Computer-assisted development of age- and sex-specific cephalometric templates for evaluating facial profiles: A cross-sectional study

INTRODUCTION

Cephalometric analysis is pivotal in selecting a proper orthodontic treatment strategy and assessing treatment-induced changes.^[1] Employing templates for cephalometric analysis brings advantages, including the identification of compensatory skeletal and dental deviations, as well as alterations in dimensions and angles related to patient aging.^[2] While templates and tabulated numerical values represent similar ideas, using templates is less laborious and time-consuming, potentially offering an effective educational resource for both dental students and patients receiving treatment.^[2,3]

The use of templates for cephalometric evaluations dates back quite some time. In 1952, Baum introduced transparent templates that outlined the upper first molars and incisor teeth, which could be placed directly onto X-ray films.^[4] In 1958, following a study on 1300 records from the Burlington growth center, Popovich and Grainger developed templates for individuals aged 3, 6, 8, 10, and 12 years.^[5] Moorrees and Lebert advanced the field in 1962 by creating mesh diagrams. Unlike earlier templates that relied on standard numerical norms, these diagrams focused on comparing the proportions of different facial components within each individual face.^[6] Subsequently, Johnston, Ackerman, and Jacobson introduced various new versions of templates.^[7-9]

A variety of templates has been created to compare patient profiles against established norms. Duangsuwan et al.^[10] developed three-dimensional cephalometric templates tailored for Thai adults. Chalipa et al.^[11] presented cephalometric templates for Iranian girls aged 8–14. In addition, Su et al.^[3] introduced digital diagnostic templates following cluster analysis on cephalograms obtained from the Chinese Han population. However, these templates have several limitations, such as not differentiating between sexes and using a single template for various age groups. In addition, the majority of available templates are constructed by determining the mean coordinates of each landmark point and subsequently connecting these points to form the final design.^[2] Therefore, available templates do not provide standard deviation (SD) for each cephalometric norm,^[3,10,11] resulting in a simplistic binary outcome of either matching or not matching the template in cephalometric evaluations.

To the best of our knowledge, there are no studies that have concentrated on creating templates derived from the most attractive portion of the population. While esthetics and attractiveness are inherently subjective phenomena, the increasing intercultural exchanges through the internet, immigration, media, and arts are contributing to a more homogenized global standard of beauty.^[12] An example is the shift from the traditionally idealized “model’s nose,” characterized by its small, short, and less projected features, to the “global nose,” which is larger, wider, and more pronounced.^[12] Therefore, templates developed to evaluate patients’ profiles can potentially be used for different populations.

Cephalometric analysis is a time-intensive process, and existing templates present several limitations. They lack soft-tissue contours, are not suitable for individuals of the same age with varying profile sizes, and consist solely of mean landmarks connected by lines without any spectrum. To overcome these shortcomings, this study aimed to develop age- and sex-specific cephalometric templates incorporating means and SDs, utilizing computer-based methods to enhance the evaluation of patients’ cephalograms.

MATERIAL AND METHODS

Cephalometric landmark identification

For each selected sample, 40 cephalometric landmarks were located and marked using Dolphin Imaging software, resulting in images with 40 red dots representing these points [Figure 1]. In addition, the outlines of the face and the bone structures of the maxilla and mandible, including the Sella– Nasion (SN) line, were traced.

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Figure 1:

An illustration of 40 cephalometric landmarks marked using Dolphin Imaging software. G: Glabella, N: Nasion, N': Soft-Tissue Nasion, S: Sella, Ba: Basion, Po: Porion, Or: Orbitale, Ptm: Pterygomaxillary Fissure, Co: Condylion, C: Condylar Center, Ar: Articulare, Ra: Ramus Point, Go: Gonion, ANS: Anterior Nasal Spine, PNS: Posterior Nasal Spine, A: Point A, A': Soft-Tissue Point A, U1: Maxillary Central Incisor, L1: Mandibular Central Incisor, B: Point B, B': Soft-Tissue Point B, Pog: Pogonion, Pog': Soft-Tissue Pogonion, Gn: Gnathion, Gn': Soft-Tissue Gnathion, Me: Menton, Me': Soft-Tissue Menton, Prn: Pronasale, Sn: Subnasale, Stms: Stomion Superius, Stmi: Stomion Inferius, Li: Labrale Inferius

