year of publication. The results confirmed a historically unprecedented boom in AI dental publications, with an average increase of 21.6% per year over the last decade and a 34.9% increase per year over the last 5 years. In the achievement of the second objective, qualitative assessment of dental AI publications since 2021 identified 1717 records, with 497 papers finally selected. The results of this assessment indicated the relative proportions of focal topics, as follows: radiology 26.36%, orthodontics 18.31%, general scope 17.10%, restorative 12.09%, surgery 11.87% and education 5.63%. The review confirms that the current use of artificial intelligence in dentistry is concentrated mainly around the evaluation of digital diagnostic methods, especially radiology; however, its implementation is expected to gradually penetrate all parts of the profession.

A Bibliometric Analysis of the Landscape of Problem-Based Learning Research (1981-2021)

Background

Problem-Based Learning (PBL) is an instructional method of hands-on, active learning centered on investigating and resolving messy, real-world problems. This study aims to systematically analyze the current status and hotspots of PBL research and provide insights for research in the field.

Methods

Problem-based learning-related publications were retrieved from the Web of Science Core Collection using "Problem-Based Learning". Annual publications, countries, institutions, authors, journals, references, and keywords in the field were visually analyzed using the R, VOSviewer, and Microsoft Excel 2019 software.

Results

A total of 2,790 articles and reviews were analyzed, with a steady increase in publications in the field of PBL. Overall, the United States was the major contributor to the study of PBL. Van Der Vleuten CPM was the key researcher in this field. Moreover, most of the publications were published in Medical Education. Keyword analysis showed that current research hotspots focus on the extensions of PBL teaching mode, application of PBL teaching method, and reform of PBL.

Conclusion

Research on PBL is flourishing. Cooperation and exchange between countries and institutions should be strengthened in the future. These findings will provide a better understanding of the state of PBL research and inform future research ideas.

Applications of Mixed Reality Technology in Orthopedics Surgery: A Pilot Study

Objective: The aim of this study is to explore the potential of mixed reality (MR) technology in the visualization of orthopedic surgery.

Methods: The visualization system with MR technology is widely used in orthopedic surgery. The system is composed of a 3D imaging workstation, a cloud platform, and an MR space station. An intelligent segmentation algorithm is adopted on the 3D imaging workstation to create a 3D anatomical model with zooming and rotation effects. This model is then exploited for efficient 3D reconstruction of data for computerized tomography (CT) and magnetic resonance imaging (MRI). Additionally, the model can be uploaded to the cloud platform for physical parameter tuning, model positioning, rendering and high-dimensional display. Using Microsoft’s HoloLens glasses in combination with the MR system, we project and view 3D holograms in real time under different clinical scenarios. After each procedure, nine surgeons completed a Likert-scale questionnaire on communication and understanding, spatial awareness and effectiveness of MR technology use. In addition to that, the National Aeronautics and Space Administration Task Load Index (NASA-TLX) is also used to evaluate the workload of MR hologram support.

Results: 1) MR holograms can clearly show the 3D structures of bone fractures, which improves the understanding of different fracture types and the design of treatment plans; 2) Holograms with three-dimensional lifelike dynamic features provide an intuitive communication tool among doctors and also between doctors and patients; 3) During surgeries, a full lesion hologram can be obtained and blended in real time with a patient’s virtual 3D digital model in order to give surgeons superior visual guidance through novel high-dimensional “perspectives” of the surgical area; 4) Hologram-based magnetic navigation improves the accuracy and safety of the screw placement in orthopaedics surgeries; 5) The combination of mixed reality cloud platform and telemedicine system based on 5G provides a new technology platform for telesurgery collaboration. Results of qualitative study encourage the usage of MR technology for orthopaedics surgery. Analysis of the Likert-scale questionnaire shows that MR adds significant value to understanding and communication, spatial awareness, learning and effectiveness. Based on the NASA TLX-scale questionnaire results, mixed reality scored significantly lower under the “mental,” “temporal,” “performance,” and “frustration” categories compared to usual 2D.

Conclusion: The integration of MR technology in orthopaedic surgery reduces the dependence on surgeons’ experience and provides personalized 3D visualization models for accurate diagnosis and treatment of orthopaedic abnormalities. This integration is clearly one of the prominent future development directions in medical surgery.

Scoping review of artificial intelligence and immersive digital tools in dental education

PURPOSE

The aim of this scoping review is to examine artificial intelligence (AI) and virtual teaching models within the context of dental education, establish methods to address the resources being investigated, and ultimately augment this approach for future scientific research.

METHODS

To evaluate the applications of AI and immersive technology, a scoping literature review was conducted using the Embase, PubMed, Web of Science, and Cochrane Library database from the years 2018 to May 19, 2021. Additionally, a manual search was completed. The search strategy was formulated according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. Studies that addressed the current uses of virtual devices and their revolutionary potential in dental education were categorized separately for further evaluation.

RESULTS

 Of the 2500 articles found in our initial search results, 31 articles met the inclusion criteria set for this review. The selected studies were directly related to AI and immersive tools in dental education.

