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INTRODUCTION
Improving facial esthetics is critical in orthodontic treatment. Many cephalometric analyses have been proposed to standardize facial evaluation and orthodontic treatment planning and to develop cephalometric norms or analyses in order to define the dentoskeletal and soft tissue characteristics of a “good face.” The positions of the maxillary and mandibular incisors are important in determining the soft tissue profile.1 In particular, the sagittal position and inclination of the incisors are highly relevant to lip and chin prominence.1,2 Thus, orthodontists must determine the ideal position of the incisors when formulating the treatment plan, selecting the extraction vs. non-extraction approach, and adopting an anchorage design.
Tweed3 indicated that the angle between the inclination of the mandibular incisors and the mandibular plane was essential for facial esthetics and tooth stability, but this supposition was only appropriate for treatment planning for patients with a normal sagittal skeletal relationship. With the advent of digitized and visualized orthodontic techniques, more emphasis has been placed on the ideal position of the maxillary incisors at the beginning of treatment planning. Researchers such as Downs,4 Steiner,5 McNamara,6 and Arnett et al.7 have all recommended evaluation methods for determining the ideal maxillary incisor sagittal position based on the relationship between the maxillary incisor and certain reference lines, such as U1-APog distance, U1-NA distance, U1-Np, and U1-Sn vert (see Fig. 1 and Table 1 for definitions of abbreviations mentioned in the text), but the accuracy of such indicators has not been evaluated in the Chinese population. Andrews and Andrews8 proposed the use of forehead position and angulation to determine the ideal sagittal position of the maxillary incisor in Element II of “The Six Elements of Orofacial Harmony,” but methods for acquiring a reproducible natural head position remain unsatisfactory.9 In addition, a small discrepancy in determining the goal anterior-limit line can result in a significant deviation in maxillary incisor positioning. Moreover, even patients with “normal” cephalometric values do not necessarily have perfect facial esthetics. Many perception studies determining the incisor position have shown that the ideal position of the maxillary incisors is related to dentoskeletal variables and soft tissue parameters.10,11
With the emergence of the digital era of orthodontics, artificial intelligence (AI)-assisted digitalized orthodontic treatment planning has come into focus. However, almost all AI-assisted treatment planning programs still depend on the personal experience of orthodontists in terms of maxillary incisor position.12 Therefore, accurately and objectively predicting the ideal position of the maxillary incisors is a key challenge to be addressed in the development of systematic treatment planning.
To this end, the current study aimed to obtain reliable predictions of appropriate maxillary incisor positions through comprehensive evaluations of skeletal, dental, and soft tissue measurements on cephalometric graphs of participants with esthetic facial profiles and to optimize digitalized orthodontic treatment planning.
MATERIALS AND METHODS
Study participants and design
This retrospective observational study was approved by the Ethics Committee of the West China Hospital of Stomatology, Sichuan University (WCHSIRB-2021-166). The participants were recruited from among Chinese women who had completed orthodontic treatment between January 2018 and December 2020, according to the following inclusion criteria: (1) young women (age, 18–40 years old) who had received orthodontic treatment with fixed appliances; (2) 1° ≤ ANB ≤ 7°; (3) an esthetic lateral profile according to the esthetic plane (EP): –4 mm ≤ UL-EP ≤ 0 mm and LL-EP ≤ 1 mm13,14; (4) no crowding and spacing, normal or totally distal occlusion, and normal overjet and overbite; and (5) good facial symmetry. The exclusion criteria were as follows: history of (1) functional orthopedic treatment; (2) surgery on the maxilla, mandible, or chin; (3) facial plastic surgeries; and (4) craniofacial defects or syndromes, e.g., cleft lip and palate.
The collected data included age at the beginning and completion of treatment, intraoral and facial photographs, and panoramic and lateral radiographic images. Participants with incomplete data were excluded. Profile photographs of the selected women were evaluated by three Chinese orthodontic specialists (professional group) and three Chinese laypersons (layperson group) to determine whether the facial profile is well-balanced. The evaluators had 3 response options (1, unpleasant; 2, acceptable; and 3, pleasant). Patients who were evaluated as “pleasant” by more than two evaluators in each evaluation group, with no “unpleasant”, were selected. In total, 498 patients who satisfied the inclusion criteria were included initially, while 254 were excluded; finally, 244 individuals were selected for further study after esthetic evaluation. The selected participants were divided into two groups: group I (skeletal Class I, 1° ≤ ANB ≤ 4°) and group II (skeletal Class II, 4° < ANB ≤ 7°).