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Facial profile template generation

The lateral cephalometric tracings of the selected samples were then superimposed using the SN line as a standard reference across all age–sex groups in Adobe Photoshop 2020. The red dots were accurately placed, and the center of each pixel represented the cephalometric point, identified by the “find contour” function in the OpenCV library with Python.

The pixel position coordinates of the labeled landmarks were averaged for each age-sex group. A new photo was then generated, displaying the average positions of the cephalometric landmarks. To account for variations, we incorporated one SD from the most superior to the most inferior and from the most anterior to the most posterior [Figure 2].

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Figure 2:

Cephalometric landmarks and maximum one standard deviation. Red dots represent the average position of cephalometric landmarks and blue boundaries represent the maximum one standard deviation.

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To replicate real-life variations in facial profile sizes, we utilized the SN plane as a reference. Before superimposition, we measured the pixel distance between the upper and lower ruler points, as well as the SN distance, for each photograph. Utilizing the real-life ruler distance as a reference (10 mm), we determined the exact measurement of the SN plane in millimeters for each image. The mean and SD of these measurements were then calculated for every group. Based on these statistics, three facial profile templates were generated for each group, representing the mean and one SD in the anteroposterior and superior–inferior dimensions. These templates were generated using Adobe Photoshop 2020.

RESULTS

Generated facial profile template

A total of 400 photographs were analyzed, equally divided between males and females. The top 20% attractive photos from each age-sex group were selected (n = 80). [Tables 1 and 2] show the results of the cephalometric analysis of the selected samples, and [Figures 3 and 4] illustrate the facial profile templates for each age–sex group.

Table 1: Soft and hard tissue cephalometric measurements of attractive Iranian males classified by age.

