Open Access

Predictability of orthodontic movement with orthodontic aligners: a retrospective study

Progress in Orthodontics201718:35

https://doi.org/10.1186/s40510-017-0190-0

Received: 9 August 2017

Accepted: 18 September 2017

Published: 13 November 2017

Abstract

Background

The aim of this study was to evaluate the predictability of F22 aligners (Sweden & Martina, Due Carrare, Italy) in guiding teeth into the positions planned using digital orthodontic setup.

Methods

Sixteen adult patients (6 males and 10 females, mean age 28 years 7 months) were selected, and a total of 345 teeth were analysed. Pre-treatment, ideal post-treatment—as planned on digital setup—and real post-treatment models were analysed using VAM software (Vectra, Canfield Scientific, Fairfield, NJ, USA). Prescribed and real rotation, mesiodistal tip and vestibulolingual tip were calculated for each tooth and, subsequently, analysed by tooth type (right and left upper and lower incisors, canines, premolars and molars) to identify the mean error and accuracy of each type of movement achieved with the aligner with respect to those planned using the setup.

Results

The mean predictability of movements achieved using F22 aligners was 73.6%. Mesiodistal tipping showed the most predictability, at 82.5% with respect to the ideal; this was followed by vestibulolingual tipping (72.9%) and finally rotation (66.8%). In particular, mesiodistal tip on the upper molars and lower premolars were achieved with the most predictability (93.4 and 96.7%, respectively), while rotation on the lower canines was the least efficaciously achieved (54.2%).

Conclusions

Without the use of auxiliaries, orthodontic aligners are unable to achieve programmed movement with 100% predictability. In particular, although tipping movements were efficaciously achieved, especially at the molars and premolars, rotation of the lower canines was an extremely unpredictable movement.

Keywords

F22 alignerOrthodontic movementMovement accuracyPredictability

Background

Since orthodontic aligners were launched on the market, they have been in growing demand among patients, especially adults, thanks to their aesthetic properties and clinical efficacy [1].

Although the idea of using consecutive clear thermoplastic appliances to align the teeth was first introduced by Kesling in 1946 [2], it was not until Align Technology (Santa Clara, CA, USA) launched the Invisalign system in 1998 that such appliances were prescribed on a large scale, thanks to their introduction of CAD/CAM technology into Orthodontics [3]. At first, aligners were marketed as an alternative to traditional fixed appliances in simple malocclusion cases such as slight crowding or minor space closure [4]. Over time, however, the range of malocclusion cases that can be treated by means of invisible aligners has widened. Clinical research has developed aligner-based solutions for even complex cases involving major rotation of the premolars, upper incisor torque, distalisation and/or extractive space closure [5].

That being said, there is as yet no consensus as to the predictability of aligner treatment in such large movements; although the aesthetic impact of aligners has been emphasised [6], few studies have yet been set up to investigate the effective capacity of aligners to achieve complex movements [7]. Indeed, the majority of articles published on aligner orthodontics have been case reports or series, reports on the use of a particular system, and expert opinions [3, 8, 9]. Furthermore, studies have concentrated on the market leader, Invisalign, even though many other competing systems have been developed since Align Technology’s patent expired. These alternative aligner systems differ from Invisalign in terms of construction material [10], production process, margin finishing and STL model precision, but perhaps the most influential difference is the professionals charged with executing treatment planning and setup (IT specialists, dental technicians or professional orthodontists) [11].

As regards treatment outcomes, Align Technology reports that roughly 20–30% of Invisalign patients require mid-course correction or post-alignment finishing in order to achieve the results prescribed on the setup [12]. This figure, however, contrasts with that reported by orthodontists, who indicate that the number of patients who require some unplanned correction or even recourse to fixed orthodontics, is closer to 70–80% [1, 13].

In fact, Kravitz [14] reported that Invisalign aligners had a mean accuracy of 41% in terms of achieving planned outcomes, with the most predictable movement being lingual contraction (47.1%), and the least predictable, extrusion (29.6%). In a systematic review of the literature, Rossini and Castroflorio confirmed that the most problematic movement for Invisalign was extrusion, followed by rotation [15].

However, these authors also emphasised the paucity of reliable literature on the subject, and the aim of this study was therefore to compare planned and achieved tipping and rotation in patients using F22 aligners (Sweden & Martina, Due Carrare, Italy) in order to provide data on their effective clinical predictability.

Methods

Sample selection

Sixteen adult Caucasian patients (6 males and 10 females, of mean age 28 years and 7 months) treated by means of F22 aligners at the University of Ferrara Postgraduate School of Orthodontics Clinic were retrospectively selected. Inclusion and exclusion criteria are reported in Table 1. Treatment staging, i.e. the maximum movement planned for each aligner, had been 2° rotation, 2.5° vestibulolingual and mesiodistal tip, and 0.2-mm linear displacement. No auxiliaries of any kind had been used (intermaxillary elastics, buttons, chains), although the use of F22 system Grip Points (attachments) and anterior and/or posterior stripping was allowed. Patients were instructed to wear their aligners for 22 h per day, excepting mealtimes and oral hygiene procedures. Aligners were replaced every 14 days.
Table 1

Inclusion and exclusion criteria

Inclusion criteria

Exclusion criteria

• Adult subjects > 18 years with permanent dentition

• Complete dentition, or with 4 missing teeth at the most (third molars excluded)

• No supernumerary teeth

• No tooth shape anomalies

• No dental rotation > 35°

• No diastems > 5 mm

• Crowding < 5 mm per arch

• Systemic pathologies

• Ongoing pharmacological treatment able to influence orthodontic movement (e.g. prostaglandin inhibitors, biphosphonates)

• Active periodontal disease

• Treatments requiring extraction space closure

Pre-treatment, ideal post-treatment (according to setup) and real post-treatment digital models of the upper and lower jaws of each patient were analysed. Pre-treatment and post-treatment models were acquired using a Trios intraoral scanner (3Shape, Copenhagen, Denmark), and setups were constructed using Orthoanalyzer software (3Shape, Copenhagen, Denmark).

