Predictability of maxillary dentoalveolar expansion with clear aligners in patients with mixed dentition.

OBJECTIVE

This prospective study evaluated the effectiveness of clear aligner treatment (CAT) in achieving dentoalveolar upper arch expansion in patients with mixed dentition and transverse maxillary deficiency.

METHODS

Forty patients with mixed dentition and a transverse discrepancy of ≤ 5 mm were treated using clear aligners. Pre- and post-treatment digital dental models were measured using specific landmarks and compared with the programmed expansion in the virtual treatment plan. Statistical analyses included the inter-class correlation coefficient to evaluate inter-rater reliability. A paired t test was employed to compare pre- and post-treatment values and to examine the significance of the changes. Multiple regression analysis was conducted to estimate the relationship between the prescribed and observed measurements, stratified by inter-dental measurements (deciduous canines, first deciduous molars, and permanent molars, at cusp and gingival levels).

RESULTS

Excellent measurement reproducibility was observed. The accuracy of dentoalveolar maxillary arch expansion varied among different tooth regions. The inter-canine accuracy was 87.7% at the cusp level and 82.7% at the gingival level. The inter-first deciduous molars exhibited accuracies of 84.9% (cusp level) and 80.5% (gingival level). The inter-first molars showed accuracies of 77.8% (cusp level) and 67.9% (gingival level). Significant differences were observed between the planned and obtained measurements for specific tooth regions.

CONCLUSIONS

CAT demonstrated reliable predictability in achieving dentoalveolar expansion of the maxillary arch in patients with mixed dentition. A higher accuracy was observed in the anterior region than in the posterior region. These findings suggest that CAT could be an effective option for treating transverse maxillary deficiencies in patients with mixed dentition with moderate inter-arch transverse discrepancies, considering tooth-specific predictability differences.