Introduction
Facial esthetics have always received much attention in orthodontic treatment, especially in young adult female patients. Three-dimensional (3D) soft-tissue changes after orthodontic extraction have not been fully explained. This study evaluated the 3D morphologic changes after orthodontic extraction in young female patients using a structured light scanner.
Methods
Forty-five adult female patients aged 20-25 years were enrolled in our study. The treatment group consisted of patients who received orthodontic treatment with 4 premolar extractions, and the control group was composed of young female volunteers who had not undergone any orthodontic treatment. To monitor the soft-tissue changes, 9 morphologic regions and 12 landmarks were identified for the 3D deviation analyses. The spatial deviations of landmarks and regions in the x, y, and z directions were constructed for quantitative analysis. Color map images were constructed to visualize soft-tissue displacement as a qualitative evaluation. The paired sample test was used to compare differences at the beginning of the experiment (T0) and after 24 months (T1) in both groups. An independent t test with Bonferroni correction was performed to compare differences between the treatment and control groups. A linear regression test was performed between incisor retraction and changes in the perioral tissues.
Results
Subtracting the effect of aging from the lip changes in the control group, the treatment group showed a statistically significant difference in the displacement of labrale superius (−1.37 mm), labrale inferius (−1.89 mm), the upper lip region (−0.98 mm), and the lower lip region (−1.36 mm) along the z-axis. No significant differences were found between the treatment and control groups in the temporal, parotideomasseteric, and buccal regions. Pearson correlation tests indicated a positive correlation between incisor tip retraction and changes in soft tissues (two-dimensional cephalometric analysis, 3D landmark measurements, and 3D regional measurements). The correlation coefficient ranged between 0.45 and 0.55.
Conclusions
Three-dimensional soft-tissue changes were mainly concentrated in the upper and lower lip regions in adult female patients after the 4 premolars were extracted. For female patients aged 20-25 years with 4 extracted premolars, soft-tissue changes in the temporal, parotideomasseteric, and buccal regions were not clinically significant.
Highlights
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A new method to quantify 3-dimensional regional soft-tissue changes was established.
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Soft-tissue changes were mainly in the lip regions in young adult female patients after extraction.
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Soft-tissue changes in the other regions of the extraction group were not clinically significant.
In recent years, more adult patients have sought orthodontic treatment. Younger adults (aged 19-30 years), especially women, are thought to place greater priority on their facial esthetics and have significantly higher odds of seeking orthodontic treatment. Facial convexity and crowding compromise many chief complaints among adult female patients seeking orthodontic care. , Orthodontic treatment, especially the extraction of 4 premolars, is widely used to correct crowding and dentoalveolar protrusion, which improves the soft-tissue profile.
In the past decades, orthodontists have focused mainly on improving the sagittal profile, and few studies have paid attention to changes in the frontal view, which is most commonly visible on social occasions. Nowadays, more Asian female adult patients complain of “bracket face” after orthodontic treatment, particularly after tooth extraction. “Bracket face” is summarized as the decrease in facial fullness from the frontal view and is characterized by invaginated cheeks and temporal regions with more prominent zygomatic regions. , It collectively renders a greater-than-actual-age facial appearance, which is especially pronounced for young Asian women, who have flatter and softer facial contours than Caucasian populations. Thus, facial changes other than those in the labial region remain elusive. The notion of “bracket face” can hardly be universally accepted without a thorough understanding of facial changes associated with orthodontic treatment.
Conventional 2-dimensional (2D) photographs and radiographs have limitations in documenting the changes in facial soft tissue; they cannot provide sufficient information such as shape and depth and tend to be susceptible to many factors such as shooting distance and angles. Three-dimensional (3D) facial scanning has changed how facial esthetics are evaluated and has numerous advantages for facial analysis. Three-dimensional imaging tools include cone-beam computed tomography and noncontact optical scanning devices, such as structured light and laser scanners. Using a structured light scanning system, color and texture information of the facial soft tissue can be easily recorded in high resolution with a short scan time, with no harm to the naked eye or additional radiation hazards. ,
In the past, most published studies on the 3D assessment of soft tissue focused on the perioral regions. At the same time, changes measured only in landmarks or displayed by color maps, as in previous studies, might not reflect the actual soft-tissue changes exactly and intuitively. Therefore, we proposed a new method of measuring the regional deviation between superimposed facial scans. Moreover, previous studies often lacked a rigorously designed control group; therefore, their results may not exclude the interference of the natural aging process during orthodontic treatment.