Measurement of digital models

Digital models pertaining to each patient were analysed in .stl format by a single operator using VAM software (Vectra, Canfield Scientific, Fairfield, NJ, USA). This enabled the identification of anatomical reference points, planes and axes on the digital models, required, in turn, for calculation of the angulation, inclination and vestibular prominence of each tooth, as well as linear and angular measurements, for example, the intra-arch diameters [16]. Measurement was based on a method originally involving the identification of a total of 60 reference points per model (excluding second molars). However, in this case, we also included the second molars in the digital measurements, thereby expanding the number of reference points to 100 per model (Fig. 1).
Fig. 1

Positioning of the 100 reference points per arch (Upper jaw)

Once the 100 reference points had been marked, their three-dimensional coordinates were extrapolated and exported, first into a .txt file, and then onto a dedicated spreadsheet provided with the software. This spreadsheet enabled extrapolation of the mesiodistal and vestibulolingual tip and rotation (Figs. 2, 3, and 4) of each tooth with respect to a 3D Cartesian grid based on the occlusal reference plane, which was obtained by means of the following points: (Fig. 5):
  • Reference points at the mediovestibular cusps of teeth 16 in the maxilla and 46 in the mandible

  • Reference points at the mediovestibular cusps of teeth 26 in the maxilla and 36 in the mandible

  • The centroid of all occlusal points of the FACC (the facial axis of the clinical crown) of teeth 15, 14, 12, 11, 21, 22, 24 and 25 in the maxilla and 35, 34, 32, 31, 41, 42, 44 and 45 in the mandible; canines were excluded from this calculation as their occlusal FACC point is generally outside the occlusal plane identified by the other teeth.

Fig. 2

Vestibulolingual tipping: labiolingual inclination of the FACC with respect to the occlusal plane of reference

Fig. 3

Mesiodistal tipping: mesiodistal inclination of the FACC with respect to the occlusal plane of reference

Fig. 4

Rotation: the angle between the mesiodistal axis of the tooth and plane y

Fig. 5

Occlusal plane of reference

One month after the 96 arches had been analysed, the analysis was repeated on 16 randomly selected digital models (8 upper and 8 lower arches). Dahlberg’s D was calculated in order to quantify the measurement error, and Student’s t test for paired data to identify any systematic error.

Analysis of mean imprecision

The following calculations were made for each type of movement of each tooth in each patient:
  • The absolute value of the prescription, i.e. the difference between ideal post-treatment and pre-treatment measurements, to identify the total programmed movement:

$$ \mid \mathrm{prescription}\mid =\mid \mathrm{ideal}\mathrm{posttreatment}-\mathrm{pretreatment}\mid $$
  • The absolute value of the imprecision, i.e. the difference between ideal and real post-treatment measurements, to identify the difference between the actual post-treatment position of each tooth and the programmed movement:

$$ \mid \mathrm{imprecision}\mid =\mid \mathrm{ideal}\mathrm{posttreatment}-\mathrm{real}\mathrm{posttreatment}\mid $$

Absolute values were used for the prescription and imprecision parameters, as the direction of movement (clockwise vs. anticlockwise rotation, and lingual vs. vestibular or mesial vs. distal for the tip) was not taken into consideration. Prescription and imprecision values were grouped into eight categories (upper and lower incisors, canines, premolars and molars) and according to the three types of movement (mesiodistal tip, vestibulolingual tip and rotation).

The different types of tooth (incisors, canines, premolars and molars) were analysed separately because of the different anatomy of the crown and the root (both in shape and length), which inevitably results in a different response to the application of orthodontic forces, in particular, in the treatment with aligners. In addition, the upper jaw teeth were divided from the mandibular ones, due to the different type and compactness of the bone, which can greatly influence the orthodontic movement.

Movements with a prescription of less than 2° were excluded from the analysis. This sensitivity threshold was determined from the mean intra-operator error pertaining to measurements made using the VAM software, which has been previously published in the study validating the method [16].

Thus a database containing measurements of 345 teeth, subdivided into the following types, was obtained:
  • 57 upper incisors

  • 29 upper canines

  • 53 upper premolars

  • 37 upper molars

  • 64 lower incisors

  • 30 lower canines

  • 52 lower premolars

  • 23 lower molars

The Kolmogorov-Smirnov statistical test was used to determine the non-normal distribution of the mean imprecision, using the median as a measure of central tendency and the interquartile interval as an expression of its distribution. The Kruskal-Wallis H test (p < 0.05) was applied in cases of an imprecision of tooth/movement combination whose mean was different to the others.