Cephalometric parameter	7–10 years old		11–14 years old		15–18 years old		>18 years old
	SD	Mean	SD	Mean	SD	Mean	SD	Mean
Legan and Burstone
Facial convexity (contour) angle°	12.692	5.939	15.883	5.181	18.131	6.096	12.292	3.795
Maxillary prognathismmm	1.567	3.423	4.15	3.931	7.631	5.454	4.792	4.53
Mandibular prognathismmm	−6.983	4.508	−5.85	5.752	−2.938	8.539	−2.742	8.33
Vertical height ratio	1	603	1.0833	0.083	0.992	0.086	1	0.127
Lower facial throat angle°	105.633	6.113	107.183	8.87	108.86	9.134	113.508	12.929
Lower vertical height–depth ratio	1.125	0.176	1.15	0.178	1.292	0.197	1.558	0.345
Nasolabial angle°	107.25	10.079	107.733	11.041	115.831	10.913	102.783	10.673
Upper lip protrusionmm	4.108	0.903	4.783	1.178	3.769	1.659	4.258	1.088
Lower lip protrusionmm	3.408	1.477	3.108	1.904	3.108	2.075	2.7	1.971
Mentolabial sulcus depthmm	−4.542	1.12	−6.029	1.645	−5.5	1.771	−5.717	1.574
Vertical lip chin ratio	49.442	0.004	51.608	0.008	49.885	0.003	48.767	0.005
Maxillary incisor exposuremm	2.275	2.276	1.958	1.496	2.062	1.763	1.717	1.667
Interlabial gapmm	1.183	0.589	1.217	0.368	1.623	0.756	1.508	0.391
Holdaway
Soft tissue facial angle°	90.65	3.267	90.275	1.917	91.323	3.674	91.3	2.621
H angle°	16.333	2.927	19.217	2.685	17.015	4.271	15.383	2.994
Nose prominencemm	9.833	2.423	10.242	2.011	11.638	1.491	14.133	2.971
Superior sulcus depthmm	2.592	0.77	2.575	1.119	3.008	0.917	2.908	1.019
Soft-tissue subnasale to H linemm	5.508	1.157	6.442	1.569	5.023	2.273	5.65	1.382
Skeletal profile convexitymm	1.208	2.126	2.6	1.706	1.608	2.84	0.783	1.999
Basic upper lip thicknessmm	14.683	2.165	17.383	2.227	18.692	2.367	18.883	2.094
Upper lip strain measurementmm	12.133	1.832	12.708	2.103	13.408	1.399	14.108	2.136
Lower lip to H linemm	1.292	1.201	0.725	1.736	1.185	1.775	0.383	1.798
Inferior sulcus to H linemm	4.008	1.281	4.675	1.78	4.461	2.022	5.608	2.256
Soft-tissue chin thicknessmm	11.067	1.568	13.375	2.937	13.292	2.289	13.575	2.865
Ricketts
Lower lip to E-planemm	0.308	1.854	0.108	2.176	−0.123	2.497	−2.017	2.551
Upper lip to E-planemm	−1.892	1.888	−1.133	1.585	−2.369	2.083	−4.317	1.972
Steiner
SNA	78.718	4.772	80.325	3.046	80.9	4.467	81.008	4.307
SNB	75.1	3.927	76.917	2.835	78.3	4.141	79.008	3.584
ANB	3.609	4.756	2.371	1.632	2.6	2.698	2	2
Occlusal plane to SN angle	17.145	3.512	17.392	4.544	14.662	6.018	13.425	4.825
Mandibular plane angle	35.527	5.657	31.808	6.468	32.431	6.105	29.083	6.101
U1-NA angle	27.645	6.373	23.842	3.067	24.862	4.891	23.492	8.421
U1-NA distance	6.591	2.518	5.742	1.486	6.646	1.89	6.042	3.392
L1-NB angle	27.491	7.33	29.8	4.089	29.431	4.032	27.133	6.293
L1-NB distance	5.718	2.357	6.15	1.871	7.177	1.569	5.8	3.262
Interincisal angle	121.227	8.13	122.958	6.1898	123.138	4.344	127.35	10.905

SD: Standard deviation, SNA: Sella-Nasion-A point, SNB: Sella-Nasion-B point, ANB: A point-Nasion-B point, U1–NA: Upper incisor to Nasion–A line, L1–NB: Lower incisor to Nasion–B line

Table 2: Soft and hard tissue cephalometric measurements of attractive Iranian females classified by age.