Thus, our study used a structured light scanner to further investigate changes in facial soft tissue after extracting 4 premolars. Our goals were to (1) quantify the 3D morphologic changes in facial soft tissue after extracting 4 premolars in young adult female patients, (2) compare the soft-tissue changes of the treatment group with those of the naturally aging control group, and (3) verify the existence of the “bracket face” phenomenon in the treatment group.
Material and methods
This study was approved by the Research Ethics Board of Beijing Stomatological Hospital, Capital Medical University.
Young adult female volunteers were recruited as the control group. The inclusion criteria for the control group were: (1) women aged 20-25 years, (2) those who have not undergone any orthodontic treatment, and (3) those with a body mass index (BMI) in the range of 18.5-23.4 kg/m 2 .
Young female patients for this study were recruited from consecutive adult patients visiting the Department of Orthodontics, Beijing Stomatological Hospital, Capital Medical University, Beijing, China. The inclusion criteria for the treatment group were: (1) women aged 20-25 years, (2) skeletal Class I or mild Class II malocclusion, (3) extraction of 4 premolars because of either crowding (≥8 mm) or crowding (<8 mm) with dentoalveolar protrusion, (4) treatment with intraoral anchorages (minimum or moderate anchorage, no maximum anchorage such as temporary anchorage devices [TADs]); (5) BMI between 18.5 and 23.4 kg/m 2 , and (6) an orthodontic treatment duration within 30 months.
The exclusion criteria for all subjects were as follows: (1) obvious facial asymmetry, (2) third molar extraction during the experiment, and (3) noticeable BMI change during the research (>1.5 kg/m 2 ).
The sample size was calculated on the basis of previous studies, and the analysis was performed using PASS software (version 15.0.5; NCSS, LLC, Kaysville, Utah). The variable we used to calculate the sample size was the displacement of the lips, which was our main outcome. We set the treatment and control groups to be 1.8 ± 1.4 and 0.6 ± 0.3 mm, respectively, on the basis of the systematic review by Konstantonis et al, which presented the soft-tissue changes after the extraction and nonextraction orthodontic treatment. A minimum sample size of 17 subjects in the control group and 17 patients in the treatment group was required to detect significant differences (significance level of 0.05; 90% power). This study increased the sample size, considering a lost-to-follow-up rate of approximately 25%. Thus, 52 female patients (26 in the control group and 26 in the treatment group) were enrolled at the beginning of our study.
At the beginning of the experiment (T0), the 3D facial scans of the control group were obtained. After 24 months (T1), they underwent a second facial soft-tissue scan. From T0 to T1, 1 subject in the control group had a BMI change >1.5 kg/m 2 , and 4 subjects had their third molars extracted, so 5 subjects were excluded. Three-dimensional facial scans were acquired at T0 and T1 for the treatment group. Two patients had a weight increase of more than 5 kg during the treatment, so they were excluded. Hence, the final study sample consisted of 45 subjects, 21 in the control group and 24 in the treatment group. All patients in the treatment group were treated with vestibula fixed appliances (0.022 × 0.028-inch bracket slot) for an average of 28.3 months by 1 experienced orthodontist.
A structured light handheld scanner, Artec Eva (Artec Group, Luxembourg), was used to collect 3D facial images. During the scanning, the subjects were seated in a back-supported chair, and the operator held Eva to circle the subject’s face. The distance between the scanner and the subject’s face was 60-70 cm. The subject was naturally relaxed with a natural head position, the mandible was in a mandibular postural position, and the lips were gently closed. The scanned data were processed by Artec Studio 12 (Artec Group, Luxembourg) to synthesize a 3D color image of the face with an accuracy of 0.1 mm, a 3D resolution of 0.5 mm, and 1.3 million pixels.