Analysis of movement accuracy

The following formula was used to quantify the accuracy of each movement for each tooth type with respect to the prescription:
$$ \mathrm{movement}\mathrm{accuracy}=\frac{\mathrm{realposttreatment}-\mathrm{initial}\mathrm{pretreatment}}{\mathrm{idealposttreatment}-\mathrm{initial}\mathrm{pretreatment}} $$

Thus, an index of the accuracy of each movement was obtained: the closer the value to 1, the more precise the dental movement achieved by the aligner series (100% of the prescription). The mean accuracy index, standard deviation and mean standard error were calculated for each type of movement in each tooth category, and Student’s t test for single samples (p < 0.05) was applied in cases in which the predictability of any type of movement/tooth was significantly different to 1, i.e. significantly lower than 100% of the prescription. Finally, F ANOVA (p < 0.05) and Bonferroni’s post hoc tests were applied if there was a statistically significant difference in the predictability among the different types of tooth movement.

Results

Measurement method analysis confirmed that there were no systematic measurement errors in any of the mesiodistal tip, vestibulolingual tip or rotation values (Table 2). Table 3 shows the absolute values for the mean prescription and mean imprecision of each movement of each tooth, alongside the median, relative interquartile and statistical significance. In the upper arch, the least precise movement in terms of absolute values was incisor rotation (imprecision, 5.0° ± 5.3°), while the most precise movement was vestibulolingual tipping of the canines (imprecision, 2.5° ± 1.5°). In the lower arch, on the other hand, the least precision was recorded for premolar rotation (imprecision, 5.4° ± 5.8°), while the most precise movement was vestibulolingual tipping of the molars (imprecision, 1.3° ± 0.9°). In the upper arch, there was no statistically significant difference in imprecision between the different types of tooth movements, whereas in the lower arch the canines showed a significantly greater error in terms of rotation of the canines (6.9° ± 5.4°) with respect to the incisors (3.4° ± 2.5°) and molars (2.0° ± 1.8°). Likewise, the lower molar rotation imprecision was significantly more precise than the lower incisor rotation.
Table 2

Method analysis

Arch

Parameter

Vestibulolingual tip

Mesiodistal tip

Rotation

 

D Dahlberg

Systematic error p level

D Dahlberg

Systematic error p level

D Dahlberg

Systematic error p level

Upper arch

11

0.300

NS

0.390

NS

0.525

NS

12

0.298

NS

0.979

NS

0.500

NS

13

0.782

NS

0.656

NS

0.957

NS

14

0.437

NS

0.783

NS

1.132

NS

15

0.674

NS

0.814

NS

1.162

NS

16

0.497

NS

0.081

NS

1.290

NS

17

0.686

NS

1.014

NS

0.964

NS

21

0.075

NS

0.274

NS

1.174

NS

22

0.785

NS

0.292

NS

0.788

NS

23

0.753

NS

0.433

NS

1.081

NS

24

0.539

NS

1.159

NS

0.883

NS

25

0.636

NS

0.715

NS

2.135

NS

26

0.579

NS

0.097

NS

1.214

NS

27

0.358

NS

1.254

NS

1.616

NS

Mean

0.528

 

0.639

 

1.102

 

Lower arch

31

0.658

NS

0.348

NS

0.551

NS

32

0.474

NS

0.536

NS

0.773

NS

33

0.445

NS

0.593

NS

0.926

NS

34

0.882

NS

0.581

NS

0.965

NS

35

0.334

NS

0.100

NS

0.800

NS

36

1.119

NS

1.510

NS

1.314

NS

37

0.954

NS

1.110

NS

1.527

NS

41

0.338

NS

0.351

NS

0.540

NS

42

0.810

NS

0.673

NS

1.275

NS

43

0.423

NS

0.752

NS

1.233

NS

44

0.877

NS

0.856

NS

1.305

NS

45

0.824

NS

0.653

NS

1.432

NS

46

1.131

NS

0.932

NS

1.389

NS

47

0.960

NS

1.262

NS

1.468

NS

Mean

0.731

 

0.733

 

1.107

 

NS not significant

Table 3

Mean prescription and mean imprecision values

 

N

Mean prescription(°)

SD

Mean imprecision(°)

SD

Median

IQR

Significance.

Upper arch

 VL tip

Incisors

57

9.2

6.7

4.5

4.0

3.4

−  0.6

NS

Canines

29

5.1

3.2

2.5

1.5

2.3

0.8

NS

Premolars

53

5.1

3.4

3.1

2.6

2.1

− 0.5

NS

Molars

37

3.9

1.4

2.9

2.2

2.5

0.3

NS

 MD tip

Incisors

57

6.4

4.5

3.2

2.6

2.5

− 0.1

NS

Canines

29

4.7

2.8

2.8

2.2

2.6

0.4

NS

Premolars

53

4.6

3.3

3.6

2.3

3.9

1.6

NS

Molars

37

4.5

1.6

3.4

2.3

3.4

1.1

NS

 Rot.

