Journal of Prosthodontics-Implant Esthetic and Reconstructive Dentistry最新文献

Purpose: This study aimed to develop a novel transformer-based model for automated tooth morphology reconstruction and evaluate its accuracy and generalizability across multiple tooth positions.

Materials and methods: Digital full-arch casts with intact target and adjacent teeth were collected, comprising 500 first molars, 600 first premolars, and 700 central incisors after data augmentation. A transformer-based implicit neural network (INN) model was developed by incorporating a self-structure enhancement module and multi-view 2D depth maps. The model was trained with either 12,000 or 50,000 sampling points. Performance was assessed using chamfer distance (CD), F-score, and volumetric intersection over union (IoU). Reconstructed generated crowns (GC) were compared with original crowns (OC) and technician-designed crowns (TC) in terms of 3D morphological deviations, measured by the root mean square (RMS, mm), and dimensional differences. Statistical analysis was performed using a linear mixed-effects model, repeated measures ANOVA or nonparametric tests (α = 0.05).

Results: The model trained with 50,000 sampling points exhibited superior reconstruction performance, with high similarity to natural tooth morphology. Central incisors showed the best accuracy (CD = 0.0028 × 10^-2, F-score = 0.9670, and IoU = 0.9716). In molars, GC presented comparable surface deviations to TC, with no significant difference. For premolars, GC exhibited higher deviations compared to TC (0.2255 ± 0.0285 mm vs. 0.1557 ± 0.0422 mm, p = 0.002). Similarly, in the incisor, GC exhibited higher deviations compared to TC (0.2155 ± 0.0272 mm vs. 0.1643 ± 0.0295 mm, p = 0.014). In dimensional analysis, GC achieved a close match to OC across all tooth types (p > 0.05). At the same time, TC showed significantly greater mesiodistal width in molars and inciso-gingival height in incisors.

Conclusions: The proposed transformer-based model effectively achieved automated reconstruction of missing single-tooth morphology with acceptable accuracy and adaptability across different tooth positions. Its high fidelity and dimensional consistency highlight its potential for improving efficiency in digital dental restoration workflows. Further studies are warranted to expand dataset diversity, refine the model architecture, and incorporate clinical and functional validations.

Purpose: Performing endodontic procedures on existing crowns is common when replacing the crown is not feasible. Traditional triangular access (TTA) is standard for maxillary molars, but more conservative designs are reported in the literature. However, research comparing the fracture resistance of maxillary molar zirconia crowns using traditional and novel endodontic access sealed with composite resin remains limited. The purpose of this in vitro study was to evaluate the fracture resistance of maxillary molar zirconia crowns with various endodontic cavity designs: traditional triangular access (TTA), conservative triangular access (CTA), and conservative circular access (CCA). A control group with no endodontic access (NEA) was also included.

Materials and methods: A maxillary right first molar typodont tooth was prepared for a full all-ceramic crown. The preparation was scanned, and 48 dies were 3D-printed based on the tooth preparation. A total of 48 zirconia crowns were fabricated (n = 12 per group) and divided into four groups according to the endodontic access cavity design: TTA, CTA, CCA, and a control group without an endodontic cavity. To ensure consistency, all restorations were designed and fabricated using a digital workflow. Endodontic access was created using a specialized bur kit and sealed using a repair kit for damaged ceramic restorations along with resin composite. The restorations were cemented, and all samples underwent artificial aging with 10,000 thermal cycles between 5°C and 55°C, with a dwell time of 30 s. The samples were then loaded to failure using a universal testing machine. The maximum load to fracture was analyzed using a one-way ANOVA and post hoc Tukey honestly significant difference (HSD) test (α = 0.001). Additionally, the fracture patterns of the specimens were evaluated descriptively using a scanning electron microscope.

Results: The mean fracture resistance of maxillary molar zirconia crowns varied significantly by endodontic access type. CCA showed the highest resistance (3677 N) among access groups, followed by CTA (3385 N) and TTA (2927 N). The control group NEA (3834 N) exhibited the highest overall resistance, exceeding all access groups.

