The Accuracy of 3D-Printed Fixed Dental Restorations

Three-Dimensional Printing Resin-Based Dental Provisional Crowns and Bridges: Recent Progress in Properties, Applications, and Perspectives

Three-dimensional (3D) printing represents a pivotal technological advancement in dental prosthetics, fundamentally transforming the fabrication of provisional crowns and bridges through innovative vat photopolymerization methodologies, specifically stereolithography (SLA) and digital light processing (DLP). This comprehensive scholarly review critically examines the technological landscape of 3D-printed resin-based dental provisional crowns and bridges, systematically analyzing their material performance, clinical applications, and prospective developmental trajectories. Empirical investigations demonstrate that these advanced restorations exhibit remarkable mechanical characteristics, including flexural strength ranging from 60 to 90 MPa and fracture resistance of 1000-1200 N, consistently matching or surpassing traditional manufacturing techniques. The digital workflow introduces substantial procedural innovations, dramatically reducing fabrication time while simultaneously achieving superior marginal adaptation and internal architectural precision. Despite these significant technological advancements, critical challenges persist, encompassing material durability limitations, interlayer bonding strength inconsistencies, and the current paucity of longitudinal clinical evidence. Contemporary research initiatives are strategically focused on optimizing resin formulations through strategic filler incorporation, enhancing post-processing protocols, and addressing fundamental limitations in color stability and water sorption characteristics. Ultimately, this scholarly review aims to provide comprehensive insights that will inform evidence-based clinical practices and delineate future research trajectories in the dynamically evolving domain of digital dentistry, with the paramount objective of advancing patient outcomes through technological innovation and precision-driven methodological approaches.

The role of artificial intelligence in intraoral scanning for complete-arch digital impressions: An in vitro study

OBJECTIVES

Artificial intelligence (AI) is increasingly being integrated into intraoral scanners (IOS) to improve the quality of digital impressions. However, information on the accuracy of AI-assisted virtual models is limited. This study aimed to evaluate the effect of AI, specifically its application in filling mesh defects, by evaluating the accuracy of digital impressions of complete arches in an in vitro setting.

METHODS

Three types of articulated maxillary models and antagonist models made from Type IV gypsum were used: an intact model (Model 1), a model with prepared teeth (FDI 13, 16) and missing teeth (FDI 14, 15) (Model 2), and a model with prepared teeth (FDI 13, 16) and missing teeth (FDI 14, 15, 17) (Model 3). A total of 120 scans were obtained using an IOS (3Shape Trios 5) with 20 digital impressions with AI assistance (AI-ON) and 20 without (AI-OFF). The files were compared with reference files generated by a desktop scanner (3Shape E3) and were analyzed for accuracy using a reverse engineering and metrology software (Geomagic Control X).

RESULTS

While AI-OFF shows better trueness in most relations, AI-ON improves precision and demonstrates significant advantages in accuracy, particularly in arch distortion and whole arch deviation measurements.

CONCLUSIONS

This study demonstrates that incorporating AI into digital impressions significantly improves the precision and accuracy of scans, particularly by enhancing consistency and reducing errors. Further studies are needed to explore the full potential of AI across different clinical scenarios and scanner types.

CLINICAL SIGNIFICANCE

This study highlights the role of AI in improving the accuracy of intraoral scans by addressing mesh defects, contributing to more precise digital workflows in dentistry.

Effect of Pixel Offset Adjustments for XY Plane Dimensional Compensation in Digital Light Processing 3D Printing on the Surface Trueness and Fit of Zirconia Crowns

This study aimed to evaluate the effect of pixel offset adjustments in digital light processing (DLP) three-dimensional (3D) printing on the marginal and internal fit and surface trueness of zirconia crowns. Zirconia crowns were designed using dental computer-aided design software (Dentbird; Imagoworks) and fabricated with a vat photopolymerization DLP 3D printer (TD6+; 3D Controls) under three pixel offset conditions (-1, 0, and 1). Pixel offset refers to the controlled modification of the outermost pixels in the XY plane during printing to compensate for potential dimensional inaccuracies. The marginal and internal fit was assessed using a triple-scan protocol and quantified using root mean square (RMS) values. Surface trueness was evaluated by measuring RMS, positive and negative errors between the designed and fabricated crowns. Statistical analyses included one-way ANOVA and Pearson correlation analysis (α = 0.05). The Pixel offset had a significant effect on fit accuracy and surface trueness (p < 0.05). Higher pixel offsets increased marginal discrepancies (p = 0.004), with the marginal gap exceeding 120 µm at a pixel offset of 1 (114.5 ± 14.6 µm), while a pixel offset of -1 (85.5 ± 18.6 µm) remained within acceptable limits (p = 0.003). Surface trueness worsened with increasing pixel offset, showing greater positive errors (p < 0.001). Optimizing pixel offset in DLP 3D printing is crucial to ensuring clinically acceptable zirconia crowns. Improper settings may increase marginal discrepancies and surface errors, compromising restoration accuracy.