Incisors

57

10.8

9.3

5.0

5.3

3.7

− 1.6

NS

Canines

29

6.5

4.6

4.3

2.8

3.6

0.8

NS

Premolars

53

7.0

6.7

3.5

3.1

2.9

− 0.2

NS

Molars

37

7.2

4.8

4.8

4.6

4.4

− 0.2

NS

Lower arch

 VL tip

Incisors

64

5.9

2.1

2.9

2.6

2.3

− 0.3

NS

Canines

30

7.2

5.0

3.5

2.8

3.1

0.3

NS

Premolars

52

6.2

4.1

3.2

2.2

2.9

0.7

NS

Molars

23

3.9

1.7

1.3

.9

1.9

1.0

NS

 MD tip

Incisors

64

4.2

1.5

2.7

1.9

2.2

0.3

NS

Canines

30

4.8

2.0

3.3

2.2

2.9

0.6

NS

Premolars

52

5.4

4.7

3.4

2.6

3.1

0.5

NS

Molars

23

6.3

3.7

4.3

3.0

3.5

0.5

NS

 Rot.

Incisors

64

7.2

4.4

3.4

2.5

2.8

0.3

*

Canines

30

12.4

10.0

6.9

5.4

5.5

0.1

*

Premolars

52

7.3

6.0

5.4

5.8

3.7

− 2.1

NS

Molars

23

4.6

2.8

2.0

1.8

1.4

− 0.4

*

VL tip vestibulolingual tip, MD tip mesiodistal tip, Rot. rotation, SD standard deviation, IQR interquartile range, NS not significant

*p < 0.05

Table 4 shows the mean accuracy, its standard deviation and standard error, and the statistical significance calculated for each type of tooth and tooth movement. In the upper arch, the inferential statistical analysis performed showed that neither the mesiodistal tip on the canines, premolars and molars, nor the rotation of the molars were significantly different from 1 (p < 0.05), chosen as the reference value to indicate 100% achievement of the planned movement. That being said, all other tooth movements displayed a predictability that was significantly lower than 100%. In contrast, in the lower arch, mesiodistal tipping and rotation of the canines and rotation of the incisors were significantly less accurate than 100%, while all other tooth movements achieved were not statistically different from the target movement.
Table 4

Accuracy of movements achieved

 

N

Mean accuracy

Standard deviation

Mean standard error

Significance

Upper arch

 VL tip incisors

28

0.65

0.34

0.064714

*

 VL tip canines

16

0.54

0.57

0.143044

*

 VL tip premolars

32

0.70

0.81

0.142849

*

 VL tip molars

16

0.52

0.53

0.133131

*

 MD tip incisors

36

0.77

0.58

0.096078

*

 MD tip canines

16

0.78

0.50

0.125380

NS

 MD tip premolars

27

0.71

0.78

0.150417

NS

 MD tip molars

22

0.98

0.98

0.217782

NS

 Rot. incisors

45

0.61

0.29

0.042538

*

 Rot. canines

25

0.62

0.66

0.131114

*

 Rot. premolars

29

0.54

0.54

0.100854

*

 Rot. molars

18

0.78

0.61

0.144458

NS

Lower arch

 VL tip incisors

35

0.86

0.65

0.109173

NS

 VL tip canines

15

0.66

0.55

0.142351

*

 VL tip premolars

29

0.90

0.82

0.151409

NS

 VL tip molars

7

0.86

0.51

0.191882

NS

 MD tip incisors

31

0.88

0.86

0.154196

NS

 MD tip canines

18

0.87

0.82

0.193936

NS

 MD tip premolars

33

0.97

0.97

0.168750

NS

 MD tip molars

17

0.62

0.82

0.199778

NS

 Rot. incisors

51

0.67

0.57

0.080357

*

 Rot. canines

25

0.54

0.74

0.147841

*

 Rot. premolars

36

0.83

1.38

0.229989

NS

 Rot. molars

14

0.85

0.67

0.180257

NS

VL tip vestibulolingual tip, MD tip mesiodistal tip, Rot. rotation, NS not significant

*p < 0.05

Table 5 compares the mean accuracy among all tooth/movement combinations. This comparison revealed only one statistically significant difference. In other words, there was no greater precision statistically demonstrable in terms of one tooth movement with respect to another, with the exception of the lower incisors, whose rotation accuracy (0.40) was significantly lower than that of the lower premolars (0.87).
Table 5