Conclusions: Conservative access designs increased the fracture resistance of zirconia crowns compared with traditional access, with circular access showing the highest strength. However, all access preparations reduced resistance relative to crowns without endodontic access.

Purpose: The present study was conducted to assess the cyclic fatigue resistance of implant-supported long single crowns and the effect of retention type on their mechanical behavior. The investigation aimed at evaluating failure modes and fracture resistance under conditions simulating mastication.

Materials and methods: Thirty implant-supported crowns were made, out of which 15 were screw-retained and 15 were cement-retained implant prostheses. The samples were tested on cyclic fatigue loading in a universal testing machine using physiological masticatory forces. The test method adhered to ISO 14801 guidelines, where cyclic loading at 275 N was used at a frequency of 5 Hz until failure or up to 5 million cycles. Fractographic analysis was carried out using FESEM. Statistical analysis was done using the independent t-test for fatigue resistance between groups.

Results: Screw-retained prostheses demonstrated a greater mean number of cycles to screw fracture (105,430 cycles) than cement-retained prostheses (87,039 cycles), and the difference was not statistically significant (p = 0.503). Screw-retained crowns demonstrated greater fatigue resistance at the expense of increased screw loosening. Cement-retained crowns demonstrated lower fatigue resistance but improved stability. Fractographic analysis verified fatigue fractures with characteristic failure modes between retention types.

Conclusion: Screw-retained crowns and cement-retained crowns have statistically insignificant differences in fatigue resistance. Screw-retained crowns are subject to loosening of the screw, whereas cement-retained crowns are more stable. The choice of retention type should be based on mechanical performance and clinical retrievability.

Purpose: To compare the cost-efficiency of digitally designed and manufactured removable complete dentures (RCDs) with conventionally fabricated RCDs through a systematic review and meta-analysis.

Methods: A comprehensive electronic and manual search was performed in PubMed, Embase, Web of Science, and Scopus up to February 10, 2025. Eligible studies included clinical trials and cohort studies comparing cost-related outcomes of digital and conventional RCD workflows. Primary outcomes were laboratory, clinical, and total costs; secondary outcomes included the number of treatment sessions. Meta-analyses were conducted using random-effects models. Risk of bias was evaluated using standardized tools.

Results: Four retrospective studies and one prospective study, including 184 patients, met the inclusion criteria. No statistically significant differences were observed between digital and conventional workflows in laboratory costs (mean difference [MD]: -239.77 (2025 USD); p = 0.1063), clinical costs (MD: 74.39 (2025 USD); p = 0.4514), total costs (MD: -357.76 (2025 USD); p = 0.2577), or treatment sessions (MD: -1.47; p = 0.3514). Operator experience significantly influenced clinical costs (p < 0.0001) and the number of sessions (p = 0.0001).

Conclusion: Within the limitations of the available evidence, digital and conventional workflows for RCD fabrication demonstrated comparable cost-efficiency. Although digital workflows may reduce the number of sessions when performed by experienced clinicians, the current evidence is insufficient to establish a clear cost-efficiency advantage.

The purpose of this article is to describe a technique to assess fit and modify zirconia in its pre-sintered state, resulting in an ideally contoured restoration. A zirconia crown and an associated die were digitally designed. A secondary die was formed by using the exact shrinkage factor of the milled zirconia crown to uniformly expand the die to evaluate the pre-sintered zirconia. The pre-sintered zirconia crown was placed on the expanded die to confirm marginal fit and adjust the safety zone. The crown was sintered and placed on the unaltered die to confirm accuracy of adjustments. This article describes a reproducible technique that aims to idealize marginal contours in zirconia restorations in the pre-sintered state and reduce post-sintered adjustments.

Purpose: Adaptation of inlays is crucial for clinical success. While various methods are currently available for measuring the marginal and internal fit of restorations, studies evaluating novel measurement techniques are scarce. This in vitro study aimed to evaluate two new digital methods and compare the marginal and internal fit of computer-aided design and computer-aided manufacturing (CAD-CAM) inlays fabricated with three different materials by using the two methods.

