MATERIALS AND METHODS: An auricular prosthesis, a complete denture, and anterior and posterior crowns were constructed using conventional methods and laser scanned to create computerized 3D meshes. The meshes were optimized independently by four computer-aided design software (Meshmixer, Meshlab, Blender, and SculptGL) to 100%, 90%, 75%, 50%, and 25% levels of original file size. Upon optimization, the following parameters were virtually evaluated and compared; mesh vertices, file size, mesh surface area (SA), mesh volume (V), interpoint discrepancies (geometric similarity based on virtual point overlapping), and spatial similarity (volumetric similarity based on shape overlapping). The influence of software and optimization on surface area and volume of each prosthesis was evaluated independently using multiple linear regression.
RESULTS: There were clear observable differences in vertices, file size, surface area, and volume. The choice of software significantly influenced the overall virtual parameters of auricular prosthesis [SA: F(4,15) = 12.93, R2 = 0.67, p < 0.001. V: F(4,15) = 9.33, R2 = 0.64, p < 0.001] and complete denture [SA: F(4,15) = 10.81, R2 = 0.67, p < 0.001. V: F(4,15) = 3.50, R2 = 0.34, p = 0.030] across optimization levels. Interpoint discrepancies were however limited to <0.1mm and volumetric similarity was >97%.
CONCLUSION: Open-source mesh optimization of smaller dental prostheses in this study produced minimal loss of geometric and volumetric details. SculptGL models were most influenced by the amount of optimization performed.
PURPOSE: The purpose of this virtual analysis study was to compare the accuracy and precision of 3-dimensional (3D) ear models generated by scanning gypsum casts with a smartphone camera and a desktop laser scanner.
MATERIAL AND METHODS: Six ear casts were fabricated from green dental gypsum and scanned with a laser scanner. The resultant 3D models were exported as standard tessellation language (STL) files. A stereophotogrammetry system was fabricated by using a motorized turntable and an automated microcontroller photograph capturing interface. A total of 48 images were captured from 2 angles on the arc (20 degrees and 40 degrees from the base of the turntable) with an image overlap of 15 degrees, controlled by a stepper motor. Ear 1 was placed on the turntable and captured 5 times with smartphone 1 and tested for precision. Then, ears 1 to 6 were scanned once with a laser scanner and with smartphones 1 and 2. The images were converted into 3D casts and compared for accuracy against their laser scanned counterparts for surface area, volume, interpoint mismatches, and spatial overlap. Acceptability thresholds were set at <0.5 mm for interpoint mismatches and >0.70 for spatial overlap.
RESULTS: The test for smartphone precision in comparison with that of the laser scanner showed a difference in surface area of 774.22 ±295.27 mm2 (6.9% less area) and in volume of 4228.60 ±2276.89 mm3 (13.4% more volume). Both acceptability thresholds were also met. The test for accuracy among smartphones 1, 2, and the laser scanner showed no statistically significant differences (P>.05) in all 4 parameters among the groups while also meeting both acceptability thresholds.
CONCLUSIONS: Smartphone cameras used to capture 48 overlapping gypsum cast ear images in a controlled environment generated 3D models parametrically similar to those produced by standard laser scanners.
OBJECTIVES: The objectives of this study were to evaluate the degradation effects of each dietary solvent on the microhardness of the different CAD/CAM dental composites and to observe the degradation effects of dietary solvent on the inorganic elements of the dental composites investigated.
METHODS: Fifty specimens with dimensions 12 mm x 14 mm x 1.5 mm were prepared for direct composite (Filtek Z350 XT [FZ]), indirect composite (Shofu Ceramage [CM]), and three CAD/CAM composites (Lava Ultimate [LU], Cerasmart [CS], and Vita Enamic [VE]). The specimens were randomly divided into 5 groups (n = 10) and conditioned for 1-week at 37°C in the following: air (control), distilled water, 0.02 N citric acid, 0.02 N lactic acid and 50% ethanol-water solution. Subsequently, the specimens were subjected to microhardness test (KHN) using Knoop hardness indenter. Air (control) and representative postconditioning specimens with the lowest mean KHN value for each material were analyzed using energy dispersive X-ray spectroscopy (EDX). Statistical analysis was done using one-way ANOVA and post hoc Bonferroni test at a significance level of p = 0.05.
RESULTS: Mean KHN values ranged from 39.7 ± 2.7 kg/mm2 for FZ conditioned in 50% ethanol-water solution to 79.2 ± 3.4 kg/mm2 for VE conditioned in air (control). With exception to LU, significant differences were observed between materials and dietary solvents for other dental composites investigated. EDX showed stable peaks of the inorganic elements between air (control) and representative postconditioning specimens.
CONCLUSIONS: The microhardness of dental composites was significantly affected by dietary solvents, except for one CAD/CAM composite [LU]. However, no changes were observed in the inorganic elemental composition of dental composites between air (control) and 1-week postconditioning.
Materials and Methods: The present systematic review was carried out according to PRISMA guidelines. The search was carried out on PubMed/MEDLINE, Cochrane collaboration, Science direct, and Scopus scientific engines using selected MeSH keywords. The articles fulfilling the predefined selection criteria based on the fit and accuracy of removable partial denture (RPD) frameworks constructed from digital workflow (CAD/CAM; rapid prototyping) and conventional techniques were included.
Results: Nine full-text articles comprising 6 in vitro and 3 in vivo studies were included in this review. The digital RPDs were fabricated in all articles by CAD/CAM selective laser sintering and selective laser melting techniques. The articles that have used CAD/CAM and rapid prototyping technique demonstrated better fit and accuracy as compared to the RPDs fabricated through conventional techniques. The least gaps between the framework and cast (41.677 ± 15.546 μm) were found in RPDs constructed through digital CAD/CAM systems.
Conclusion: A better accuracy was achieved using CAD/CAM and rapid prototyping techniques. The RPD frameworks fabricated by CAD/CAM and rapid prototyping techniques had clinically acceptable fit, superior precision, and better accuracy than conventionally fabricated RPD frameworks.