Abstract
This preliminary study aims to identify soft tissue facial morphological features that vary among ethnically diverse, facially balanced adults using Principal Component Analysis (PCA) of 3D facial scans. A total of 210 3D facial scans (35 per subgroup: Chinese, Hungarian, and Hispanic; stratified by sex) were selected from a database at the University of Alabama. Facial scans were captured using 3D-laser scanning and stereophotogrammetry (3dMD). A total of 57 landmarks were manually placed on each scan. The landmark coordinates were analyzed using Generalized Procrustes Analysis and PCA (conducted in R) to identify principal components contributing most significantly to shape variation. PCA identified four principal components (PCs) accounting for 77.72% of the total variance in soft tissue morphology. PC1 (49.13%) was associated with upper facial height. PC2 (17.70%) reflected the spatial relationship between nose protrusion and eye position. PC3 (6.31%) corresponded to interocular distance and vertical eye placement. PC4 (4.14%) represented upper lip protrusion. These PCs showed that the greatest morphological variability was in the upper facial region. Observed differences were interpreted within clinical and aesthetic contexts and were consistent with findings from prior literature on facial development and attractiveness. Significant variations in upper facial soft tissue morphology exist among normal adult subjects from different ethnic backgrounds. This study demonstrates the utility of PCA in revealing clinically relevant patterns in facial morphology and highlights the importance of individualized, ethnically sensitive treatment planning in orthodontics and orthognathic surgery. Future longitudinal and AI-driven studies are recommended to refine personalized diagnostics and develop inclusive aesthetic standards.
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This study was initiated by the investigator. All data supporting the study’s conclusions are included in the article . The raw data underlying these findings can be obtained from the corresponding authors upon request.
References
Kau, C. H., Zhurov, A., Scheer, R., Bouwman, S. & Richmond, S. The feasibility of measuring three-dimensional facial morphology in children. Orthod. Craniofac. Res. 7 (4), 198–204 (2004).
Kau, C. H., English, J. D., Gor, T., Lee, R. P. & Borbelye, P. Three-dimensional comparison of facial morphology in white populations in Budapest, Hungary, and Houston, Texas. Am. J. Orthod. Dentofac. Orthop. 137 (Issue 3), 424–432 (2010).
Marmulla, R., Hassfeld, S., Lüth, T. & Mühling, J. Laser-scan-based navigation in cranio-maxillofacial surgery. J. Craniomaxillofac. Surg. 31 (5), 267–277 (2003).
Ji, Y., Zhang, F., Schwartz, J., Stile, F. & Lineaweaver, W. C. Assessment of facial tissue expansion with three-dimensional digitizer scanning. J. Craniofac. Surg. 13 (5), 687–692 (2002).
McCance, A. M., Moss, J. P., Fright, W. R., Linney, A. D. & James, D. R. Three-dimensional analysis techniques–Part 1: Three-dimensional soft-tissue analysis of 24 adult cleft palate patients following Le Fort I maxillary advancement: a preliminary report. Cleft Palate Craniofac. J. 34 (1), 36–45 (1997).
McCance, A. M., Moss, J. P., Wright, W. R., Linney, A. D. & James, D. R. A three-dimensional soft tissue analysis of 16 skeletal class III patients following bimaxillary surgery. Br. J. Oral Maxillofac. Surg. 30 (4), 221–232 (1992).
Nute, S. J. & Moss, J. P. Three-dimensional facial growth studied by optical surface scanning. J. Orthod. 27 (1), 31–38 (2000).
Fatemifar, G. et al. Genome-wide association study of primary tooth eruption identifies pleiotropic loci associated with height and craniofacial distances. Hum. Mol. Genet. 22 (18), 3807–3817 (2013).
Paternoster, L. et al. Genome-wide association study of three-dimensional facial morphology identifies a variant in PAX3 associated with nasion position. Am. J. Hum. Genet. 90 (3), 478–485 (2012).
Hennessy, R. J., McLearie, S., Kinsella, A. & Waddington, J. L. Facial surface analysis by 3D laser scanning and geometric morphometrics in relation to sexual dimorphism in cerebral–craniofacial morphogenesis and cognitive function. J. Anat. 207 (3), 283–295 (2005).
Majid, Z., Chong, A. K. & Setan, H. Important considerations for craniofacial mapping.
Kau, C. H., Richmond, S., Incrapera, A., English, J. & Xia, J. J. Three-dimensional surface acquisition systems for the study of facial morphology and their application to maxillofacial surgery. Int. J. Med. Robot. 3 (2), 97–110 (2007).
