Alignment methods to improve the trueness of digital mandibular models: A clinical study

Objective: This study aimed to investigate how different alignment strategies influence the trueness of digital mandibular model superimpositions obtained from intraoral scans at different time points. Methods: A clinical study was conducted with 15 participants, each underwent intraoral scanning at three time points (T0, T1, and T2). Five alignment methods were tested in metrology software: full-arch alignment; bilateral first molars and canines; teeth including 1 mm of gingiva; partial alignment (first molar to canine); and full-arch excluding gingiva. Superimposition trueness was quantified using root mean square error (RMS) values, and data were analyzed using Kruskal-Wallis and Mann-Whitney U tests (α = 0.05). Results: Full-arch excluding gingiva and teeth including 1 mm gingiva presented the lowest RMS (0.132 mm and 0.134 mm, respectively), each approximately 0.037 mm lower than the partial alignment (first molar to canine) (0.167 mm). However, the partial alignment segment provided superior local trueness (specific-area RMS: 0.073 mm; ratio 0.43, p < 0.001), while teeth including 1 mm gingiva exhibited strong consistency between total and specific-area trueness (ratio 0.85; p = 0.44). No statistically significant differences were observed in total area RMS among all methods (p = 0.532). Conclusion: Alignment methods that exclude gingival tissue or include minimal adjacent gingiva improve the trueness and consistency of digital model superimpositions. Although partial alignments enhanced localized trueness, they may increase greater variability in full-arch superimpositions. Alignment strategy should be selected according to the clinical and research objective. Clinical significance: Trueness of digital superimpositions is shaped by gingival inclusion and alignment region. Careful optimization ensures more reliable longitudinal monitoring.