Esthetic treatment planning with digital animation of the smile dynamics: A technique to create a 4-dimensional virtual patient

Creating a 3D diagnostic cast with realistic tooth shade and translucency using an open source nondental CAD software program: A dental technique

This article describes a digital technique for acquiring a 3-dimensional (3D) diagnostic cast with authentic tooth shade and translucency using an open source nondental computer-aided design (CAD) software program detailing the operational methods and parameters. The resultant 3D diagnostic cast can be transmitted to a dental laboratory for the fabrication of definitive prostheses.

The influence of different tooth proportions obtained using digital smile design on the perception of smile esthetics

OBJECTIVE

The aim of this study is to examine the effect of designs using different esthetic dental proportions made with a digital smile design program on the esthetic perception of individuals of different ages, genders and educational statuses.

MATERIALS AND METHODS

Different smile designs were made on facial photos taken of a female and male model using a smile design program. Four different dental proportions (golden proportion [GPR], golden percentage [GPE]), Preston proportion [P] and recurring esthetic dental proportion [RED]) and two different tooth shapes (oval and square) were used. Images with 16 different smile designs were presented to 4th and 5th-year students of a faculty of dentistry, dentists, specialist dentists and laypersons for scoring.

RESULTS

The gender of the participants did not affect the scores given (p > 0.05), and participants over the age of 30 and lay people had higher scores (p < 0.05). The GPR design was scored lower than RED when all designs were subdivided by tooth shape and gender (p < 0.001).

CONCLUSIONS

The esthetic perceptions of people of different ages and dentistry education levels may differ from each other. Using the GPR when designing a digital smile may not be suitable for both genders.

CLINICAL SIGNIFICANCE

If esthetic dental proportions are to be utilized when designing a smile, it may be more appropriate to use the P and RED proportions instead of the GPR. In addition, if the patients whose smiles will be designed are young and have received dental education, it should be considered that their esthetic expectations may be high. Trial registration ClinicalTrials.gov Identifier: NCT0567043.

Virtual patient representation with silicone guide and a 3D scanner accessory for a user-friendly facial scanning workflow: A clinical report of smile design and ceramic veneers

Digital smile design and ceramic veneers are described with virtual patient representation. The procedure included facial scanning with a 3D scanner accessory (Structure sensor pro; Occipital Inc) mounted on a tablet computer (iPad; Apple Inc) and an innovative chairside silicone guide to replace the intraoral scan body for a straightforward and user-friendly workflow.

Accuracy between 2D Photography and Dual-Structured Light 3D Facial Scanner for Facial Anthropometry: A Clinical Study

(1) Background: Facial scanners are used in different fields of dentistry to digitalize the soft tissues of the patient's face. The development of technology has allowed the patient to have a 3-dimensional virtual representation, facilitating facial integration in the diagnosis and treatment plan. However, the accuracy of the facial scanner and the obtaining of better results with respect to the manual or two-dimensional (2D) method are questionable. The objective of this clinical trial was to evaluate the usefulness and accuracy of the 3D method (a dual-structured light facial scanner) and compare it with the 2D method (photography) to obtain facial analysis in the maximum intercuspation position and smile position. (2) Methods: A total of 60 participants were included, and nine facial landmarks and five interlandmarks distances were determined by two independent calibrated operators for each participant. All measurements were made using three methods: the manual method (manual measurement), the 2D method (photography), and the 3D method (facial scanner). All clinical and lighting conditions, as well as the specific parameters of each method, were standardized and controlled. The facial interlandmark distances were made by using a digital caliper, a 2D software program (Adobe Photoshop, version 21.0.2), and a 3D software program (Meshlab, version 2020.12), respectively. The data were analyzed by SPSS statistical software. The Kolmogorov-Smirnov test revealed that trueness and precision values were normally distributed (p > 0.05), so a Student's t-test was employed. (3) Results: Statistically significant differences (p ≤ 0.01) were observed in all interlandmark measurements in the 2D group (photography) to compare with the manual group. The 2D method obtained a mean accuracy value of 2.09 (±3.38) and 2.494 (±3.67) in maximum intercuspation and smile, respectively. On the other hand, the 3D method (facial scanner) obtained a mean accuracy value of 0.61 (±1.65) and 0.28 (±2.03) in maximum intercuspation and smile, respectively. There were no statistically significant differences with the manual method. (4) Conclusions: The employed technique demonstrated that it influences the accuracy of facial records. The 3D method reported acceptable accuracy values, while the 2D method showed discrepancies over the clinically acceptable limits.

Three-dimensional morphometric analysis of facial units in virtual smiling facial images with different smile expressions

PURPOSE

Accuracy of image matching between resting and smiling facial models is affected by the stability of the reference surfaces. This study aimed to investigate the morphometric variations in subdivided facial units during resting, posed and spontaneous smiling.

MATERIALS AND METHODS

The posed and spontaneous smiling faces of 33 adults were digitized and registered to the resting faces. The morphological changes of subdivided facial units at the forehead (upper and lower central, upper and lower lateral, and temple), nasal (dorsum, tip, lateral wall, and alar lobules), and chin (central and lateral) regions were assessed by measuring the 3D mesh deviations between the smiling and resting facial models. The one-way analysis of variance, Duncan post hoc tests, and Student's t-test were used to determine the differences among the groups (α = .05).