Materials and methods: A standardized inlay preparation was performed on a typodont right first molar and optically scanned. Three different material groups of inlays (n = 15) were designed and fabricated based on the scanned preparations: (a) LD: lithium disilicate ceramic, (b) ZLS: zirconia reinforced lithium silicate ceramic, (c) RNC: resin nano-ceramic. Digital silicone replica technique (DSRT) and triple-scan technique (TST) were both used to measure the marginal gap (MG) at 250 ± points and the internal gap (IG) at 1300 ± points. Repeated measurement ANOVA was used to assess gap differences related to the materials. The reliability of measurement methods was tested by the coefficient of variation (CV), while paired t-tests and the Bland-Altman diagram were used to compare the differences in marginal fit values (α = 0.05).

Results: The CV showed that the DSRT method had better repeatability. The MG and IG values measured by the DSRT were smaller than all samples. The RNC group demonstrated a significantly lower mean MG (27.46 ± 2.33 µm and 46.27 ± 5.65 µm, p < 0.05) than the other two groups with both methods. However, no statistically significant inter-group differences were found in IG.

Conclusion: Both DSRT and TST are reliable for assessing the marginal and internal gap of inlays. TST is a new method for assessing the marginal and internal gap. As a reliable method widely used in marginal fit measurement, the reliability and stability of DSRT is better than TST, although their results are consistent. The marginal fit of CAD-CAM inlays is influenced by the restorative materials, with RNC providing the best marginal fit.

Purpose: To investigate the effectiveness of a novel transformer-based deep learning model for generating monolithic implant-supported crowns (ISCs), comparing its performance to traditional software-generated crowns.

Materials and methods: A total of 311 patients who received single implant placements in the posterior first molar area were included. Digital impressions as well as technician-designed crowns were imported into the AI model. The PoinTr architecture-based AI model was trained on 291 cases and validated using 20 additional cases. Four groups of ISC designs were evaluated: Group 1, Software1-generated crowns; Group 2, Software 2-generated crowns; Group 3, AI-generated crowns; and Group 4, technician-designed crowns. Accuracy was evaluated through overall contour deviation, occlusal morphology, proximal contact, and emergence profile.

Results: Relative to the reference (Group 4), AI-generated crowns (Group 3) demonstrated significantly lower overall contour deviation (438.6 ± 169.4 µm) compared with both software-generated crowns (Groups 1-2: 679.5-705.1 µm, p < 0.01). Occlusal discrepancies were smaller and contact distributions more comparable to technician-designed crowns in the AI group, while software-generated crowns showed higher frequencies of premature contacts. For emergence profile, AI crowns predominantly reproduced concave contours and angles approximating technician-designed crowns, whereas software groups often produced convex forms. Across all automated groups (1-3), proximal contact adaptation remained less accurate than in technician-designed crowns.

Conclusions: Within the limitations of this proof-of-concept study, AI-generated implant-supported crowns achieved closer approximation to technician designs than software-generated crowns, particularly in contour, occlusal morphology, and emergence profile.

Purpose: This systematic review evaluated the application of ChatGPT and other large language models in answering dental patient inquiries and explored their accuracy.

Methods: Following PRISMA guidelines, seven databases, including PubMed, Scopus, and Cochrane, were searched for studies published between November 2022 and June 2024. The review focused on publications addressing large language models' performance in responding to patients' questions, with studies evaluated for quality using the modified QUADAS-2 framework. Data on accuracy were extracted, and a meta-analysis was conducted. Subgroup and sensitivity analyses were performed to explore variations in performance and ensure robustness.

Results: A total of 25 studies were included, evaluating ChatGPT and other large language models. The pooled accuracy score for all large language models included was 81.87% (95% CI: 77.24%-86.51%), and 69.9% (95% CI: 57.3%-82.6%) of responses were considered clinically acceptable. Subgroup analysis revealed that the accuracy score of responses from ChatGPT-3.5 was significantly higher than Microsoft Bing but not different from ChatGPT-4.0 and Google Bard.

Conclusion: ChatGPT and other LLMs are promising alternatives for addressing patient inquiries and providing oral health education. However, challenges remain regarding accuracy, variability, and their ability to handle complex clinical scenarios, and further research is needed.