Comparative Analysis of Alignment Accuracy in Dental CAD Software for Morphologically Altered Digital Models

PURPOSE: To evaluate the trueness and precision of alignment protocols across three dental CAD platforms for spatially aligning virtually altered digital dental models to their original position. MATERIALS AND METHODS: A digital cast of the lower dentition served as the basis for generating a digital model, which was morphologically altered through base trimming, virtual extractions, crown modifications, orthodontic tooth movements, surface adjustments, and mesh density reduction. The altered model was then displaced and aligned to the original cast using five alignment protocols across three software platforms: BlueSky Plan (landmark-based), Exocad (landmark-based and landmark-based with best-fit optimization), and Blender for Dental (B4D) (landmark-based with generalized ICP and reference-based with localized ICP). Each protocol was repeated ten times. Alignment accuracy was quantified against the reference standard using root mean square (RMS) error, average and maximum absolute 3D deviation, and linear landmark deviation. Data were analyzed using descriptive statistics, coefficient of variation (CV%), and Welch's ANOVA with Games-Howell post hoc tests (α = 0.05). RESULTS: Alignment accuracy differed significantly between methods (P<.001). Exocad's landmark-based with best-fit optimization achieved 12 μm RMS error (CV: 1.17%). B4D's reference-based with localized ICP achieved 47 μm (CV: 14.82%). Landmark-based methods performed poorly: BlueSky 250 μm, Exocad 160 μm, and B4D with generalized ICP 152 μm, with high variability (CV: 20.1-25.3%). CONCLUSION: Alignment method selection critically affects accuracy when processing altered dental digital models. Landmark-based alignment combined with optimized best-fit algorithms and reference-based alignment with localized ICP achieved clinically acceptable accuracy, while landmark-based methods alone produced unacceptable errors unsuitable for precision digital workflows.