Accuracy among tooth/movement combinations

Group/arch

Group/arch

Vestibulolingual tip

Mesiodistal tip

Rotation

Difference between means

Standard error

Significance

Difference between means

Standard error

Significance

Difference between means

Standard error

Significance

Incisors—upper arch

Incisors—lower arch

− .06361

.11235

NS

− .23697

.13106

NS

− .13364

.11270

NS

Canines—upper arch

− .18249

.13887

NS

.02068

.16072

NS

− .24391

.13745

NS

Canines—lower arch

− .07897

.14178

NS

− .22471

.15442

NS

− .27064

.13745

NS

Premolars—upper arch

− .19907

.11467

NS

− .18541

.13618

NS

− .18593

.13121

NS

Premolars—lower arch

− .18289

.11740

NS

− .28056

.12891

NS

− .4711025*

.12321

.005

Molars—upper arch

− .10530

.13887

NS

− .36883

.14475

NS

− .13254

.15367

NS

Molars—lower arch

.05389

.18725

NS

− .22751

.15741

NS

− .11360

.16863

NS

Incisors—lower arch

Incisors—upper arch

.06361

.11235

NS

.23697

.13106

NS

.13364

.11270

NS

Canines—upper arch

− .11888

.13372

NS

.25765

.16466

NS

− .11027

.13453

NS

Canines—lower arch

− .01537

.13675

NS

.01227

.15851

NS

− .13700

.13453

NS

Premolars—upper arch

− .13546

.10838

NS

.05156

.14081

NS

− .05229

.12815

NS

Premolars—lower arch

− .11928

.11127

NS

− .04359

.13379

NS

− .33746

.11995

NS

Molars—upper arch

− .04170

.13372

NS

− .13186

.14912

NS

.00110

.15107

NS

Molars—lower arch

.11749

.18347

NS

.00946

.16143

NS

.02004

.16626

NS

Canines—upper arch

Incisors—upper arch

.18249

.13887

NS

− .02068

.16072

NS

.24391

.13745

NS

Incisors—lower arch

.11888

.13372

NS

− .25765

.16466

NS

.11027

.13453

NS

Canines—lower arch

.10351

.15926

NS

− .24539

.18379

NS

− .02673

.15585

NS

Premolars—upper arch

− .01658

.13568

NS

− .20609

.16876

NS

.05798

.15038

NS

Premolars—lower arch

− .00040

.13800

NS

− .30124

.16295

NS

− .22719

.14345

NS

Molars—upper arch

.07718

.15667

NS

− .38951

.17575

NS

.11137

.17033

NS

Molars—lower arch

.23637

.20080

NS

− .24819

.18632

NS

.13031

.18394

NS

Canines—lower arch

Incisors—upper arch

.07897

.14178

NS

.22471

.15442

NS

.27064

.13745

NS

Incisors—lower arch

.01537

.13675

NS

− .01227

.15851

NS

.13700

.13453

NS

Canines—upper arch

− .10351

.15926

NS

.24539

.18379

NS

.02673

.15585

NS

Premolars—upper arch

− .12010

.13866

NS

.03929

.16277

NS

.08471

.15038

NS

Premolars—lower arch

− .10391

.14093

NS

− .05585

.15674

NS

− .20046

.14345

NS

Molars—upper arch

− .02633

.15926

NS

− .14412

.17001

NS

.13810

.17033

NS

Molars—lower arch

.13286

.20283

NS

− .00280

.18091

NS

.15704

.18394

NS

Premolars—upper arch

Incisors—upper arch

.19907

.11467

NS

.18541

.13618

NS

.18593

.13121

NS

Incisors—lower arch

.13546

.10838

NS

− .05156

.14081

NS

.05229

.12815

NS

Canines—upper arch

.01658

.13568

NS

.20609

.16876

NS

− .05798

.15038

NS

Canines—lower arch

.12010

.13866

NS

− .03929

.16277

NS

− .08471

.15038

NS

Premolars—lower arch

.01618

.11361

NS

− .09515

.13881

NS

− .28517

.13749

NS

Molars—upper arch

.09377

.13568

NS

− .18342

.15363

NS

.05338

.16534

NS

Molars—lower arch

.25296

.18490

NS

− .04210

.16562

NS

.07233

.17932

NS

Premolars—lower arch

Incisors—upper arch

.18289

.11740

NS

.28056

.12891

NS

.4711025*

.12321

.005

Incisors—lower arch

.11928

.11127

NS

.04359

.13379

NS

.33746

.11995

NS

Canines—upper arch

.00040

.13800

NS

.30124

.16295

NS

.22719

.14345

NS

Canines—lower arch

.10391

.14093

NS

.05585

.15674

NS

.20046

.14345

NS

Premolars—upper arch

− .01618

.11361

NS

.09515

.13881

NS

.28517

.13749

NS

Molars—upper arch

.07758

.13800

NS

− .08827

.14723

NS

.33856

.15907

NS

Molars—lower arch

.23677

.18660

NS

.05305

.15969

NS

.35750

.17356

NS

Molars—upper arch

Incisors—upper arch

.10530

.13887

NS

.36883

.14475

NS

.13254

.15367

NS

Incisors—lower arch

.04170

.13372

NS

.13186

.14912

NS

− .00110

.15107

NS

Canines—upper arch

− .07718

.15667

NS

.38951

.17575

NS

− .11137

.17033

NS

Canines—lower arch

.02633

.15926

NS

.14412

.17001

NS

− .13810

.17033

NS

Premolars—upper arch

− .09377

.13568

NS

.18342

.15363

NS

− .05338

.16534

NS

Premolars—lower arch

− .07758

.13800

NS

.08827

.14723

NS

− .33856

.15907

NS

Molars—lower arch

.15919

.20080

NS

.14132

.17273

NS

.01894

.19636

NS

Molars—lower arch

Incisors—upper arch

− .05389

.18725

NS

.22751

.15741

NS

.11360

.16863

NS

Incisors—lower arch

− .11749

.18347

NS

− .00946

.16143

NS

− .02004

.16626

NS

Canines—upper arch

− .23637

.20080

NS

.24819

.18632

NS

− .13031

.18394

NS

Canines—lower arch

− .13286

.20283

NS

.00280

.18091

NS

− .15704

.18394

NS

Premolars—upper arch

− .25296

.18490

NS

.04210

.16562

NS

− .07233

.17932

NS

Premolars—lower arch

− .23677

.18660

NS

− .05305

.15969

NS

− .35750

.17356

NS

Molars—upper arch

− .15919

.20080

NS

− .14132

.17273

NS

− .01894

.19636

NS

NS not significant

*p < 0.05

Discussion

It is a common experience among clinicians that some tooth movements can be achieved more easily than others with aligners. However, the precise degree to which the achieved movements differ from the ideal movements planned using digital setups is difficult to quantify experimentally. First and foremost, it is necessary to identify stable structures within the oral cavity that can be used as reference points for superimposition of digital images. Among these, the palatine folds are the most frequently chosen [17], even though several studies have shown that their position and/or dimensions may vary in certain clinical conditions [18]. Furthermore, palatal structures may only be used as reference points in the upper jaw. This is one of the reasons why superimposition on stable teeth has been selected as the method of choice for evaluating the accuracy of Invisalign by several authors [14, 19, 20]. However, that method may only be used in cases in which orthodontic treatment involves the displacement of only some teeth; moreover, even if this is the case, collateral effects on the position of other teeth cannot be ruled out. Indeed, intrusion may occur due to the masticatory forces exerted when wearing aligners, and any teeth used as anchorage may be subject to reactionary displacement [20].