Three-dimensional facial images at T0 and T1 were registered using Geomagic Design X (version 2020.1.1; 3D Systems, Rock Hill, SC). First, the lower face region was removed from the T0 image. The new image without the lower face region was denoted as the T0’ image. Second, the initial multipoint registration was conducted using 8 points (glabella, bilateral tragion, bilateral outer and inner canthi, and soft-tissue nasion). Best-fit alignment was then performed to calculate the best fit between the 2 scans (T0’ and T1 images) on the upper and middle third of the face. The combination of multipoint registration and the best-fit method has been applied in previous studies and has been shown to be reliable. Finally, the T0’ image was replaced by the T0 image without changing the superimposition.
A coordinate system was constructed on the basis of the superimposed T0 image ( Fig 1 ). The nasion of the soft tissue (Ns) was set to be the origin of the coordinate system at which the 3 planes coincided. The software calculated the sagittal plane (YZ), which divided the face equally because of its mirror-symmetry structure. The transverse plane (XZ) was constructed by rotating the adjusted Camper’s plane (perpendicular to the sagittal plane containing the right Ala-Tragal line) 7.5° upward with translation to Ns. The coronal plane (XY) was perpendicular to the previous 2 planes. Outward and inward displacements on the x-axis were recorded as “+” and “−,” respectively. On the y-axis, upward and downward displacements (upward: “+”; downward: “−”) were recorded. On the z-axis, the frontward and backward displacements (frontward: “+”; backward: “−”) were recorded. Finally, superimposed 3D images of T0 and T1 with 1 coordinate system were established for each subject.
To monitor the soft-tissue changes, 9 morphologic regions of the face ( Fig 2 ) and 12 landmarks ( Fig 3 ) were identified for the 3D deviation analyses ( Table I ). Morphologic regions were defined on the basis of the original work of Gonzales-Ulloa and Tirbod T. Fattahi, who proposed classifications of facial esthetic subunits ( Fig 2 , A ).
| Regions and landmarks | Definition |
|---|---|
| Regions | |
| Temporalfacial region | The temporofacial region is bounded by the hairline superiorly and posteriorly. The inferior border is the superior aspect of the zygomatic arch, and the anterior boundary is an imaginary projection line of temporal bone suture |
| Parotideomasseteric region | The parotideomasseteric region is bounded superiorly by the inferior border of the zygomatic arch, inferiorly by the jawline, anteriorly by the anterior border of the masseter muscle, and posteriorly by the preauricular creases |
| Buccal region | The buccal region is bounded superiorly by the inferior border of the zygomatic bone and inferiorly by the jawline, anteriorly by the lips and mental area, and posteriorly by the anterior border of the masseter muscle |
| Upper lip region | The upper lip region is bounded superiorly by the alar grooves and columella, laterally by the nasolabial grooves, and inferiorly by the interlabial gap |
| Lower lip region | The lower lip region is bounded superiorly by the interlabial gap, laterally by the melolabial grooves, and inferiorly by the mentolabial groove |
| Mental region | The mental region starts at the mentolabial groove superiorly, forming a curvilinear border laterally, and ends at the submental area |
| Landmarks | |
| Paranasal point (PaN) | The point at the confluence of nasolabial sulcus and labialfacial sulcus |
| Subnasale (Sn) | The point at the junction of the columella and upper lip |
| A’ point (A’) | The deepest point in the soft-tissue contour of the upper lip |
| Chresta philtri (Chp) | The most prominent point of the vermilion border of chresta philtri of the upper lip |
| Labrale superius (Ls) | The midpoint of the upper vermilion line |
| Cheilion (Ch) | The point located at each labial commissure |
| Labrale inferius (Li) | The midpoint of the lower vermilion line |
| B’ point (B’) | The deepest point of the soft-tissue contour between the lower lip and chin |
| Pogonion’ (Pog’) | The most anterior midpoint of chin |
Qualitative comparisons and quantitative measurements were performed using Geomagic Control X software (version 2020.1.1; 3D Systems). Qualitative comparisons of soft-tissue changes were illustrated using superimposed color map images. Increases in the blue indicated greater inward displacement at T1, whereas red indicated outward displacement ( Fig 4 ); green was set to indicate displacements within 1.23 mm, considering the validity of 0.72 ± 0.51 mm obtained by the 3D facial scans in previous research. Quantitative 3D-deviation analysis was performed for each patient to calculate the deviation in landmarks and regions for the superimposed facial meshes. The comparison point tool in the software was used to analyze the deviation between T0 and T1 data at selected landmarks. Each comparison point consisted of x-, y-, and z-coordinates and more information, such as normal, radius, maximum angle, and maximum distance criteria values ( Fig 5 , A ).
