Journal of prosthodontic research最新文献

Purpose: This study aimed to analyze how the wall thickness of 3D-printed hollow zirconia teeth affects shape accuracy.

Methods: Datasets with measurement points were created for different artificial teeth resembling the mandibular right first molar (Geomagic Design X, 3D Systems). Reference distances were 9.8 mm for mesio-distal direction (M-D), 10.9 mm for bucco-lingual direction (B-L), 7.0 mm for MB-BB and DB-BB, and 4.5 mm for ML-LB and DL-LB. The outer geometry was identical for all artificial teeth with wall thicknesses of 0.30, 0.50, 0.75, and 1.00 mm. Twenty zirconia teeth were fabricated using a 3D printer (CeraFab 7500 Dental, Lithoz) for each group and sintered before support removal. After performing analog distance measurements using a micrometer screw, the digital distance measurements and angular deviations between measurement points on 3D scans were analyzed. Possible effects were investigated using nonparametric ANOVA, followed by Tukey's honest significant difference (HSD) test for multiple comparisons.

Results: The shape accuracy was acceptable for artificial teeth with wall thicknesses of ≥0.5 mm. The largest distance deviation was observed for a wall thickness of 0.3 mm. In particular, DB-BB showed a median deviation of >56.2 µm, which is significantly larger than that for other test groups, ranging from 7.4-9.5 µm (P < 0.05). In most cases, angular deviations were the largest for teeth with 0.3-mm wall thickness (11.6°) and remained below 5.0° for the other test groups.

Conclusions: Acceptable accuracy was obtained for artificial teeth with wall thicknesses of at least 0.5 mm.

Patients: This case report describes a procedure for assessing changes in occlusal relationships in patients with acquired open bites due to temporomandibular joint disease using an intraoral scanner (IOS). A digital impression was made using the IOS at the initial visit. Subsequent impressions were made every 6 months using the IOS and magnetic resonance imaging (MRI) or computed tomography (CT). Standard triangulated language (STL) image files of two digital impressions at different points in time were superimposed, including the occlusal relationship with reference to the maxillary dentition. Finally, three-dimensional (3D) changes in the occlusal relationship over time were evaluated.

Discussion: In Case 1, the superimposed STL image indicated almost no evident deviation of the mandible. Therefore, an orthodontic treatment was initiated. In contrast, in cases 2 and 3, where changes in the occlusal relationship continued, secondary treatment was postponed and patients continued to be monitored periodically. In case 3, even though left condyle resorption was progressive, the degree of open bite on the right side improved after 6 months. However, the open bite continued to progress for another 6 months despite the stability of the condyle.

Conclusions: Changes in the condylar shape observed using imaging may not always reflect changes in the occlusal relationship. In addition to changes in the condyles and eminences of the temporomandibular joint (TMJ), changes in the occlusal relationships of patients with acquired open bite should be evaluated using an intraoral scanner.

Purpose: This review aims to summarize the available technologies, material categories, and prosthodontic applications of additive manufacturing (AM) dental ceramics, evaluate the achievable accuracy and mechanical properties in comparison with current mainstream computer-aided design/computer-aided manufacturing (CAD/CAM) subtractive manufacturing (SM) methods, and discuss future prospects and directions.

Study selection: This paper is based on the latest reviews, state-of-the-art research, and existing ISO standards on AM technologies and prosthodontic applications of dental ceramics. PubMed, Web of Science, and ScienceDirect were amongst the sources searched for narrative reviews.

Results: Relatively few AM technologies are available and their applications are limited to crowns and fixed partial dentures. Although the accuracy and strength of AM dental ceramics are comparable to those of SM, they have the limitations of relatively inferior curved surface accuracy and low strength reliability. Furthermore, functionally graded additive manufacturing (FGAM), a potential direction for AM, enables the realization of biomimetic structures, such as natural teeth; however, specific studies are currently lacking.

Conclusions: AM dental ceramics are not sufficiently developed for large-scale clinical applications. However, with additional research, it may be possible for AM to replace SM as the mainstream manufacturing technology for ceramic restorations.