Cephalometric Parameter	7–10 years old		11–14 years old		15–18 years old		>18 years old
	SD	Mean	SD	Mean	SD	Mean	SD	Mean
Legan and Burstone
Facial convexity (contour) angle°	17.583	4.828	17.1	4.322	17.775	4.414	15.642	3.992
Maxillary prognathismmm	2.758	3.848	4.733	2.82	4.192	3.228	5.592	3.228
Mandibular prognathismmm	−9.083	6.021	−5.933	6.239	−8.008	7.893	−4	4.373
Vertical height ratio	1.041	0.108	1.05	0.1	1.05	0.138	1.05	0.116
Lower facial throat angle°	105.142	5.467	104.317	7.017	107.792	3.61	106.467	6.005
Lower vertical height–depth ratio	1.117	0.083	1.108	0.144	1.275	0.121	1.217	0.152
Nasolabial angle°	115.208	9.228	111.183	8.623	111.625	8.615	109.6	10.375
Upper lip protrusionmm	3.942	1.413	3.667	0.967	3.725	1.478	4.15	1.618
Lower lip protrusionmm	3.208	2.173	3.358	1.51	3.875	1.056	2.742	2.5
Mentolabial sulcus depthmm	−4.267	1.089	−5.408	1.704	−5.025	1.082	−5.225	0.679
Vertical lip chin ratio	0.49	0.069	0.51	0.025	0.47	0.071	0.5	0.045
Maxillary incisor exposuremm	2.492	1.576	2.875	1.399	4.217	1.626	2.433	1.872
Interlabial gapmm	1.717	0.579	2.392	1.362	2.783	2.153	1.742	0.579
Holdaway
Soft-tissue facial angle°	88.733	3.821	89.992	3.214	90.533	4.135	89.85	2.71
H angle°	17.617	3.634	16.758	2.63	16.983	3.339	16.092	2.799
Nose prominencemm	11.075	3.933	12.667	1.967	12.858	3.422	13.092	1.731
Superior sulcus depthmm	2	0.802	2.3	0.92	2.442	1.022	2.842	0.764
Soft-tissue subnasale to H linemm	5.158	1.759	4.817	1.127	4.8	1.804	5.358	2.058
Skeletal profile convexitymm	2.667	1.089	1.883	2.593	2.417	2.124	2.383	1.733
Basic upper lip thicknessmm	14.792	1.67	15.95	2.465	15.692	1.099	15.85	1.765
Upper lip strain measurementmm	11.25	1.358	12.175	1.509	12.042	2.358	12.375	1.669
Lower lip to H linemm	1.117	1.85	1.5	1.437	1.975	1.13	0.525	1.911
Inferior sulcus to H linemm	3.725	1.247	4.667	1.524	3.992	1.256	5	1.278
Soft-tissue chin thicknessmm	10.358	2.226	11.692	1.871	11.217	2.23	11.75	1.68
Ricketts
Lower lip to E-planemm	0.192	2.667	−0.1	1.831	0.367	1.305	−1.167	2.491
Upper lip to E-planemm	−1.575	2.31	−2.925	1.287	−3.017	1.886	−3.15	1.24
Steiner
SNA	79.475	3.593	79.142	2.536	79.458	3.821	81.55	2.55
SNB	75.1	3.92	76.342	3.015	76.308	3.61	78.292	2.537
ANB	4.842	3.005	2.825	2.778	3.175	1.924	3.242	1.431
Occlusal plane to SN angle	18.317	3.208	16.242	4.004	17.942	5.651	14.383	3.285
Mandibular plane angle	33.15	3.942	31.825	3.593	33.758	5.092	30.642	4.404
U1-NA angle	22.417	8.549	23.642	8.444	21.642	5.972	20.325	6.149
U1-NA distance	4.15	2.886	5.25	2.742	5.183	2.302	4.233	2.079
L1-NB angle	26.625	6.65	27.667	6.728	29.425	3.929	25.467	3.597
L1-NB distance	5.75	4.07	5.475	2.036	6.267	1.648	4.55	1.589
Interincisal angle	126.133	11.964	125.858	10.778	125.783	6.647	130.967	8.525

SNA: Sella-Nasion-A point, SNB: Sella-Nasion-B point, ANB: A point-Nasion-B point, U1–NA: Upper incisor to Nasion–A line, L1–NB: Lower incisor to Nasion–B line

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Figure 3:

Cephalometric templates for males in each age group. (a) 7–10 years old. (b) 11–14 years old. (c) 15–18 years old. (d) >18 years old. In each row, the middle template is the average profile size, the left is one standard deviation (SD) smaller, and the right is one SD larger. Pictures are 25% of their real size. Black line: average pixel size, blue line: Half SD smaller, pink line: Half SD larger.

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Figure 4:

Cephalometric templates for females in each age group. (a) 7–10 years old. (b) 11–14 years old. (c) 15–18 years old. (d) >18 years old. In each row, the middle template is the average profile size, the left is one standard deviation (SD) smaller, and the right is one SD larger. Pictures are 25% of their real size. Black line: average pixel size, blue line: half SD smaller, pink line: half SD larger.

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DISCUSSION

In contemporary orthodontics, cephalometric templates serve various functions.^[2] While numerous templates incorporating cephalometric norms have been created,^[3,10,11] there is a lack of extensive research on templates that assess facial profiles using lateral cephalograms. Therefore, this study was conducted to develop templates based on the means and SDs derived from the lateral cephalograms of the top 20% most attractive patients, categorized into four different age groups.