Each region was characterized by the mean and maximum values of the measurements at selected points within it. The number of points selected was determined by the size of the region, which was set at 50 for the temporal, parotideomasseteric, and buccal regions; 40 for the upper lip region; 25 for the lower lip region; and 15 for the mental region. All points were evenly distributed in the target regions ( Figs 5 , B and C ).
Cephalometric radiographs were taken for patients in the treatment group before and after orthodontic treatment. However, the control group did not obtain cephalograms to avoid unnecessary x-ray radiation exposure. For the treatment group, pretreatment and posttreatment cephalometric variables were measured using Dolphin Imaging software (version 11.8.06.22; Dolphin Imaging and Management Solutions, Chatsworth, Calif) on the basis of profile analysis methods described by Arnett et al. The reference system was constructed through 2 lines: the Frankfort horizontal (FH) plane (line) and Pn line (Dreyfus Line), which was placed through the subnasale and perpendicular to the FH line ( Fig 6 ). Soft tissue and tooth landmarks were projected horizontally to the Pn line, and the movement of landmarks was calculated by the change in distance from the Pn line.
The measurements of the 12 landmarks and 9 regions were obtained by 2 operators 3 times with an interval of 2 weeks, and then the average values were used. Whenever the difference was >0.5 mm, the values were judged by a third observer (observer 1 [Q.C.Q.], observer 2 [L.Z.], observer 3 [X.J.X.]). Operators were blinded to the groups of each patient. The intraclass correlation coefficients of all measurements were >0.85. Interobserver and intraobserver variabilities were analyzed using Bland-Altman plots. All data are displayed as mean values ± standard deviation. The assumption of normal distribution was confirmed using the Kolmogorov-Smirnov and Shapiro-Wilk tests. The paired samples test was performed to determine changes in both groups between T0 and T1. An independent t test was used to compare the treatment and control groups, followed by a Bonferroni correction to correct the comparisons for multiple testing with P values adjusted accordingly. Pearson’s correlation linear regression analysis was performed between incisor retraction and changes in soft tissues. All statistical analyses were performed using SPSS software (version 22.0; IBM Corp, Armonk, NY).
Results
Table II provides the descriptive statistics of the data. The quantitative analysis of the 3D changes at soft-tissue landmarks in both groups is shown in Table III . Because of the retraction of the upper and lower lips in the treatment group, backward movement of perioral landmarks was prominent on the z-axis (sagittal dimension). The magnitude of deviation at all the landmarks on the x- and y-axes was relatively small compared with the z-axis, accounting for almost 90% of the deviations on average. Labrale inferius (Li) changed by −0.59 mm in the Z direction in the control group, which was statistically significant. Retracting the effect of aging from the lip changes in the control group, the treatment group showed a statistically significant difference in the displacement of Labrale superius (Ls) (−1.37 mm) and Li (−1.89 mm) along the z-axis ( P = 0.0009 and P = 0.0001, respectively).