The method of tooth position measurement proposed by Huanca [16], on the other hand, is based on the occlusal plane as a point of reference. Calculated as the plane passing through the mesiovestibular cusps of the first molars and the centroid of the FACC of all of the other teeth, with the exception of canines, the occlusal plane is a reference that enables the measurement error due to tooth movement during orthodontic treatment to be minimised. Moreover, it is applicable to both arches in all individuals, and allows evaluation of orthodontic movement of all teeth, both anterior and posterior. What is more, the reliability of this method has been demonstrated for tooth movements greater than 2°, at which it displays no measurement or systematic error.

Using this method, we demonstrate that the mean accuracy of orthodontic movement provided by the F22 aligner is 73.6%, considering all movements in both anterior and posterior teeth, while it falls to 70.6% if only the anterior teeth are considered. Although derived from a different methodology, these figures appear to compare favourably with the 56 and 41% predictability achieved by Invisalign for anterior teeth reported by Nguyen and Cheng [21], and Kravitz et al. [14], respectively.

We found that the most accurate movement achieved by F22 was mesiodistal tipping, whose mean accuracy was 82.5% (SD = 77.4) overall, and 96.7% at the lower premolars (SD = 96.9), closely followed by the upper molars (93.4%, SD = 72.6) and lower incisors (87.7%, SD = 85.9%). Less precise movements were found to be vestibulolingual tipping of the upper molars (52.5%, SD = 53.3) and upper canines (54.0%, SD = 57.2%) and rotation of the upper premolars (54.0%, SD = 54.3) and lower canines (54.2%, SD = 73.9) (Table 6, Fig. 6).
Table 6

Mean (%) accuracy of tooth movements achieved using F22

 

Vestibulolingual tip

Mesiodistal tip

Rotation

Tooth

Mean (%)

n

SD

Mean (%)

n

SD

Mean (%)

n

SD

Upper incisors

64.5

28

34.2

76.7

36

57.6

61.5

45

28.5

Upper canines

54.0

16

57.2

78.3

16

50.2

62.3

25

65.6

Upper premolars

69.6

32

80.8

70.6

27

78.2

54.0

29

54.3

Upper molars

52.5

16

53.3

93.4

22

72.6

78

18

61.3

Lower incisors

86.1

35

64.6

87.7

31

85.9

67

51

57.4

Lower canines

66.4

15

55.1

86.7

18

82.3

54.2

25

73.9

Lower premolars

90.4

29

81.5

96.7

33

96.9

82.7

36

138

Lower molars

86.2

7

50.8

61.8

17

82.4

85.4

14

67.4

Total

71.2

178

59.7

81.5

200

75.8

68.1

243

68.3

Fig. 6

Accuracy of planned movements by tooth type

Rotation

Rotation movements, especially of rounded teeth like the canines and premolars, are notoriously difficult to achieve with aligners. Indeed, one prospective study [19] conducted on 53 canines in 31 subjects found a mean canine rotation accuracy of 36%. Greater canine rotation accuracy can be achieved with interproximal reduction (IPR), but this only provides an accuracy of 43%, albeit with a lower standard deviation (SD = 22.6%). Another study [14] found a rotation accuracy of 32% at the upper canines and even less at the lower canines (29%), as compared to the upper central (55%) and lower lateral incisors (52%). Moreover, there is an even further significant reduction in the accuracy of upper canine rotation at rotations of greater than 15° (19%; SD = 14.1%; P < .05).

Our data confirm that among the lower teeth canine movement is the least accurate. That being said, our predictability percentage was higher than that reported in the literature for other aligner systems (54.2%, SD = 73.9). Furthermore, the F22 aligners achieved an accuracy index not significantly different from 1, i.e. 100% of the prescribed movement, for rotation of the upper molars (0.78, SD = 0.61), lower premolars (0.83, SD = 1.27) and lower molars (0.85, SD = 0.67).

That being said, comparison of all movements achieved by F22 in all tooth categories shows that, with respect to the prescription, the mean rotation of the upper incisors appeared significantly more accurate than the mean rotation of the lower premolars. This is in line with several literature reports on other aligner systems, for example Djeu et al.’s Invisalign study [22], in which they noted that one of the strengths of the system was the ability to correct the rotation of anterior teeth and level the incisor margins. Kravitz [14] also showed that the greatest rotation accuracy is achieved at the upper incisors (mean accuracy 48.8% for central and lateral incisors); Nguyen and Cheng [21] too confirm this finding, reporting a mean incisor rotation of 60%. This parallels our figure of 61.5% (SD = 28.5%), but with F22 aligners, we found that the best rotation accuracy was achieved at the lower molars (85.4%, SD = 67.4) and lower premolars (82.7%, SD = 138)—teeth that were not considered in Kravitz’s analysis—albeit with a high standard deviation.

