Three-dimensional accuracy of in-office aligner therapy: a retrospective comparison between planned and achieved tooth positions.

OBJECTIVES

To evaluate the three-dimensional clinical predictability of an in-office aligner workflow by comparing digitally planned virtual setups (T1) with post-treatment dental models (T2) using a reproducible open-source protocol.

METHODS

Sixty-eight digital dental models (maxillary and mandibular arches) from adult patients treated with in-office aligners were retrospectively analyzed. T1 and T2 STL models were superimposed using a landmark-based three-dimensional protocol, and linear and angular discrepancies were quantified using freely available Slicer CMF software (version 4.11). Statistical analyses were conducted at a 5% significance level, including intraexaminer reliability assessment after a 15-day interval and Wilcoxon signed-rank test for paired comparisons. Clinically relevant thresholds were defined as linear displacements >0.5 mm and angular deviations >2°

RESULTS

Planned and achieved tooth positions showed high three-dimensional agreement. No statistically significant differences were detected for any linear or angular variables (p > 0.05), and all observed deviations remained below predefined clinical relevance thresholds. Incisal edge positions, intercanine widths, and intermolar widths exhibited minimal discrepancies between T1 and T2.

CONCLUSIONS

Virtual setups for in-office aligner therapy demonstrated high three-dimensional accuracy, with no clinically meaningful differences between planned and achieved tooth positions. These findings support the clinical predictability of digitally planned, in-office aligners.

CLINICAL RELEVANCE: In-office aligner systems provide clinicians with full control over digital planning and fabrication. Their demonstrated predictability supports reliable treatment, reduces the need for refinements, and improves clinical efficiency. Moreover, three-dimensional superimposition may serve as an objective, open-access tool for auditing treatment outcomes and refining digital planning strategies in daily clinical practice.