Effect of 3D superimposition software on intraoral scanner accuracy and monitoring outcome.

OBJECTIVES: To determine whether 3D superimposition software ("Apps") systematically affects 3D deviation outcomes derived from intraoral scanner (IOS) data, using two quantile‑range accuracy metrics (Q90_Q10_half and Q95_Q05_half). MATERIALS AND METHODS: Two jaw‑sized reference models were digitized with a high‑resolution optical scanner (ATOS III) to generate reference STL meshes (REF_STL). Five IOS devices acquired ten scans per device and per jaw model, exported as STL meshes (IMP_STL): Emerald Green, iTero 5D, Medit i900, Primescan, and Trios 5. Each IMP_STL was trimmed (1 mm above gingival line) and superimposed to REF_STL in four Apps: commercial industrial software: Geomagic Control X and GOM Inspect, and open dentistry-focused software Medit Design (Compare) and Dentexion; resulting in total to N = 400 superimpositions. For each superimposition, Q90_Q10_half and Q95_Q05_half values were computed from point-wise signed surface distances. A linear mixed‑effects model tested factor App as fixed effect with random intercepts for factors Device and Jaw, followed by Bonferroni‑adjusted pairwise comparisons (α = 0.05). RESULTS: App significantly influenced Q90_Q10_half (p < 0.01) and Q95_Q05_half (p < 0.001). Control X yielded higher adjusted means than Dentexion and Compare for Q90_Q10_half (both p < 0.01), while Dentexion, GOM, and Compare did not differ. For Q95_Q05_half, Control X exceeded all other Apps (all p < 0.01). Notably, IOS rankings were stable across Apps, indicating that software altered magnitude but not relative ordering. CONCLUSIONS: Evaluation software is a significant source of variability in 3D deviation metrics; Control X produced consistently higher (more conservative) quantile‑range values, particularly for Q95_Q05_half. CLINICAL RELEVANCE: Inter‑study comparisons in digital accuracy research should report the evaluation software and settings. Dentistry‑focused Apps (e.g., with automated tooth segmentation) may reduce operator‑dependent effects and facilitate clinically applicable monitoring.