Predictability of Orthodontic Tooth Movement With Invisalign Aligners

Summary

Together with the increased adult patient demand for orthodontic treatment and the push toward increasingly personalized treatment, technology developments have resulted in a growing worldwide demand for clear aligners, to the point that they are now an essential part of any orthodontic practice.

Despite the widespread use of the technique, the existing literature about reliability of orthodontic tooth movement with Invisalign aligners seems not encouraging. Several papers have demonstrated that what is virtually planned is not what is clinically achievable. However, it should be considered that clear aligner orthodontics techniques are customized not only for the patients but for orthodontists too. Therefore, virtual treatment plan design, in terms of attachments' design and placement, orthodontic tooth movement (OTM) staging and aligner deformation overengineering, or in other words aligners biomechanics knowledge, plays a crucial role in defining the quality of the orthodontic treatment with Invisalign aligners.

Based on these considerations the present study was designed to answer two research-clinical questions: 1) which are the less predictable orthodontic movements with Invisalign aligners when the treatment plan is designed by expert operators? and 2) which is the impact of the orthodontist experience, in terms of patient motivation, on the predictability of orthodontic tooth movement with Invisalign aligners? To answer those questions, the predictability of OTM in a sample of Invisalign patients treated by expert operators was compared with the predictability of OTM in a sample treated by post-graduate students.

The null hypothesis for question 1 is that all the prescribed orthodontic tooth movements are predictable, while the null hypothesis for question 2 is that the reliability of orthodontic tooth movement is not affected by operator experience.

98 patients (31 M, 67 F; mean age 28 ± 12 years) were selected among those in treatment at the Department of Orthodontics of the University of Turin, which is the coordinating center, and at 5 private orthodontics offices across Italy. The inclusion criteria for practitioners were as follows: orthodontist with huge and renewed experience in Invisalign treatments; has the ability to scan plaster model or to collect intraoral scans and upload (via internet) the files obtained to a central repository; affirms that the practice can devote sufficient time in patient scheduling to allow focused recording of all data required for the study; and does not anticipate retiring, selling the practice, or moving during the study. Signed, written informed consent was required before inclusion in the trial.

All participants included in this prospective observational study had Class I or mild Class II malocclusion with mild to moderate crowding or spacing in the maxillary and mandibular dental arches (nonextraction cases). Interproximal enamel reduction was performed as prescribed in each patient's virtual treatment plan.

The average treatment time was 10 ± 5 months. The sample considered a total of 2716 teeth that were analyzed overlapping the real post-treatment .stl file obtained with the final intra-oral scan to the planned post-treatment .stl file obtained exporting the final stage of the virtual setup.

Every virtual treatment plan was designed by orthodontists with a huge and renewed experience in Invisalign treatments. While in the private practices the treatment was directly conducted by 5 expert orthodontist (mean age 45.6 ± 8.2) who controlled the patient at every appointment, in the University setting the treatment was conducted by 5 post-graduate students at the last year of their program (mean age 26.4± 1.4). Control appointments were fixed at 6 weeks interval in both the University and the private settings.

Posttreatment digital models and final virtual treatment plan models were exported from ClinCheck® software as stereolithography files and subsequently imported into Geomagic Qualify software (3D Systems(r), Rock Hill, South Carolina, USA), in order to compare individual tooth positions between digital models of each patient. The dental arches were superimposed using the landmark-based method and the surface-based method (Best Fit Alignment). So that the differences between the tooth positions could be calculated, 3 reference planes were identified on the virtual treatment plan model. Differences between the actual treatment outcome and the predicted outcome were calculated and tested for statistical significance for each tooth in the mesial-distal, vestibular-lingual, and occlusal-gingival directions, as well as for angulation, inclination, and rotation. Differences greater than 0.5 mm for linear measurements and 2° for angular measurements were considered clinically significant. In addition, the statistical significance of categorical variables was tested for each previously calculated difference in tooth movement.

Conditions

• Tooth Crowding
• Malocclusion
• Malocclusion, Angle Class II
• Malocclusion, Class I/II

Interventions

DEVICE

Aligner

A method of straightening teeth without fixed braces

Sponsors & Collaborators

• University of Turin, Italy

  lead OTHER

Principal Investigators

• Tommaso Castroflorio, DDS, PhD · Department of Orthodontics of the University of Turin

Eligibility

Min Age

11 Years

Max Age

77 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2019-10-12

Primary Completion

2021-12-21

Completion

2022-01-31

Countries

• Italy

Study Locations