Data collection
The lateral cephalograms of the selected participants were acquired using a cephalometer (Veraviewepocs; Morita, Kyoto, Japan) with the head in a natural position, the teeth in centric occlusion, and the lips in the resting position. Thereafter, Uceph software (version 4.3.2; Uceph, Chengdu, China) was used to adjust the cephalograms with the Frankfort plane parallel to the horizontal plane and to perform cephalometric tracing and analysis.
The radiographic magnification of the cephalograms was standardized at 100% actual size with a 200 mm metal ruler image captured in the digital film as the reference. Sixteen hard and nine soft tissue landmarks were identified on each digitized cephalogram (Figure 1). The skeletal, dental, and soft tissue measurements (Table 1) were then computed according to the reference lines.
First, differences in all measurements between two groups based on the sagittal skeletal pattern (ANB angle) were compared. Thereafter, indicators related to the sagittal position of maxillary incisor were analyzed with the others via linear correlation. The indicators directly related to the sagittal position of maxillary incisor were then screened out and used to obtain prediction models via stepwise multiple linear regression analysis. Finally, the prediction models were tested on a new sample of 30 women who had completed orthodontic treatment between January 2021 and April 2021, and satisfied the inclusion criteria. The esthetic evaluations of these new women were also performed by the same evaluators. Radiographs acquired before and after treatment were all measured and analyzed. The outcomes were compared with the actual values on the posttreatment cephalograms to estimate the accuracy of the regression models.
Both intraexaminer and interexaminer reliabilities were evaluated using the Bland–Altman method and intraclass correlation coefficients. Thirty randomly selected lateral cephalograms were digitized and measured twice by two independent examiners. Each examiner repeated the measurements after an interval of 2 weeks. The intraexaminer correlation coefficient of the cephalometric analysis was excellent, ranging from 0.90 to 0.97. The interexaminer reliability was also excellent, ranging from 0.91 to 0.94.
Statistical analysis
All statistical analyses were performed using IBM SPSS Statistics for Windows, Version 26.0 (IBM Corp., Armonk, NY, USA). Statistical analyses demonstrated a normal distribution of the data according to the Kolmogorov–Smirnov test (p > 0.05). The independent t-test was used to compare the mean values of the measurements between the two groups. Pearson correlation analysis was performed to identify the relationships between the skeletal, dental, and soft tissue variables and the sagittal maxillary incisor position. Stepwise multiple linear regression analysis was used to detect whether the variables were helpful in predicting the sagittal location of the maxillary central incisor. A p-value less than 0.05 was considered statistically significant.
RESULTS
In total, 244 women were included in this study: 133 in group I (mean age, 26.6 ± 6.7 years) and 111 in group II (mean age, 27.1 ± 6.4 years). The anteroposterior position of the maxillary incisors in group II was more protruded than that in group I. The L1-NB values (distance and angle) were significantly lower in group I than in group II. The maxillary incisor showed more lingual tipping (U1-NA angle and U1-SN) and the mandibular incisors (L1-NB angle and FMIA) showed significantly more labial tipping in group II than in group I. Interestingly, no significant difference in the U1-L1 angle was found between two groups (Table 2).
Pearson correlation analysis showed that the ideal position of the maxillary incisor was most correlated with the sagittal discrepancy between the maxilla and mandible (ANB), protrusion of the midface (A-Np), nasal tip projection (Prn-Sn vert), and development of the chin (Pog-NB and Pog’-Sn vert). Additionally, U1-APog distance, U1-NPog, and U1-G’ vert showed positive correlations with SN-MP and FMA. In addition, U1-APog distance and U1-NPog positively correlated with most of the soft tissue variables, including upper and lower lip lengths (Stmi-Me’), lower facial height (Sn-Me’), and the thickness of the soft tissue of the chin (Pog-Pog’). Moreover, the anteroposterior position of the maxillary incisors showed a close correlation with the inclination of both the maxillary and mandibular incisors (Table 3). Notably, among all measurements evaluating the sagittal position of the maxillary incisor, only the distance of U1-Sn vert showed a correlation with upper lip thickness, even though the distances of U1-Ap, U1-NA, and U1-Sn vert correlated with basic upper lip thickness (Table 4).
