Mehmet Gözen, Ceyda Akın
Digital scan trueness is significantly influenced by preparation geometry and margin location. Rounded shoulder designs and supragingival margins provide more reliable digital outcomes. Careful selection of finish line configuration and scanner technology is critical for optimizing marginal accuracy in digital restorative workflows.
PURPOSE: To evaluate the influence of margin level and finish line geometry on the trueness of digital impressions obtained with different intraoral scanners (IOS).
MATERIALS AND METHODS: Six maxillary molar crown preparations were designed combining two margin levels (supragingival and subgingival) and three finish line designs (shoulder, chamfer, rounded shoulder). Models were fabricated using high-resolution three-dimensional printing. Each model was scanned 12 times with four IOS systems (Medit i700, Primescan, Trios 3, and Trios 5), generating 288 datasets. Reference scans were obtained using a laboratory scanner. Trueness was quantified using root mean square (RMS) deviation in accordance with ISO 5725-1. Data were analyzed using Robust analysis of variance and Bonferroni-adjusted post hoc tests (α = .05).
RESULTS: Scanner type, finish line design, and margin level significantly affected trueness (P < .05). Rounded shoulder preparations demonstrated the lowest RMS values, whereas shoulder designs showed the highest deviations, particularly at the subgingival level. Supragingival margins exhibited significantly higher trueness than subgingival margins. Among scanners, Medit i700 and Primescan showed superior performance compared with Trios 3 and Trios 5. Margin-specific RMS values were consistently higher than total surface values.
CONCLUSION: Digital scan trueness is significantly influenced by preparation geometry and margin location. Rounded shoulder designs and supragingival margins provide more reliable digital outcomes. Careful selection of finish line configuration and scanner technology is critical for optimizing marginal accuracy in digital restorative workflows.