Evidence map›Paper›PMID 41735422›Full record

ArticleScientific reports2026

Principal component analysis of 3-dimensional facial soft-tissue morphology in three adult populations.

Chung H Kau, Peter Borbely, Alexei Zhurov, Jolaiya Oguntoba

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Chung H Kau *Department of Orthodontics, School of Dentistry, University of Alabama at Birmingham, 1919 7th Avenue South, SDB 313, Birmingham, AL, 35294- 0007, USA. ckau@uab.edu.
Peter Borbely *Department of Orthodontics, University of Szeged, Szeged, Hungary, Faculty of Dentistry at the University of Szeged, H-6720.
Alexei Zhurov *Department of Mathematics , Russian Academy of Sciences, Moscow, Russia.
Jolaiya Oguntoba *Department of Orthodontics, School of Dentistry, University of Alabama at Birmingham, 1919 7th Avenue South, SDB 313, Birmingham, AL, 35294- 0007, USA. oguntoba@uab.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

FaceImaging, Three-DimensionalPrincipal Component AnalysisAdultFemaleHumansMalePhotogrammetryYoung AdultAnthropometryComputer-assistedCraniofacial morphologyEthnic groupsFacial aestheticsFacial landmarkingFacial soft tissue variationImage processingMultivariate analysisOrthodonticsPersonalized orthodonticsPrincipal component analysisSoft tissueStereophotogrammetryThree-dimensional imaging

Identifiers

PMID41735422
PMCPMC13031976

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.