Purpose: A growing body of evidence suggests that oral health is associated with a wide range of health outcomes; however, opinions tend to vary because of inconsistent findings. This study aimed to simultaneously examine the association between oral health status and multiple health and well-being indicators using outcome-wide epidemiology.

Methods: Data were obtained from the Japan Gerontological Evaluation Study. Oral health status was categorized as: ≥20 teeth, 10-19 teeth with dental prosthesis, 0-9 teeth with prosthesis, 10-19 teeth without prosthesis, and 0-9 teeth without prosthesis. We examined the associations between oral health status in 2013 and 35 health and well-being outcomes in 2019, including physical/cognitive health, psychological distress, subjective health, social well-being, prosocial/altruistic behaviors, and health behaviors, using two databases (n=32,827 and 15,905).

Results: Compared to individuals with ≥20 teeth, those with <20 teeth had a 10-33% higher risk of mortality and a 6-14% higher risk of functional disability six years later. Additionally, individuals with fewer than 20 teeth tended to go out less frequently and eat fewer vegetables and fruits. Furthermore, individuals with 0-9 teeth without a prosthesis were more likely to have severe functional disability (risk ratio (RR):1.17, 95% confidence interval (CI):1.05-1.31), engage in fewer intellectual activities (standardized difference: 0.17, 95% CI: 0.10-0.24), and feel more hopeless (RR: 1.21, 95% CI: 1.04-1.41).

Conclusions: The prevention of tooth loss and prosthodontic treatment may be associated with reduced mortality and functional disability, as well as maintenance of intellectual ability, frequency of going out, and improvements in dietary lifestyle.

Purpose: To build an image recognition network to evaluate tongue coating status.

Methods: Two image recognition networks were built: one for tongue detection and another for tongue coating classification. Digital tongue photographs were used to develop both networks; images from 251 (178 women, 74.7±6.6 years) and 144 older adults (83 women, 73.8±7.3 years) who volunteered to participate were used for the tongue detection network and coating classification network, respectively. The learning objective of the tongue detection network is to extract a rectangular region that includes the tongue. You-Only-Look-Once (YOLO) v2 was used as the detection network, and transfer learning was performed using ResNet-50. The accuracy was evaluated by calculating the intersection over the union. For tongue coating classification, the rectangular area including the tongue was divided into a grid of 7×7. Five experienced panelists scored the tongue coating in each area using one of five grades, and the tongue coating index (TCI) was calculated. Transfer learning for tongue coating grades was performed using ResNet-18, and the TCI was calculated. Agreement between the panelists and network for the tongue coating grades in each area and TCI was evaluated using the kappa coefficient and intraclass correlation, respectively.

Results: The tongue detection network recognized the tongue with a high intersection over union (0.885±0.081). The tongue coating classification network showed high agreement with tongue coating grades and TCI, with a kappa coefficient of 0.826 and an intraclass correlation coefficient of 0.807, respectively.

Conclusions: Image recognition enables simple and detailed assessment of tongue coating status.

Purpose: To improve smile esthetics, clinicians should comprehensively analyze the face and ensure that the sizes selected for the maxillary anterior teeth are compatible with the available anthropological measurements. The inter commissural (ICW), interalar (IAW), intermedial-canthus (MCW), interlateral-canthus (LCW), and interpupillary (IPW) widths are used to determine the width of maxillary central incisors (CW). The aim of this study was to develop an automated approach using machine learning (ML) algorithms to predict central incisor width in a young Turkish population using anthropological measurements. This automation can contribute to digital dentistry and clinical decision-making.

Methods: In the initial phase of this cross-sectional study, several ML regression models-including multiple linear regression (MLR), multi-layer-perceptron (MLP), decision-tree (DT), and random forest (RF) models-were validated to confirm the central width prediction accuracy. Datasets containing only male and female measurements, as well as combined were considered for ML model implementation, and the performance of each model was evaluated for an unbiased population dataset.

Results: Compared with the other algorithms, the RF algorithm showed improved performance for all cases, with an accuracy of 96%, which represents the percentage of correct predictions. The plot reveals the applicability of the RF model in predicting the CW from anthropological measurements irrespective of the candidate's sex.

