Effect of printing layer thickness on the trueness and fit of additively manufactured removable dies

To assess crown die trueness using additive manufacturing (AM) based on intraoral scanning (IOS) data and compare it with stone models. Materials and Methods: Crown dies with four finish line typesequigingival shoulder (SAE), subgingival shoulder (SAS), equigingival chamfer (CAE), and subgingival chamfer (CAS)-were incorporated into a reference model and scanned with a coordinate measurement machine (CMM; n = 1 scan). Trios4 (3Shape) scans generated a second reference dataset (IOS; n = 10 scans). Using scans, crown dies were produced with two different 3D printers (MAX UV385 [Asiga] and NextDent 5100 [3DSystems]; n = 10 per system). Stone dies were created from conventional impressions (n = 10). Specimens were digitized with a laboratory scanner (E4, 3Shape). Trueness was evaluated with Geomagic Control X (3DSystems). Data analysis was done using Shapiro-Wilk, Levene, ANOVA, and t tests (α < .05). Results: All crown dies fell within the clinically acceptable trueness range (150 µm). IOS exhibited significantly lower (P < .05; Δ ≤ 21.7 μm) or similar trueness compared to stone models. Asiga dies demonstrated similar and NextDent significantly lower marginal trueness than IOS (P < .05; Δ ≤ 57.3 μm). Most AM margin areas had significantly lower trueness than stone (P < .001; Δ ≤ 57.2 μm). Asiga outperformed NextDent (P < .001). Shoulder trueness surpassed chamfer in optical scans (P = .01). Finish line design and gingiva location did not have a significant impact on AM and stone models (P > .05). Conclusions: Combining IOS and AM achieves clinically acceptable crown die trueness for single molar teeth. The choice of AM device is critical, with Asiga outperforming NextDent. Finish-line design has an impact on optical scans. Finish-line design and marginal gingiva location have little effect on AM trueness.

Section: Discussionmentioning

confidence: 99%

“…34,35 Moreover, many current studies examining the accuracy of digital workflows lack a control group of stone models. [36][37][38][39] The incorporation of a stone control group is crucial to thoroughly assess the clinical applicability and reliability of digital techniques in restorative dentistry.…”

mentioning

confidence: 99%

Trueness of Crown Preparation Dies in Dental Models: An In Vitro Assessment of Digital and Analog Workflows

Auskalnis,

Akulauskas,

Jegelevicius

et al. 2024

“…A DLP-based 3D printer (MAX UV, Asiga) was used to fabricate all casts with a layer thickness of 100 µm. 4,8 After fabrication, DM casts were ultrasonically cleaned in 98% isopropyl alcohol for 10 minutes (5 minutes of prewash and 5 minutes of postwash). 4 GP casts were ultrasonically cleaned in 96% ethanol for 5 minutes.…”

Section: Methodsmentioning

confidence: 99%

“…4,8 After fabrication, DM casts were ultrasonically cleaned in 98% isopropyl alcohol for 10 minutes (5 minutes of prewash and 5 minutes of postwash). 4 GP casts were ultrasonically cleaned in 96% ethanol for 5 minutes. 29 Thereafter, all casts were left to dry.…”

Section: Methodsmentioning

confidence: 99%

Dimensional Stability of Additively Manufactured Diagnostic Maxillary Casts Fabricated with Different Model Resins

Dönmez,

Wepfer,

Güven

et al. 2024

To evaluate the effect of model resin type and time interval on the dimensional stability of additively manufactured diagnostic casts. Materials and Methods: Ten irreversible hydrocolloid impressions and 10 impressions from an intraoral scanner were made from a reference maxillary stone cast, which was also digitized with a laboratory scanner. Conventional impressions were poured in type III stone (SC), while digital impressions were used to additively manufacture casts with a nanographene-reinforced model resin (GP) or a model resin (DM). All casts were digitized with the same laboratory scanner 1 day (T0), 1 week (T1), 2 weeks (T2), 3 weeks (T3), and 4 weeks (T4) after fabrication. Cast scans were superimposed over the reference cast scan to evaluate dimensional stability. Data were analyzed with Bonferroni-corrected repeated measures ANOVA (α = .05). Results: The interaction between the main factors (material type and time interval) affected anterior teeth deviations, while the individual main factors affected anterior teeth and entire-cast deviations (P ≤ .008). Within anterior teeth, DM had the lowest deviations at T3, and GP mostly had lower values at T2 and lower deviations at T3 than at T0 (P ≤ .041). SC had the highest pooled anterior teeth deviations, and GP had the highest pooled entire cast deviations (P < .001). T3 had lower pooled anterior teeth deviations than at T0, T1, and T4, and higher pooled entire cast deviations than T1 were demonstrated (P ≤ .027). Conclusions: The trueness of nanographene-reinforced casts was either similar to or higher than that of other casts. Dimensional changes were acceptable during the course of 1 month.

“…As mentioned before, 3D printing and milling can achieve a high degree of finish and detail reproduction 39 but with increased production times and costs. To overcome this problem, it is possible to request an alveolar model-A model where the base is produced with one technology and the removable dies are either produced with the same technology at a different resolution or with a different technology.…”

Section: Alveolar Modelsmentioning

confidence: 99%

Working Models in the Digital Workflow: Are They Reliable?

Appiani,

Scattarelli,

Ori

et al. 2024

This position paper summarizes all relevant aspects of the use of working models derived from digital data in digital and hybrid workflows, aiming to (1) provide the reader with a comprehensive review of the types of models that currently can be produced from a digital file created by an intraoral scanner (IOS); ( 2) critically analyze issues that may undermine or compromise their reliability when requested for the fabrication of both tooth-borne and implant-supported fixed dental prostheses (FDPs); and (3) indicate the procedures to be implemented in order to overcome these issues and produce satisfactory restorations. Materials and Methods: By way of a thorough literature review, the authors highlight the critical issues of milled and 3D-printed models, solid and alveolar, explaining the differences in terms of accuracy and reliability. Results and Conclusions: By describing the peculiarities of models with prepared natural teeth and those incorporating metal implant analogs, the clinical indications for their use are given while proposing the strategies that can be adopted to avoid errors during fabrication or to overcome inaccuracies.