Multivariate regression analysis revealed that the sagittal position of the maxillary incisors was generally influenced by Prn-Sn vert, A-Np, and U1-L1. Moreover, U1-Ap, U1-NA distance, and U1-Sn vert were associated with U1-NA angle and L1-APog angle. Among all the multivariate regression analyses related to maxillary incisor position, analysis of U1-NPog showed the highest adjusted R2 value (Table 5). The multiple correlation analysis between predicted U1-NPog value (Y) and the skeletal, dental, and soft tissue variables was Y = 12.812 – 0.542* (Pog-Np) + 0.496* (A-Np) – 0.086* (U1-L1) + 0.206* (Prn-Sn vert). The multivariable prediction equation for U1-NPog could explain 76.4% of the variability. In addition, the adjusted R2 values in the analysis for U1-Sn vert, U1-NA distance, U1-Ap, and U1-APog distance were all above 0.5, indicating a goodness-of-fit.
Finally, the regression models were tested on 30 new women who had completed treatment. The measurement values of pretreatment skeletal and soft tissue variables were entered into the regression equations, using the means of incisor inclination from Table 2. Some variations were found between the actual and predicted values of the regression models. The differences between the actual and predicted mean values of the variables are shown in Table 6.
DISCUSSION
The position of the maxillary incisors is crucial for achieving an esthetic facial profile, and the concept of a planned incisor position has become indispensable to orthodontists.15,16 Previous studies demonstrated that certain variables associated with the incisor position, such as the distance from the maxillary and mandibular incisors to the AP-line or NA-line, significantly correlated with subjective facial evaluation.5,6,17 However, since dental and skeletal structures and soft tissues vary between individuals, orthodontists must formulate customized treatment plans rather than try to achieve normal mean values. By using multiple linear regression, this study aimed to provide accurate predictions of appropriate maxillary incisor positions based on individual dentoskeletal and soft tissue cephalometric measurements to facilitate treatment planning.
The interrelationships of the nose, lip, and chin play an important role in the perception of facial esthetics, and several reference lines have been introduced for this purpose. One of the most well-known analyses is the E-line described by Ricketts,18 as part of his computerized cephalometric analysis. The esthetic plane developed by Ricketts has been found sensitive in facial esthetic assessments and is recommended for discerning beautiful profiles.17-20 Huang and Li17 assessed Chinese patients and found that retraction of their lips in relation to the E-line correlated with an improvement in attractiveness ratings. Therefore, we applied this finding as a reference and included patients whose upper and lower lips were at the normal distance from Ricketts’ E-line, as indicated by previous studies.14
In this study, group II showed a more protruded maxilla (a significantly greater SNA degree and A-Np distance) and retrusive chin (significantly lower Pog-Np and Pog-NB distance) features than did group I. The anteroposterior position of the lips in group II was significantly more protrusive than that in group I, indicating that in accordance with a previous study, a protrusive lower lip could achieve facial balance with retrusive chin morphology in skeletal Class II malocclusion.17 The upper lip length between skeletal Class I and Class II malocclusions showed no significant difference, as previously reported.21 However, we found that the characteristics of some soft tissue measurements, such as basic upper lip thickness, soft tissue chin thickness, and upper lip length, according to the sagittal skeletal pattern were distinct with significant differences (Table 2). Basic upper lip thickness in group II was significantly lower than that in group I, while soft tissue chin thickness in group II was greater than that in group I. These observations can be explained as a natural effort of the soft tissues to compensate for the protruded maxilla and a retrusive chin to mask the condition and to provide a more balanced facial appearance.21,22
For incisor positioning, Tweed3 emphasized the mandibular incisors while Andrews23 and Steiner5 focused on maxillary incisor position. However, contradictions often occur between treatment goals estimated using different analysis methods and meeting all the standards is unreasonable for most patients treated. Thus, the treatment goal should be set with proper compensation according to the dentoskeletal pattern and soft tissue morphology.