Conclusions: These results demonstrated the possibility of predicting central incisor widths based on anthropometric measurements using ML models. The accurate central incisor width prediction from these trials also indicates the applicability of the proposed model to be deployed for enhanced clinical decision-making.

Purpose: In this narrative review, we present the current applications and performances of artificial intelligence (AI) models in different phases of the removable prosthodontic workflow and related research topics.

Study selection: A literature search was conducted using PubMed, Scopus, Web of Science, and Google Scholar databases between January 2010 and January 2023. Search terms related to AI were combined with terms related to removable prosthodontics. Articles reporting the structure and performance of the developed AI model were selected for this literature review.

Results: A total of 15 articles were relevant to the application of AI in removable prosthodontics, including maxillofacial prosthetics. These applications included the design of removable partial dentures, classification of partially edentulous arches, functional evaluation and outcome prediction in complete denture treatment, early prosthetic management of patients with cleft lip and palate, coloration of maxillofacial prostheses, and prediction of the material properties of denture teeth. Various AI models with reliable prediction accuracy have been developed using supervised learning.

Conclusions: The current applications of AI in removable prosthodontics exhibit significant potential for improving the prosthodontic workflow, with high accuracy levels reported in most of the reviewed studies. However, the focus has been predominantly on the diagnostic phase, with few studies addressing treatment planning and implementation. Because the number of AI-related studies in removable prosthodontics is limited, more models targeting different prosthodontic disciplines are required.

Purpose: To investigate whether depth-gauge burs in veneer preparations influence preparation depth in a randomized, controlled, single-blinded trial and whether inexperienced operators can perform adequate veneer preparations.

Methods: Participants were 20 undergraduate dental students with no prior veneer preparation experience. The instruments used were the "Laminate Veneer System" (LVS), "Keramik-Veneers. de" (KVD), and a "Freehand" group (FH) for reference. All participants prepared three educational acrylic resin maxillae and three mandibular central incisors mounted in typodonts in patient simulators. The objectives were to achieve a preparation depth of 0.6 mm (tooth 11) and 0.4 mm (tooth 31). The sequences of the instruments used and prepared teeth were randomized. The measurements were performed using a laser triangulation coordinate-measuring machine. The data were stratified according to tooth location.

Results: The preparation depths of both depth-gauge-instrument-groups LVS and KVD achieved the objectives significantly better than did the instruments from the "Freehand" group (P < 0.001). The differences between the depth gauge groups were insignificant, although the maximum preparation depths were smaller in the KVD group. Regarding the prepared teeth, the preparation depths in the mandibular incisors were lower, and the differences were smaller.

Conclusions: The use of special depth-gauge burs for initial veneer preparation leads to significantly lower preparation depths than "Freehand" preparations. The tapered instruments resulted in a lower incidence of extreme preparation depths. The inexperienced operators performed veneer preparation remarkably well.

Purpose: Individuals with impaired masticatory function tend to prefer soft foods, which results in decreased masticatory muscle activity. This study examined the association between the oral condition (number of teeth, occlusal force, and occlusal contact area) and dietary hardness using a daily dietary questionnaire.

Methods: This cross-sectional study evaluated 1841 participants aged 69-71 and 79-81 years. Registered dentists examined the number of teeth, occlusal force, and occlusal contact area. Dietary hardness was defined as the estimated masticatory muscle activity required for a habitual diet. Habitual diet during the preceding month was assessed using a brief self-administered diet history questionnaire. Confounding factors, such as age, sex, socioeconomic status, smoking habits, history of chronic diseases (hypertension, hyperlipidemia, and diabetes), and cognitive function were also evaluated. Multivariate linear regression analyses were performed to assess the association between dietary hardness and each oral condition.

Results: Occlusal force (standardized regression coefficients [β]=0.08, P < 0.01) and occlusal contact area (β=0.06, P < 0.01) were significantly associated with dietary hardness after adjusting for the confounding factors. Number of teeth was not significantly associated with dietary hardness. In addition, the associations between dietary hardness, sex, and a history of diabetes were stronger than those between dietary hardness and oral factors.

Conclusions: Occlusal force and contact area were significantly associated with dietary hardness as estimated from the masticatory muscle activity using a daily diet questionnaire.