Mesiodistal and vestibulolingual tipping

Kravitz’s 2009 study [14] repeated a mean accuracy of 41% for mesiodistal tipping, which was most accurate at both the upper (43%) and lower (49%) lateral incisors; mesiodistal tipping of the upper (35%) and lower (27%) canines and the upper central incisors (39%) was the least accurate. Our F22 results are in line with these findings, in that the least predictable movements achieved in the anterior sector were the upper canines and incisors, although once again, our accuracy scores were markedly higher. Indeed, the mesiodistal tip achieved at neither the upper canines (0.78, SD = 0.5), nor the upper premolars (0.7, SD = 0.78), upper molars (0.93, SD = 1.02), lower incisors (0.88, SD = 0.86), lower canines (0.87, SD = 0.82), lower premolars (0.97, SD = 0.97) or lower molars (0.62, SD = 0.82) was significantly different from 1, considered full achievement of the outcomes predicted by the setup. As regards vestibulolingual tipping, on the other hand, neither the lower incisors (0.86, SD = 0.64), nor the lower premolars (0.9, SD = 0.81) or lower molars (0.86, SD = 0.5) exhibited an accuracy index not significantly different from 1.

The orthodontic movement is a multifactorial issue. There are many parameters that can affect the ability to reach the goal planned in the setup. The crown anatomy, the root length and bone density were taken in consideration in this study dividing the sample into different groups by dental typology. Other parameters like sex and age of the patient could also influence the response to the aligners’ application, as suggested by literature [23]. In addition, the characteristics of the material, thickness, alignment protocol application and staging may affect the efficiency of the orthodontic movement. All these parameters will need to be thoroughly investigated in future research.

There were several limitations to this study. First and foremost, it would have benefitted from a larger sample. Only 16 patients remained after the selection process, giving a potential 448 teeth to be analysed. However, once movements of prescription lower than 2° were excluded, this number fell to 346. Second point, as this is a retrospective study, the cases with complete records are more likely to be those that completed treatment, rather than truly representative of those who started treatment with aligners. This could overestimate the effectiveness of the treatment.

Furthermore, we analysed only three types of tooth movement: rotation, mesiodistal tipping and vestibulolingual tipping; as digital models rather than radiographs were used for measurements, there was no information regarding root position from which to derive torque values. Nevertheless, the method of measurement we used, with the aid of VAM software, did enable us to analyse both anterior and posterior teeth, relying as it did on an “average” occlusal plane, passing through the centroids of the FACC points of all teeth (except for the canines) as a reference. Indeed, this plane is only minimally affected by the tooth movements achieved during treatment. That being said, the occlusal plane cannot be considered entirely stable and, moreover, it is difficult to compare the results of this type of analysis with those in the literature, which derive from superimpositions of the palatine folds and posterior teeth.

Finally, it is worth noting that the study design did not enable us to explore the full potential of F22 aligner treatment. Indeed, complex movements are usually aided by the use of auxiliaries such as elastics or chains, whereas we evaluated outcomes achieved by the F22 Grip Points (attachments) and stripping alone. It is conceivable that in the hands of an experienced orthodontist, with a full array of auxiliaries at their disposal, the accuracy percentages we revealed could be further improved upon.

Conclusions

Our analysis of the predictability of orthodontic movements that can be achieved using F22 aligners, without auxiliaries, enables us to state that
  • The mean accuracy of rotation, mesiodistal tipping and vestibulolingual tipping was 70.6% in the anterior sector and 73.6% across both full arches.

  • Mesiodistal tipping was the most predictable movement, reaching a mean accuracy of 82.5%; vestibulolingual tipping and rotation reached 72.9 and 66.8% of the prescribed movement, respectively.

  • The least predictable movement was rotation of the lower canines (54.2%), while the most predictable movements were mesiodistal tipping of the upper molars and lower premolars (respectively 93.4 and 96.7%).

  • The mean rotation error was significantly greater at the lower canines than at the lower incisors and molars.

  • In the upper arch, mesiodistal tipping of the canines, premolars and molars displayed a very high accuracy index, not significantly different from 1. This was also true of vestibulolingual tipping of the molars.

  • In the lower arch, the accuracy index was not significantly different from 1 for mesiodistal tipping of all teeth, vestibulolingual tipping of the incisors, premolars and molars, and rotation of the premolars and molars.

  • There were no significant differences in the accuracy index between tooth movements, with the exception of upper incisor rotation, which was significantly lower to that achieved at the lower premolars.

  • Further research on the topic using such a precise and reproducible means of model superimposition and measurement is required and should involve larger samples in order to shed light on the potential benefits and drawbacks of aligner systems.

Declarations

Authors’ contributions

FR analysed the dataset. AA recruited and treated the patients. LHG developed the analytical method. LL designed the study. GS supervised the research. All authors read and approved the final manuscript.

Ethics approval and consent to participate

The study was performed in accordance with the Declaration of Helsinki.

