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Author Spotlight: 3D Movement Assessment of Maxillary Posterior Teeth in Clear Aligner Treatment
Published on: February 23, 2024
Maxillary impacted canines: Statistical modeling of traction duration and resorption
Laura Brands1,2, Jean-Baptiste Kerbrat1,2, Thomas Schouman1,2
1Hôpital Pitié-Salpêtrière, Service de Stomatologie et Chirurgie maxillo-faciale, 47-83 boulevard de l’Hôpital, 75651 Paris cedex 13, France
Introduction:
Maxillary canines are needful to achieving both functional and aesthetic occlusion. Their impaction affects approximately 0.92% of the general population.
Objective:
This study aims to identify etiological factors associated with maxillary canine impaction, and to develop predictive models for traction duration and the risk of resorption.
Materials And Methods:
A retrospective cohort study was conducted on 50 patients (68 impacted maxillary canines). The diagnosis was based on comprehensive clinical examination, including intraoral and extraoral evaluation, panoramic radiographs, lateral cephalograms, and cone-beam computed tomography (CBCT).
Results:
Palatal canines are more frequently impacted than vestibular canines, and require a longer traction duration. Etiological factors differed between vestibular and palatal canines. A general predictive model for traction duration was developed with 91% accuracy, incorporating the horizontal position of the canine, follicle size, vertical height, and apex location. Distinct predictive models were generated with high accuracy for both vestibular and palatal canine impactions. Among external factors, the use of a palatal expander was associated with longer traction durations, likely due to greater case complexity, whereas prior extraction of the deciduous canine shortened the traction time, particularly for palatal cases. Risk factors for resorption included agenesis (excluding lateral incisors), the presence of lateral incisor microdontia, and the position of the canine apex. A predictive model for resorption was developed with 76% accuracy.
Conclusion:
Early detection and imaging-based assessment are essential for optimizing the management of impacted canines. The predictive models developed in this study may assist clinicians in forecasting traction duration and resorption risk, and may serve as a foundation for future diagnostic software to guide orthodontic treatment planning.