CONCLUSION

To our knowledge, there are very few comprehensive literature reviews identifying the applications and efficacy of virtual and AI-driven tools in dental education. With limited verifiable evidence, an improved understanding of virtual and AI domains is needed to enable dental students to adapt to changes within and beyond their dental training education. To increase the scientific value of digital-related research, the scientific community must quickly define guidelines to enhance methodological approaches in order to effectively digitalize dentistry.

The relationship between postural stability and cybersickness: It's complicated - An experimental trial assessing practical implications of cybersickness etiology

Virtual reality (VR) is known to cause cybersickness, and studies report that deteriorations of postural stability coincides with the onset cybersickness. It is unclear whether these deteriorations are the cause or a consequence of cybersickness. Thus, it is also unclear whether measures of postural stability may either predict susceptibility (cause) or objectively measure (consequence) the malaise. To examine whether deteriorations of postural stability can either predict or objectively measure cybersickness, healthy active adults (n = 50) were exposed to one of two different 10 min 360˚ VR videos. Postural stability was assessed, using a force platform, before exposure with eyes open (baseline) and eyes closed, during the first and last minute of exposure, and approximately 10 min after exposure. The deterioration of postural stability from baseline to the first minute of exposure was larger in participants who reported cybersickness, compared to those who did not, for both total trace length (p = 0.017) and standard deviation velocity (p = 0.008). However, there was substantial individual variation and overlap between sick and well participants. Deteriorations of postural stability from baseline to the eyes closed condition did not differ between sick and well participants (trace length, p = 0.270; standard deviation velocity, p = 0.112). There was a significant correlation between the severity of cybersickness and the change of postural stability from the first to the last minute of VR exposure for trace length (r_s=0.32, p = 0.027), but not standard deviation velocity (r_s=0.20, p = 0.187). The deteriorations had returned to baseline levels 10 min after exposure. These findings suggest that deteriorations of postural stability was both a predictor and objective measure at a group level. However, the large individual variation, substantial overlap between sick and well participants, and the limited strength of correlations suggest that deterioration of postural stability has limited practical value as both a predictor and objective measure. These findings emphasize the complicated nature of the relationship between cybersickness and postural stability.

The Modern and Digital Transformation of Oral Health Care: A Mini Review

Dentistry is a part of the field of medicine which is advocated in this digital revolution. The increasing trend in dentistry digitalization has led to the advancement in computer-derived data processing and manufacturing. This progress has been exponentially supported by the Internet of medical things (IoMT), big data and analytical algorithm, internet and communication technologies (ICT) including digital social media, augmented and virtual reality (AR and VR), and artificial intelligence (AI). The interplay between these sophisticated digital aspects has dramatically changed the healthcare and biomedical sectors, especially for dentistry. This myriad of applications of technologies will not only be able to streamline oral health care, facilitate workflow, increase oral health at a fraction of the current conventional cost, relieve dentist and dental auxiliary staff from routine and laborious tasks, but also ignite participatory in personalized oral health care. This narrative article review highlights recent dentistry digitalization encompassing technological advancement, limitations, challenges, and conceptual theoretical modern approaches in oral health prevention and care, particularly in ensuring the quality, efficiency, and strategic dental care in the modern era of dentistry.

Artificial intelligence in fixed implant prosthodontics: a retrospective study of 106 implant-supported monolithic zirconia crowns inserted in the posterior jaws of 90 patients

Background

Artificial intelligence (AI) is a branch of computer science concerned with building smart software or machines capable of performing tasks that typically require human intelligence. We present a protocol for the use of AI to fabricate implant-supported monolithic zirconia crowns (MZCs) cemented on customized hybrid abutments.

Methods

The study protocol consisted of: (1) intraoral scan of the implant position; (2) design of the individual abutment and temporary crown using computer-aided design (CAD) software; (3) milling of the zirconia abutment and the temporary polymethyl-methacrylate (PMMA) crown, with extraoral cementation of the zirconia abutment on the relative titanium bonding base, to generate an individual hybrid abutment; (4) clinical application of the hybrid abutment and the temporary PMMA crown; (5) intraoral scan of the hybrid abutment; (6) CAD of the final crown with automated margin line design using AI; (7) milling, sintering and characterisation of the final MZC; and (8) clinical application of the MZC. The outcome variables were mathematical (quality of the fabrication of the individual zirconia abutment) and clinical, such as (1) quality of the marginal adaptation, (2) of interproximal contact points and (3) of occlusal contacts, (4) chromatic integration, (5) survival and (6) success of MZCs. A careful statistical analysis was performed.

Results

90 patients (35 males, 55 females; mean age 53.3 ± 13.7 years) restored with 106 implant-supported MZCs were included in the study. The follow-up varied from 6 months to 3 years. The quality of the fabrication of individual hybrid abutments revealed a mean deviation of 44 μm (± 6.3) between the original CAD design of the zirconia abutment, and the mesh of the zirconia abutment captured intraorally at the end of the provisionalization. At the delivery of the MZCs, the marginal adaptation, quality of interproximal and occlusal contacts, and aesthetic integration were excellent. The three-year cumulative survival and success of the MZCs were 99.0% and 91.3%, respectively.

Conclusions

AI seems to represent a reliable tool for the restoration of single implants with MZCs cemented on customised hybrid abutments via a full digital workflow. Further studies are needed to confirm these positive results.