Abstract
BACKGROUND: To assess the trueness of trial restorations fabricated using the two-step mock-up methods with varying distributions of hard tissue stop areas in the complete-arch mock-up process and to compare these outcomes with the one-step method. METHODS: Complete-arch digital diagnostic waxings were designed on a worn maxillary cast. The original waxings were modified into four intermediate versions, each retaining a different set of original worn teeth: bilateral molars, molars and incisors, lateral incisors along with canines and molars, or alternating teeth. One complete-arch waxing cast, four intermediate waxing casts and 25 original worn casts were 3D printed, and silicone indices were prepared. Trial restorations were made by injecting bis-acrylic resin into the silicone indices and curing under pressure. Five groups were formed, one-step (Group 1) and four two-step methods (Groups 2-5). Root mean square (RMS) was applied for 3D analysis (global and tooth levels). Point-to-point measurements were used for 2D occlusal surfaces. One-way ANOVA with post-hoc tests was performed to assess intergroup differences. RESULTS: Significant differences in overall trueness were found among the five groups (F (4,20) = 92.61, P < 0.001). Group 1 (one-step) showed the largest mean RMS deviation (0.31 ± 0.02 mm) while Group 5 (alternating teeth) had the smallest (0.15 ± 0.01 mm), not significantly different from Group 4 (0.17 ± 0.01 mm). Tooth-level 3D analyses revealed a similar pattern, with the largest deviations observed at premolars (0.34 ± 0.07 mm) and canines (0.60 ± 0.09 mm) in Group 1, both significantly greater than Groups 4 and 5 (< 0.17 mm, all P < 0.001). Occlusal surface 2D analyses showed statistically significant differences among groups (all P < 0.001), with Group 1 reaching 0.58 ± 0.12 mm at premolars compared with 0.16 ± 0.09 mm in Group 5. CONCLUSIONS: The two-step methods enhance the trueness of complete-arch trial restorations compared to the one-step method, with increased supporting teeth reducing overall deviations.