No universally agreed on reference point or line exists for superimposing lateral cephalograms to ensure precise and standardized evaluations. While the SN line was considered as a reference in the current study, Akhoundi et al.^[16] implemented two different reference lines for cephalometric superimposition: SN and Basion–Nasion (Ba-N). It was observed that the choice of the reference line, whether SN or Ba-N, did not affect the template’s outcome, as all points would rotate or translate in unison on altering the reference line. The same finding was reported by Chalipa et al.^[11] when designing craniofacial templates for 8–14-year-old Iranian girls. As endorsed by Bookstein, the superimposition method does not impact measurement accuracy, and clinicians have the flexibility to choose any technique.^[17] The ease of tracing, the unique positioning of S and N points, and the SN line’s location within the cranial base range might encourage clinicians to favor this reference line over others.

Another noteworthy aspect of the current study is the provision of templates for subjects within the same age group but with varying SN distances, which represent profile size. This approach offers several advantages over previous methods. By accounting for differences in SN distance within the same age group, the templates allow for a more precise and individualized representation of craniofacial characteristics. Unlike previous studies, where subjects with larger SN distances had to rely on templates from older age groups that could lead to inaccuracies, this study ensures a more precise and age-appropriate representation. Such an improvement enhances the reliability and applicability of the templates in clinical and research settings, providing a more refined tool. The use of trained senior dental students for preliminary cephalometric tracing has been validated in our previously published reliability investigation, where the same examiners demonstrated good to excellent ICC values across most cephalometric parameters.^[15] This approach is consistent with methods used in large-scale cephalometric research, where calibrated examiners perform standardized initial tracings and specialists conduct final verification. In the present study, all landmarking was subsequently reviewed by a senior orthodontist, ensuring both efficiency in handling a large dataset and specialist-level diagnostic accuracy.

To the best of our knowledge, existing cephalometric templates do not include SDs for cephalometric values, resulting in a simplistic binary outcome of either conforming to or deviating from established norms.^[3,10,11] On the contrary, our approach was to incorporate SDs along with mean values to provide a spectrum that determines whether measurements align with defined norms. While manually traced templates can assess dentofacial features, forecast growth, and assist in diagnoses, digital templates can effectively demonstrate average changes, thereby enhancing the evaluation of treatment outcomes.^[3] Moreover, the pixel-based measurements in digital templates provide greater precision than manual evaluations, which are based on millimeters. Although some variables demonstrated wider SD ranges (4–10°), these values represent the inherent biological variability within the most attractive 20% of each age–sex group, rather than random or systematic tracing errors. This interpretation is supported by our previously validated reliability study, where the same examiners demonstrated good to excellent intra- and inter-examiner ICC values across most cephalometric variables.^[15] Accordingly, the SD ranges in our tables reflect clinically meaningful diversity in esthetically acceptable facial morphology, not inconsistency in landmark identification.

The templates developed in this research contain soft-tissue boundaries for a more comprehensive assessment. Adhering to the soft-tissue paradigm, the foremost objective of a modern clinician should be to attain an occlusal and facial condition that optimally serves each patient’s specific needs. Given that soft tissues significantly dictate the boundaries of orthodontic therapy in terms of functionality, stability, and esthetics, it is imperative for the clinician to strategize the treatment in accordance with the patient’s limits of soft-tissue adaptation and contours.^[18] Furthermore, we tried to display the created templates in the form of actual facial profiles rather than mere basic lines and dots. This approach aims to enhance understanding and provide a more straightforward explanation for dental students, patients undergoing treatment, and parents.