It is a retrospective analysis, and the protocol was approved by the Chairman of Postgraduate School of Orthodontics, University of Ferrara.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors’ Affiliations

(1)
Postgraduate School of Orthodontics, University of Ferrara
(2)
Department of Biomedical Sciences and Health, University of Milan

References

  1. Sheridan JJ. The Readers’ Corner 2: what percentage of your patients are being treated with Invisalign appliances? J Clin Orthod. 2004;38:544–5.PubMedGoogle Scholar
  2. Kesling HD. Coordinating the predetermined pattern and tooth positioner with conventional treatment. Am J Orthod Oral Surg. 1946;32:285–93.View ArticlePubMedGoogle Scholar
  3. Kuo E, Miller RJ. Automated custom-manufacturing technology in orthodontics. Am J Orthod Dentofac Orthop. 2003;123:578–81.View ArticleGoogle Scholar
  4. Joffe L. Invisalign: early experiences. J Orthod. 2003;30:348–52.View ArticlePubMedGoogle Scholar
  5. Baldwin DK, King G, Ramsay DS, Huang G, Bollen AM. Activation time and material stiffness of sequential removable orthodontic appliances. Part 3: premolar extraction patients. Am J Orthod Dentofac Orthop. 2008;133:837–45.View ArticleGoogle Scholar
  6. Lombardo L, Arreghini A, Maccarrone R, Bianchi A, Scalia S, Siciliani G. Optical properties of orthodontic aligners—spectrophotometry analysis of three types before and after aging. Prog Orthod. 2015;16:41.View ArticlePubMedPubMed CentralGoogle Scholar
  7. Zheng M, Liu R, Ni Z, Yu Z. Efficiency, effectiveness and treatment stability of clear aligners: a systematic review and meta-analysis. Orthod Craniofac Res. 2017;26Google Scholar
  8. Wong BH. Invisalign A to Z. 5, May 2002. Am J Orthod Dentofac Orthop. 2002;121:540–1.View ArticleGoogle Scholar
  9. Boyd RL. Complex orthodontic treatment using a new protocol for the Invisalign appliance. J Clin Orthod. 2007;41:525–47.PubMedGoogle Scholar
  10. Lombardo L, Martines E, Mazzanti V, Arreghini A, Mollica F, Siciliani G. Stress relaxation properties of four orthodontic aligner materials: a 24-hour in vitro study. Angle Orthod. 2017;87:11–8.View ArticlePubMedGoogle Scholar
  11. Guarneri MP, Lombardo L, Gracco A, Siciliani G. The state of the art of clean aligner technique [in Italian]. Bologna, Italy: Martina Editor. 2013:15–24.Google Scholar
  12. Align Technology, Inc. The Invisalign reference guide. Santa Clara, Calif; 2002.Google Scholar
  13. Boyd RL. Increasing the predictability of quality results with Invisalign. Proceedings of the Illinois Society of Orthodontists; Oak Brook; March 7, 2005.Google Scholar
  14. Kravitz ND, Kusnoto B, BeGole E, Obrez A, Agran B. How well does Invisalign work? A prospective clinical study evaluating the efficacy of tooth movement with Invisalign. Am J Orthod Dentofac Orthop. 2009;135:27–35.View ArticleGoogle Scholar
  15. Rossini G, Parrini S, Castroflorio T, Deregibus A, Debernardi CL. Efficacy of clear aligners in controlling orthodontic tooth movement: a systematic review. Angle Orthod. 2015;85(5):881–9.View ArticlePubMedGoogle Scholar
  16. Huanca Ghislanzoni LT, Lineberger M, Cevidanes LH, Mapelli A, Sforza C, McNamara JA Jr. Evaluation of tip and torque on virtual study models: a validation study. Prog Orthod. 2013;26:14–9.Google Scholar
  17. Miller RJ, Kuo E, Choi W. Validation of Align Technology’s Treat III digital model superimposition tool and its case application. Orthod Craniofac Res. 2003;6(Suppl 1):143–9.View ArticlePubMedGoogle Scholar
  18. Ali B, Shaikh A, Fida M. Stability of palatal rugae as a forensic marker in orthodontically treated cases. J Forensic Sci. 2016;61:1351–5.View ArticlePubMedGoogle Scholar
  19. Kravitz ND, Kusnoto B, Agran B, Viana G. Influence of attachments and interproximal reduction on the accuracy of canine rotation with Invisalign. A prospective clinical study. Angle Orthod. 2008;78:682–7.View ArticlePubMedGoogle Scholar
  20. Simon M, Keilig L, Schwarze J, Jung BA, Bourauel C. Treatment outcome and efficacy of an aligner technique—regarding incisor torque, premolar derotation and molar distalization. BMC Oral Health. 2014;14:68.View ArticlePubMedPubMed CentralGoogle Scholar
  21. Nguyen CV, Chen J. (Chapter 14) in: O.C. Tuncay (Ed.) The Invisalign system. New Malden: Quintessence Publishing Company, Ltd; 2006. p. 12–32.Google Scholar
  22. Djeu G, Shelton C, Maganzini A. Outcome assessment of Invisalign and traditional orthodontic treatment compared with the American Board of Orthodontics objective grading system. Am J Orthod Dentofac Orthop. 2005;128:292–8.View ArticleGoogle Scholar
  23. Chisari JR, McGorray SP, Nair M, Wheeler TT. Variables affecting orthodontic tooth movement with clear aligners. Am J Orthod Dentofac Orthop. 2014;145(4 Suppl):S82–91.View ArticleGoogle Scholar

Copyright

© The Author(s). 2017

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