Effect of different digital technology on the adaptation and retention of Co‐Cr partial denture frameworks

Purpose To evaluate the overall adaptation and retention of class I cobalt‐chromium (Co‐Cr) removable partial denture (RPD) frameworks using three different computer‐aided design and computer‐aided manufacturing (CAD‐CAM) technologies: Indirect wax milling with lost wax technique (LWT), direct milling, and selective laser melting (SLM) technique. Materials and Methods An educational maxillary stone model (Kennedy class I) was scanned after preparing rest seats to create a resin model. The resin model was scanned, and the RPD framework was digitally designed and saved as a standard tessellation language (STL) file. Twenty‐four Co‐Cr RPD frameworks were then constructed and divided into three groups (n = 8) based on fabrication technique: Group A (indirect wax milling with LWT), Group B (direct milling), and Group C (selective laser melting). In Group A, the STL file was used to mill the design from castable resin blanks which were then cast by the LWT. In Group B, the STL file was used to mill the design from the Co‐Cr blank directly. Finally in Group C, the STL file was used to print the design from Co‐Cr powder using SLM 3D printed technique. Geomagic Control X software was used to measure the overall adaptation of the fabricated RPD frameworks, Retention was also tested using a universal testing machine. One‐way Analysis of Variance (ANOVA) test was used to compare the three groups then the Tukey HSD post‐hoc test was used for pair‐wise comparisons. The significance level was set at p ≤ 0.05. Results Regarding the overall adaptation, Group B (0.71 ± 0.02 mm) showed significantly higher adaptation than Group A (0.96 ± 0.06 mm) and Group C (1.05 ± 0.16 mm). Regarding retention, Group B (2.03 ± 0.34 N) showed significantly higher retention than Group A (1.00 ± 0.13 N) and Group C (0.78 ±0.17 N). Conclusion Based on the findings of this in vitro study, Co‐Cr RPD frameworks fabricated by direct milling technique revealed the best adaptation and retention.