RESULTS

The smallest morphometric changes were observed at the upper and central forehead and nasal dorsum; meanwhile, the largest deviation was found at the nasal alar lobules in both the posed and spontaneous smiles (P < .001). The spontaneous smile generally resulted in larger facial unit changes than the posed smile, and significant difference was observed at the alar lobules, central chin, and lateral chin units (P < .001).

CONCLUSION

The upper and central forehead and nasal dorsum are reliable areas for image matching between resting and smiling 3D facial images. The central chin area can be considered an additional reference area for posed smiles; however, special cautions should be taken when selecting this area as references for spontaneous smiles.

The Status of Digital Dental Technology Implementation in the Saudi Dental Schools' Curriculum: A National Cross-Sectional Survey for Healthcare Digitization

Objective: The primary objective of this cross-sectional national study was to investigate the status of digital dental technology (DDT) adoption in Saudi Arabian undergraduate dental education. A secondary objective was to explore the impact of dental schools' funding sources to incorporate digital technologies. Methods: A self-administered questionnaire was distributed to the chairpersons of prosthetic sciences departments of the 27 dental schools in Saudi Arabia. If any department chairman failed to respond to the survey, a designated full-time faculty member was contacted to fill out the form. The participants were asked about the school's sector, DDT implementation in the curriculum, implemented level, their perceptions of the facilitators and challenges for incorporating DDT. Results: Of the 27 dental schools (18 public and 8 private), 26 responded to the questionnaire (response rate: 96.3%). The geographic distribution of the respondent schools was as follows: 12 schools in the central region, 6 in the western region, and 8 in other regions. Seventeen schools secure and preserve patients' records using electronic software, whereas nine schools use paper charts. Seventeen schools (64,4%) implemented DDT in their curricula. The schools that did not incorporate DDT into their undergraduate curricula were due to not being included in the curriculum (78%), lack of expertise (66%), untrained faculty and staff (44%), and cost (33%). Conclusions: This national study showed that digital components still need to be integrated into Saudi Arabian dental schools' curricula and patient care treatment. Additionally, there was no association between funding sources and the DDT implementation into the current curricula. Consequently, Saudi dental schools must emphasize the implementation and utilization of DDT to align with Saudi Vision 2030 for healthcare digitization and to graduate competent dentists in digital dental care.

Facial scanning technologies in the era of digital workflow: A systematic review and network meta-analysis

PURPOSE

The aim of this network meta-analysis is to evaluate the accuracy of various face-scanning technologies in the market, with respect to the different dimensions of space (x, y, and z axes). Furthermore, attention will be paid to the type of technologies currently used and to the best practices for high-quality scan acquisition.

MATERIAL AND METHODS

The review was conducted following the PRISMA guidelines and its updates. A thorough search was performed using the digital databases MEDLINE, PubMed, EMBASE, and the Cochrane Central Register of Controlled Trials by entering research lines or various combinations of free words. The main keywords used during the search process were "photogrammetry", "laser scanner", "optical scanner", "3D, and "face".

RESULTS

None of the included technologies significantly deviated from direct anthropometry. The obtained mean differences in the distances between the considered landmarks range from 1.10 to -1.74 mm.

CONCLUSION

Limiting the movements of the patient and scanner allows for more accurate facial scans with all the technologies involved. Active technologies such as laser scanners (LS), structured light (SL), and infrared structured light (ISL) have accuracy comparable to that of static stereophotogrammetry while being more cost-effective and less time-consuming.

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.

Digital Workflow in Implant Treatment Planning For Terminal Dentition Patients

Treatment planning for the transition of patients from terminal dentition to full-arch implant rehabilitation poses challenges. Such challenges pertain to achieving the new orientation of the occlusal and esthetic plane as well as the change of vertical dimension of occlusion (VDO), while the fixed provisionalization using a digital workflow, still tends to be considered complex and hard to perform. This article illustrates step-by-step the utilization of a digital workflow protocol in the treatment planning for rehabilitation of terminal dentition patients, simplifying the smile design and ensuring that fixed provisionalization serves both the functional and esthetic requirements. This protocol includes facially-driven, three-dimensional (3D) digital smile design and chairside mock-up restoration workflows that enable prosthetically-driven assessment prior to implant treatment planning and 3D printing of surgical templates, which can predictably reduce chairside time and adjustments at the surgical and fixed provisionalization appointment. This article is protected by copyright. All rights reserved.

Integration of imaging modalities in digital dental workflows - possibilities, limitations, and potential future developments

The digital workflow process follows different steps for all dental specialties. However, the main ingredient for the diagnosis, treatment planning and follow-up workflow recipes is the imaging chain. The steps in the imaging chain usually include all or at least some of the following modalities: cone-beam computed tomographic data acquisition, segmentation of the cone-beam computed tomography image, intraoral scanning, facial three-dimensional soft tissue capture and superimposition of all the images for the creation of a virtual augmented model. As a relevant clinical problem, the accumulation of error at each step of the chain might negatively influence the final outcome. For an efficient digital workflow, it is important to be aware of the existing challenges within the imaging chain. Furthermore, artificial intelligence-based strategies need to be integrated in the future to make the workflow more simplified, accurate and efficient.