The position and angulation of the maxillary and mandibular incisors have been proposed to compensate for skeletal discrepancy.24 Meanwhile, the labiolingual inclination of the maxillary and mandibular incisors is a key factor influencing facial attractiveness.11,16,25 Orthodontists must balance the anteroposterior position and the inclination of the incisors to achieve harmonious facial profiles in patients undergoing orthodontic treatment.26 Previous studies have shown that normal and slightly proclined mandibular incisors were acceptable, whereas greater proclination resulted in a disruption of facial esthetics.27 In this study, we found that the maxillary incisors were more retracted and lingually tipped while the mandibular incisors were more proclined in skeletal Class II malocclusion than in skeletal Class I malocclusion for the benefit of the esthetic profile (Table 2), and a close correlation existed between maxillary incisor anteroposterior position and inclination (Table 3).
An esthetic profile feature with proper labial position and the underlying incisor position depends on coordination among different facial parts, mainly nose and chin morphology and lip thickness.28 In fact, both the depth and prominence of the nose are unaffected by orthodontic treatment. Additionally, soft tissues around the chin region and upper lip thickness have been reported to be relatively stable.2,29 In this study, Pearson correlation analysis showed that variables associated with ideal maxillary incisor position generally showed strong correlations with nose and chin morphology. The distances of U1-APog, U1-Ap, U1-NA, U1-NPog, and U1-Sn vert positively correlated with the prominence of the nose; moreover, U1-APog distance, U1-Np, and U1-Sn vert showed positive correlations with soft tissue chin thickness. Taken together, these results suggest that nose and chin morphology should be considered variants to predict ideal upper incisor position and that a more protrusive maxillary incisor position is more harmonious with a prominent nose and chin.30 For the upper lip, our results showed that only the distance of the U1-Sn vert correlated with maxillary lip thickness, and the distances of U1-Ap, U1-NA, and U1-Sn correlated with basic upper lip thickness. However, the ideal sagittal positions of maxillary incisors relative to the planes of A-Pog, Np, N-Pog, and G’ vert showed no correlations with upper lip thickness. These findings indicated that although the thickness of the upper lip affects the profile, the ideal sagittal position of the maxillary incisor need not be predicted in every evaluation method.
In the stepwise multiple linear regression analysis, the independent variables used in each regression model test were selected according to the results of the correlation tests (Tables 3 and 4). The adjusted R2 value indicated that the multivariable prediction equation for U1-NPog distance could explain 76.4% of the variability (72.2% for U1-Sn vert). Additionally, in the comparison of means between the results derived from the prediction equations of the pretreatment cephalograms and actual results of the posttreatment cephalograms, the prediction accomplished using multivariable regression analysis was fairly accurate, especially for U1-NPog (Table 6). Therefore, the obtained regression equation can be used for forecasting outcomes to a satisfactory degree, and in the future, these models might benefit from improvements in software programs that would enable better maxillary incisor positioning, treatment planning, and setting visual treatment objectives.
The major limitation of the study is the subjectivity. The conclusions of this study are limited to women with skeletal Class I and skeletal Class II malocclusions. Therefore, further studies should expand the sample size to include all the groups representing a specific category. Additionally, the growth and development of skeletal and soft tissues are complete in adults. Therefore, growth was not considered in this study. Hence, future studies are warranted to determine whether the current findings are applicable to adolescent patients with growth and development potential during orthodontic treatment. In addition, in the regression equations, the values of the independent variables are the pretreatment measurements. Therefore, in orthodontic camouflage treatment for patients with severe skeletal deformity, where the Pog-point and A-point might change considerably after a large amount of tooth movement or mandibular rotation, these models require appropriate adjustments.
CONCLUSION
The appropriate position of the maxillary incisor is distinct in different sagittal skeletal patterns. The ideal position of the maxillary incisor correlated with the sagittal discrepancy between the maxilla and mandible, nose and chin morphology, and inclination of the maxillary and mandibular incisors. With the regression models, the ideal maxillary incisor position could be feasibly predicted using the U1-NPog distance calculated using dentoskeletal and soft tissue variables. Therefore, instead of using average values or norms, orthodontists must predict ideal, customized maxillary incisor positions based on a thorough consideration of dentoskeletal and soft tissue patterns.
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