Dimensional Accuracy, Surface, Optical, and Mechanical Performance of 3D-Printed Dental Surgical Guides and Occlusal Splints

Abstract

Objectives: This in vitro study aimed to evaluate the effect of different additive manufacturing systems and material combinations on the performance of 3D-printed dental devices, including surgical guides and occlusal splints. Specifically, this study investigated dimensional accuracy, mechanical properties, surface characteristics, optical properties, and the effect of thermocycling on selected mechanical outcomes. Materials and Methods: Five 3D printing systems—Asiga Max UV, Carbon M2, SprintRay Pro S, Stratasys Origin One, and Stratasys J5 DentaJet—were evaluated using corresponding dental resins for surgical guides and occlusal splints. Specimens (n = 3 per group for accuracy tests; n = 10 for most mechanical and surface tests) were fabricated and analyzed. Dimensional accuracy was assessed using intaglio surface trueness (RMS deviation and in-tolerance percentages at the tolerance of ±30 µm, ±50 µm, and ±100 µm), implant access deviation (linear, angular, and diameter), and wall thickness measurements. Mechanical properties were evaluated using flexural strength, tensile strength, fracture toughness, Vickers microhardness, and creep testing. Surface roughness (Ra) was measured before and after polishing, and gloss and optical properties (color measurements and total transmission) were assessed for soft splint materials. Thermocycling (5,000 cycles between 5°C and 55°C) was performed to simulate aging. Statistical analyses were conducted using one-way and two-way ANOVA with Tukey HSD and Student’s t-tests (α = 0.05). Results: Dimensional accuracy was significantly influenced by printer system (p < 0.05). For surgical guides, Stratasys J5 DentaJet and Asiga Max UV demonstrated the highest in-tolerance values and lowest RMS deviations, whereas SprintRay Pro S showed lower accuracy across all thresholds. However, RMS deviation values remained low across all groups. Hard occlusal splints showed no statistically significant differences in trueness among the evaluated printer systems (p > 0.05), while soft splints exhibited significant differences in in-tolerance values (p < 0.05) despite similar RMS deviations. Implant access (linear, angular, and diameter) and wall thickness measurements also differed significantly among systems (p < 0.05). Mechanical properties were significantly affected by material–printer combinations (p < 0.05), with variability in flexural strength, fracture toughness, microhardness, and creep behavior across groups. Surface roughness (Ra) decreased significantly after polishing (p < 0.001), while gloss varied among materials. Optical properties of soft splints showed significant differences in color (L*, a*, b*) and total transmission among printer systems (p < 0.05). Thermocycling treatment significantly reduced mechanical properties (p < 0.05), including tensile strength in all groups and flexural strength in hard splints. Shore hardness of soft splints showed variable responses, with more pronounced degradation observed in certain groups, particularly SprintRay Pro S. Conclusion: The performance of 3D-printed dental devices is significantly influenced by the interaction between printer system and material type. Although no single system demonstrated superior performance across all evaluated properties, specific combinations achieved optimal outcomes for accuracy, mechanical behavior, and esthetic performance. These findings emphasize the importance of appropriate material–printer selection and optimized processing protocols to ensure clinically acceptable results.