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

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.

Purpose: To investigate the relevant factors affecting the accuracy of the autonomous dental implant robotic system (ADIR)-assisted implant surgery, providing the foundation for the clinical application of ADIR.

Materials and methods: This retrospective study involved 85 patients with 138 implants who underwent ADIR-assisted implant surgery between March 2022 and May 2024. Drilling plans and virtual preoperative implant placement were designed preoperatively. Cone-beam computed tomography (CBCT) was used immediately after surgery to assess the linear and angular deviations in two-dimensional (2D) and three-dimensional (3D) space between planned and actual implants. Generalized estimation equations (GEE) were applied to analyze the relevant factors affecting the accuracy of ADIR-assisted implant surgery.

Results: The GEE showed a significant correlation between relevant factors (implant position and length) and the linear deviations at both the 2D platform and apex in ADIR-assisted implant surgery (p < 0.05). The platform and apex are more deviated linearly in the anterior region than in the posterior region. Compared to 8 mm implants, 12 and 16 mm implants exhibited larger linear deviation. Sex and age were relevant factors influencing implant 3D positional deviation. Females and patients over 40 years of age showed increased 3D linear deviation of the platform (p < 0.05), but there was no statistical difference in angular deviation. Implant shape, diameter, bone classification, side of arch, guided bone regeneration (GBR), and flap procedure had statistically nonsignificant effects on ADIR-assisted implant surgical accuracy.

Conclusions: The relevant factors (implant length, implant position, age, and sex of the patient) may affect the accuracy of ADIR-assisted implant surgery. This study is of clinical interest and helps surgeons make clinical decisions to improve the precision of implant surgery.

Purpose: The success of removable partial dentures (RPDs) depends on well-designed abutments or surveyed crowns. Advances in computer-aided design and computer-aided manufacturing (CAD-CAM) technology have made all-ceramic materials viable alternatives to traditional ceramo-metal surveyed crowns, but their performance, particularly regarding internal fit and fracture resistance, requires further studies, especially with different rest seat preparations simulated on the abutment dies. This study evaluated the internal fit and fracture resistance of CAD-CAM ceramic crowns with wide and narrow rest seat designs to assess their potential as surveyed crowns for RPDs.

Materials and methods: Sixty mandibular premolar abutment dies were modified to simulate narrow and wide occlusal relief designs and were divided into six groups based on the design (wide/narrow) and material type: force-absorbed hybrid ceramics (HC), zirconium lithium silicate (ZLS), and lithium disilicate glass-ceramic (LDC). CAD-CAM ceramic crowns were fabricated, milled, and analyzed for internal fit using Geomagic Control X software. Fracture resistance in newton (N) was tested using a universal testing machine. Scanning electron microscopy (SEM) was employed to examine fracture morphology. Statistical analyses included two-way analysis of variance (ANOVA) and post hoc Tukey's test (α = 0.05).

Results: The LDC group had the highest fracture resistance, while ZLS and HC showed no significant difference [F(2) = 10.523, p < 0.001]. Internal fit did not significantly differ between materials [F(2) = 0.381, p = 0.686], though LDC had a slightly larger internal gap. Rest seat design significantly affected both fracture resistance and internal fit [F(1) = 68.581, p < 0.001; F(1) = 11.185, p = 0.002], with wide designs showing higher fracture resistance and narrow designs having larger internal gaps. SEM revealed crack propagation originating from rest seat bases, with longer crack lines observed in wide rest designs.

Conclusion: Rest seat design significantly influences the fracture resistance and internal fit of CAD-CAM ceramic crowns. Wide rest seat designs provide superior fracture resistance compared to narrow designs, while narrow seats exhibit larger internal gaps, potentially compromising restoration longevity.

Purpose: To evaluate the accuracy of guided surgery in a healed ridge and various maxillary anterior extraction sockets.

Materials and methods: Forty radiopaque urethane resin bone models simulating the maxillary right central incisor were fabricated and divided into four groups (n = 10 each). Group H (healed ridge), Group L (socket adjacent to labial cortex), Group C (centralized socket), and Group P (socket adjacent to palatal cortex). Models were scanned using a TRIOS 4 intraoral scanner, and CBCT scans were acquired. Implant planning was performed using software (Codiagnostix), and implants were placed with a fully guided static computer-aided implant surgery (s-CAIS) protocol. Deviations between planned and actual implant positions were measured in global, bucco-lingual, and mesio-distal deviations at the crest and apex.

Results: Group C showed the greatest global deviation at both the crest (0.83 ± 0.34 mm) and apex (0.98 ± 0.29 mm), whereas Group L showed the lowest global deviations at the crest (0.38 ± 0.17 mm) and apex (0.49 ± 0.26 mm). Angular deviation was highest in Group H (2.91° ± 1.37°) and lowest in Group C (1.87° ± 1.11°). Depth deviations were not statistically different. One-way ANOVA revealed socket morphology significantly influenced global, labial-palatal, and mesial-distal deviations at both crest and apex levels (p < 0.05), with Group L showing superior apical accuracy (p < 0.001).

Conclusions: Socket morphology significantly affects s-CAIS accuracy. Centralized sockets showed greater positional deviations, particularly at the crest. Socket morphology should be carefully considered during virtual treatment planning for immediate implant placement.

Alveolar bone morphology drives the edentulous patient's rehabilitation. In edentulism, maxillary resorption is often in three vectors: superiorly, medially, and posteriorly, leading to a prosthetically unfavorable pseudo-class III ridge relationship. Longstanding edentulism, especially in the context of ill-fitting dentures, can result in severe maxillary atrophy. Rehabilitation of the severely atrophic maxilla remains a challenge, frequently requiring extensive bone grafting procedures in combination with endosseous dental implants. Graftless options, using longer endosseous and/or tilted dental implants placed into the nasal, pyriform rim, pterygoid process, and zygomatic bone, have been developed to solve this treatment dilemma. These options have specific patient anatomy limitations, can be technique sensitive, and can result in increased patient morbidity. Digitally planned, custom-milled, and rigidly fixated subperiosteal implants offer a recently introduced immediate fixed option when conventional solutions fail or are contraindicated. Cone-beam computed tomography (CBCT) and computer-aided design and computer-aided manufacturing (CAD-CAM) redefine a controversial 70-year-old concept, using prosthodontic reverse-engineering to offer stability, reduced morbidity, and improved patient satisfaction. Long-term follow-up for the use of this technique in fixed definitive restorations is not available at this time.

Rigidly fixated custom subperiosteal implants (SPIs) have been reported in the literature for fixed retention of a prosthesis when there is limited or absent alveolar bone for placement of endosteal implants. Advances in digital technology and manufacturing have provided excellent adaptation and stability for this latest generation of SPIs, and the applications for this technique extend beyond fixed restorations of the partially or completely edentulous arch. In this case report, a modern patient-specific SPI was utilized to retain a surgical obturator without additional interdental or interosseous wiring.