Objective: The purpose of this study was to assess the accuracy of full coverage crowns produced by two manufacturing methods: additive 3D printing and subtractive milling utilizing three different predefined cement spaces.
Materials and Methods: Six groups were allocated based on the manufacturing method and the predefined cement space: printed wax with a 20 µm space (PW1); printed wax with a 50 µm space (PW2); printed wax with a 100 µm space (PW3); milled wax with a 20 µm cement space (MW1); milled wax with a 50 µm cement space (MW2); milled wax with a 100 µm cement space (MW3); milled zirconia coping with a 20 µm cement space (MZ1); milled zirconia coping with a 50 µm cement space (MZ2); milled zirconia with a 100 µm cement space (MZ3). All fabricated specimens were scanned using an Identica Blue 3D scanner and saved as standard tessellation language (STL) files. A triple scan method was performed using 3-matic software to assess accuracy. The discrepancy values were recorded in micrometers, and the analysis was conducted using one-way ANOVA.
Results: The wax printing method, with a cement gap design of 100 μm, demonstrated a significant improvement in the accuracy compared to the other methods (P<.01). In contrast, the zirconia milling method exhibited significantly lower accuracy relative to the other techniques (P<0.01). Moreover, different cement spaces resulted in various accuracy levels but the only statistically significant difference was observed for the 100 µm cement space in the printed wax group.
Conclusion: The additive 3D printing method exhibited greater accuracy than the subtractive milling approach. Furthermore, altering the cement gap was found to impact the accuracy of both techniques, albeit without statistical significance.
Clinical Significance: The accuracy of each CAM technique was investigated in this study, highlighting the promising accuracy of 3D-printed patterns for the lost-wax technique over direct crown milling. However, all methods produced reliable and accurate crown restorations.