In the current study, laypeople evaluated subjects’ attractiveness by scoring their profiles. There is an ongoing debate in the literature about the appropriateness of involving laypeople in judging facial attractiveness. Some researchers believe that laypeople may assess attractiveness based on subjects’ facial features rather than their profile.^[19] Lima et al.^[20] resulted in more criticism among dental professionals regarding esthetic evaluations compared to non-professionals, while Zange et al.^[21] indicated that laypeople are often more stringent in their esthetic judgments. Ren et al.^[22] discovered that laypeople consider the chin as the key determinant of facial attractiveness, whereas orthodontists focus more on the lips. However, regardless of the referees’ specialty, teeth contributed less to facial attractiveness compared to lips and chin. This suggests that if the clinician concentrates solely on dental corrections without considering soft tissue, the enhancement in the patient’s facial attractiveness might be minimal.^[22]

Although this study focuses on one ethnicity, it is essential to recognize that beauty standards are increasingly influenced by global factors, resulting in cross-cultural convergence. As Raggio and Adamson^[23] discuss, beauty is both a biological and sociocultural construct shaped by factors such as globalization, immigration, and the rapid dissemination of beauty ideals through social media. These influences have accelerated the evolution of beauty standards worldwide, allowing certain esthetic ideals, such as symmetry, youthfulness, and sexual dimorphism, to gain recognition across various cultural contexts. Moreover, artificial beauty standards, propagated through media, reinforce shared ideals that transcend cultural boundaries. Consequently, while this research is based on the perspectives of a single ethnicity, its findings may reflect a global trend toward universally accepted beauty ideals. Such a perspective underscores the importance of understanding attractiveness within a framework that acknowledges the dynamic and interconnected nature of global beauty standards.

Several artificial intelligence models have recently been developed to quickly assess patients’ cephalograms and rapidly calculate cephalometric values.^[24] Although these models are beneficial for diagnosing profile problems and selecting a suitable treatment plan in minimal time, they may not serve as a convenient tool for educating dental students or patients. For instance, templates could be used to demonstrate to patients the step-by-step correction of their orthodontic problems throughout their treatment and to help students understand the deviation of a patient’s current condition from cephalometric norms.

In terms of limitations, longitudinal studies that track children from a younger age and monitor their cephalograms through various growth stages could yield more robust results. Although this study has a cross-sectional design, it is interesting that the generated templates illustrate typical profile changes associated with growth in both soft and hard tissues. Regarding hard tissues, an increase in the Sella-Nasion-B point (SNB) angle, mandibular length, and maxillary length with age was observed. Regarding soft tissues, raters in this study found larger noses more acceptable in older individuals, aligning with the natural growth progression of the nose. In addition, the distances from both the upper and lower lips to the E-plane reduced as age increased, consistent with mandibular development and the increased prominence of the nose in older adults. Moreover, the subjects’ profiles in this study were evaluated using two-dimensional photographs, whereas assessments in three dimensions might lead to different findings. An alternative method could involve referees scoring subjects based on in-person assessments or video recordings, followed by taking lateral cephalograms from those deemed most attractive. Another limitation arises from the fact that the data were collected from individuals who sought orthodontic treatment, rather than from the general population. However, given the ethical concerns around exposing healthy individuals to radiographs purely for research purposes, this approach was necessary. The researchers addressed this limitation by ensuring the data had a normal distribution, suggesting that, despite the selection bias, the sample could still reasonably represent the general population’s characteristics.^[13]

CONCLUSION

In this article, 24 desirable facial profile templates were presented, tailored for four age groups within each sex and in three different profile sizes. These templates can be specifically selected for a subject based on age, SN distance, and sex, while incorporating soft-tissue boundaries in their design. These templates can be invaluable not only for orthodontists and general dentists in formulating treatment plans but also for dental students and parents in understanding and demonstrating treatment needs. Nevertheless, the reliability and validity of template-based diagnosis must be verified through further studies and testing on more cephalograms.

Notably, soft-tissue characteristics in attractive profiles diverged from traditional norms, with males showing fuller upper lips, prominent chins, and angular lower faces, while females displayed more convex profiles with reduced nasal prominence. Hard tissue analysis revealed a preference for mild skeletal convexity in females and skeletal harmony in males. Age and sex differences further influenced facial esthetics, reinforcing the need for personalized, age-appropriate diagnostic criteria.