| Characteristic | Control group (n = 21) | Treatment group (n = 24) | P value |
|---|---|---|---|
| Age at T0 (y) | 22.9 ± 1.6 | 22.5 ± 1.8 | 0.89 |
| Age at T1 (y) | 25.1 ± 1.6 | 24.9 ± 1.9 | 0.85 |
| BMI at T0 | 20.9 ± 1.4 | 21.0 ± 1.6 | 0.61 |
| BMI at T1 | 21.0 ± 1.3 | 21.2 ± 1.6 | 0.80 |
| Observation/treatment duration (mo) | 27.0 ± 1.8 | 28.3 ± 2.0 | 0.11 |
| Variables | Control group | Treatment group | P value | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Deviation | X | Y | Z | Deviation | X | Y | Z | Deviation | X | Y | Z | |
| PaN (R) | 0.22 ± 0.66 | −0.04 ± 0.08 ∗ | 0.00 ± 0.09 | −0.23 ± 0.39 ∗ | −0.35 ± 0.83 | −0.01 ± 0.19 | 0.06 ± 0.15 | −0.34 ± 0.80 | 0.014 | 0.391 | 0.129 | 0.553 |
| PaN (L) | 0.34 ± 0.58 | 0.05 ± 0.23 | 0.01 ± 0.20 | −0.07 ± 0.71 | −0.36 ± 0.86 | −0.01 ± 0.11 | 0.05 ± 0.13 | −0.35 ± 0.84 | 0.860 | 0.112 | 0.134 | 0.844 |
| Sn | 0.32 ± 0.71 | 0.04 ± 0.19 | 0.02 ± 0.41 | −0.28 ± 0.84 | −0.74 ± 1.12 | 0.12 ± 0.31 | −0.16 ± 0.38 ∗ | −0.68 ± 1.04 ∗ | <0.001 ∗ | 0.324 | 0.144 | 0.163 |
| A’ | −0.11 ± 0.47 | −0.04 ± 0.22 | −0.03 ± 0.22 | −0.24 ± 0.73 | −1.31 ± 1.21 | −0.03 ± 0.28 | −0.39 ± 0.68 ∗ | −1.17 ± 1.05 ∗ | <0.001 ∗ | 0.945 | 0.020 | 0.001 |
| Ls | −0.88 ± 0.78 | 0.03 ± 0.40 | 0.01 ± 0.29 | −0.26 ± 0.83 | −1.79 ± 1.73 | −0.20 ± 0.72 | 0.18 ± 0.61 | −1.63 ± 1.61 ∗ | 0.026 | 0.189 | 0.241 | <0.001 ∗ |
| Chp (R) | −0.62 ± 0.55 | −0.05 ± 0.36 | 0.04 ± 0.23 | −0.19 ± 0.76 | −1.62 ± 1.38 | −0.53 ± 0.49 ∗ | −0.23 ± 0.67 | −1.39 ± 1.25 ∗ | 0.003 | <0.001 ∗ | 0.077 | <0.001 ∗ |
| Chp (L) | −0.50 ± 0.64 | −0.06 ± 0.25 | 0.03 ± 0.22 | −0.27 ± 0.84 | −1.62 ± 1.44 | −0.48 ± 0.76 ∗ | 0.04 ± 0.49 | −1.40 ± 1.30 ∗ | 0.002 | 0.019 | 0.929 | 0.001 |
| Li | −1.16 ± 0.81 | −0.05 ± 0.26 | −0.16 ± 0.40 | −0.59 ± 1.14 ∗ | −2.74 ± 2.03 | −0.03 ± 0.79 | −0.28 ± 1.23 | −2.48 ± 1.82 ∗ | 0.002 | 0.935 | 0.642 | <0.001 ∗ |
| Ch (R) | −0.58 ± 0.66 | 0.02 ± 0.18 | 0.22 ± 0.38 ∗ | −0.42 ± 0.69 ∗ | −1.31 ± 1.70 | −0.29 ± 0.46 ∗ | 0.65 ± 0.89 ∗ | −1.06 ± 1.41 ∗ | 0.061 | 0.005 | 0.044 | 0.057 |
| Ch (L) | −0.23 ± 0.88 | 0.09 ± 0.35 | 0.01 ± 0.57 | −0.10 ± 0.90 | −1.15 ± 2.00 | −0.24 ± 0.50 ∗ | 0.73 ± 1.35 ∗ | −0.80 ± 1.42 ∗ | 0.051 | 0.015 | 0.024 | 0.052 |
| B’ | −0.17 ± 0.48 | 0.00 ± 0.07 | 0.04 ± 0.34 | −0.29 ± 0.99 | −1.27 ± 2.18 | −0.01 ± 0.35 | 0.28 ± 1.10 | −1.15 ± 1.90 ∗ | 0.024 | 0.893 | 0.319 | 0.062 |
| Pog’ | −0.50 ± 0.60 | 0.06 ± 0.21 | 0.04 ± 0.61 | −0.32 ± 0.93 | −0.44 ± 2.01 | −0.15 ± 0.22 ∗ | 0.04 ± 1.13 | −0.50 ± 1.62 | 0.881 | 0.003 | 0.983 | 0.634 |
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