Bookstein, F. Morphometric Tools for Landmark Data: Geometry and Biology (Cambridge University Press, 1992).
Souccar, N. M. & Kau, C. H. Methods of Measuring the Three-Dimensional Face. Semin. Orthod. 18 (3), 187–192 (2012).
Farnell, D. J. J. et al. Multilevel principal components analysis of three-dimensional facial growth in adolescents. Comput. Methods Programs Biomed. 188, 105272 (2020).
Farnell, D. J. J. & Claes, P. Initial steps towards a multilevel functional principal components analysis model of dynamical shape changes. J. Imaging 9 (4). (2023).
Zacharopoulos, G. V. et al. Neoclassical facial canons in young adults. J. Craniofac. Surg. 23 (6), 1693–1698 (2012).
Holdaway, R. A. A soft-tissue cephalometric analysis and its use in orthodontic treatment planning. Part I. Am. J. Orthod. 84 (1), 1–28 (1983).
Farkas, L. G. et al. International anthropometric study of facial morphology in various ethnic groups/races. J. Craniofac. Surg. 16 (4), 615–646 (2005).
McKnight, A., Momoh, A. O. & Bullocks, J. M. Variations of structural components: specific intercultural differences in facial morphology, skin type, and structures. Semin Plast. Surg. 23 (3), 163–167 (2009).
Zhuang, Z. Q. et al. Facial anthropometric differences among gender, ethnicity, and age groups. Ann. Occup. Hyg. 54, 391–402 (2010).
Gibelli, D. et al. 3D facial superimposition between monozygotic twins: a novel morphological approach to the assessment of differences due to environmental factors. Leg. Med. (Tokyo Japan). 31, 33–37 (2017).
Singh, P. et al. Face Structure, Beauty, and Race: A Study of Population Databases Using Computer Modeling. Aesthet. Surg. J. Open. Forum. 5, ojad072. https://doi.org/10.1093/asjof/ojad072 (2023).
Wu, X. J., Liu, W. & Bae, C. J. Craniofacial variation between southern and northern Neolithic and Modern Chinese. Int. J. Osteoarchaeol. 22, 98–109. https://doi-org.uab.idm.oclc.org/10.1002/oa.1190 (2012).
Fang, F., Clapham, P. J. & Chung, K. C. A systematic review of interethnic variability in facial dimensions. Plast. Reconstr. Surg. 127 (2), 874–881. https://doi.org/10.1097/PRS.0b013e318200afdb (2011).
Canoon, J. Craniofacial height and depth increment. Am. J. Orthod. 58, 202–218 (1970).
Richmond, S., Howe, L. J., Lewis, S., Stergiakouli, E. & Zhurov, A. Facial Genetics: A Brief Overview. Front. Genet. 9, 462. https://doi.org/10.3389/fgene.2018.00462 (2018).
Philip, A. Y., Uttam, S., Dale, H. R. & Fred, S. Circles of prominence. Arch. Facial Plast. Surg. 8 (4), 263–267. (2006).
Reid, B. B. Perceptions of facial attractiveness: outcomes of orthognathic surgery. https://digitalcommons.library.uab.edu/etd-collection/2810 (2015).
Asli, H. N. & Khosravi, M. G. Evaluation of the Relationship Between Upper Intercanine and Inner Canthal Distances in Selected Patients. Biosc Biotech. Res. Comm. 10 (2), 143–147 (2017).
Tripathi, S., Singh, R. D., Chand, P., Kumar, L. & Singh Gulshan K1. A Study to Correlate Various Facial Landmarks with Intercanine Distance. Indian J. Dent. Res. 29 (4), 440–444. https://doi.org/10.4103/ijdr.IJDR_80_17 (2018).
Uysal, T., Baysal, A., Yagci, A., Sigler, L. M. & McNamara, J. A. Jr Ethnic differences in the soft tissue profiles of Turkish and European-American young adults with normal occlusions and well-balanced faces. Eur. J. Orthod. 34 (3), 296–301. https://doi.org/10.1093/ejo/cjq165 (2012).
Young, N. M. et al. Facial surface morphology predicts variation in internal skeletal shape. Am. J. Orthod. Dentofac. Orthop. 149 (Issue 4), 501–508 (2016).
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Kau, C.H., Borbely, P., Zhurov, A. et al. Principal component analysis of 3-dimensional facial soft-tissue morphology in three adult populations. Sci Rep (2026). https://doi.org/10.1038/s41598-026-41517-z
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DOI: https://doi.org/10.1038/s41598-026-41517-z


