Original article
3D stereophotogrammetry versus traditional craniofacial anthropometry: Comparing measurements from the 3D facial norms database to Farkas's North American norms

https://doi.org/10.1016/j.ajodo.2018.06.018Get rights and content

Highlights

  • Soft-tissue facial norms differ by measurement method—3D versus traditional anthropometry.

  • Large differences between normative datasets involve measures from all facial regions.

  • One must consider the collection method when using facial norms for comparisons.

Introduction

Datasets of soft-tissue craniofacial anthropometric norms collected with the use of different methods are available, but there is little understanding of how the measurements compare. Here we compare a set of standard facial measurements between 2 large datasets: the 3D Facial Norms (3DFN) dataset collected with the use of 3D stereophotogrammetry (n = 2454), and the Farkas craniofacial norms collected with the use of direct anthropometry (n = 2326).

Methods

A common set of 24 craniofacial linear distances were compared by computing standardized effect sizes (Cohen d) for each measurement to describe the overall direction and magnitude of the difference between the 2 datasets.

Results

Variables with higher mean d values (suggesting greater discrepancy across datasets) included measurements involving the ear landmark tragion, the landmark nasion, the width of nasolabial structures, the vermilion portion of the lips, and palpebral fissure length. Variables with lower mean d values included smaller midline measurements involving the lips and lower face and horizontal distance measures between the eyes. Eight measurements showed a significant negative correlation (P < 0.05) between Cohen d and age, indicating greater similarity across the 2 datasets as age increased.

Conclusions

There are considerable differences between the 3DFN and Farkas norms. In addition to the measurement methods, other factors accounting for discrepancies may include secular trends in craniofacial morphology or differences in ethnic composition.

Section snippets

Material and methods

The 3DFN dataset is composed of 2454 unrelated individuals of self-reported European ancestry: 952 male and 1502 female. These participants were recruited from 2010 to 2013 from the general population at 4 US sites: Pittsburgh, Pa; Seattle, Wash; Houston, Texas; and Iowa City, Iowa. The full dataset is composed of male and female subjects ranging in age from 3 to 40 years. As described in detail elsewhere,9 all of the participants were screened for any personal or family history of medical

Results

The observed mean d values varied considerably across the 24 measurements and are shown as a forest plot in Figure 2. For half of the measurements, the mean d value was positive (meaning the measurement was larger in 3DFN than in Farkas). Variables with large and moderate d values—suggesting greater discrepancy across datasets—included those measurements involving the ear landmark tragion (eg, measures of facial depth), the landmark nasion (eg, measures of facial height), the width of central

Discussion

The results indicate that, although some facial measurements showed reasonably good concordance between the 3DFN and Farkas normative datasets, many other measurements showed large discrepancies. All measurements, except perhaps 5 with very small mean effect sizes, showed differences great enough to warrant caution in how these craniofacial norms should be used. Of the 24 measurements compared, one-half were larger and one-half were smaller in the 3DFN dataset compared with the Farkas dataset.

Conclusions

Of the 24 facial measurements investigated, all but a handful showed meaningful differences between the 3DFN and Farkas normative datasets, with more than half showing moderate-to-large effect sizes (d ≥ 0.50). These differences were not systematically biased in any direction; one half of the measurements were larger and the other half smaller in the 3DFN dataset. Although many of the differences noted here may be related to the method of measurement (3D image–based indirect versus

Data availability statement

The individual-level measurements and raw 3D surface images for all participants in the 3DFN dataset are available through the controlled-access FaceBase repository (https://www.facebase.org/). In addition, genotypic markers for these individuals are available to the research community through the dbGaP controlled-access repository (https://www.ncbi.nlm.nih.gov/gap) at accession number: phs000949.v1.p1. The summary statistics for the Farkas dataset are published and publically available.23

Acknowledgments

The author thanks Zachary D. Raffensperger and Raquel S. Sandoval for their assistance with data collection and Michael L. Cunningham, Carrie L. Heike, Jacqueline T. Hecht, George L. Wehby, Lina M. Moreno, and Mary L. Marazita for their assistance with the 3DFN project.

References (32)

  • M.J. Kesterke et al.

    Using the 3D Facial Norms Database to investigate craniofacial sexual dimorphism in healthy children, adolescents, and adults

    Biol Sex Differ

    (2016)
  • S.M. Weinberg et al.

    Hypertelorism and orofacial clefting revisited: an anthropometric investigation

    Cleft Palate Craniofac J

    (2017)
  • J.C. Kolar et al.

    Craniofacial anthropometry: practical measurement of the head and face for clinical, surgical and research use

    (1997)
  • S.M. Weinberg et al.

    The 3D Facial Norms database: part 1. A web-based craniofacial anthropometric and image repository for the clinical and research community

    Cleft Palate Craniofac J

    (2016)
  • J.R. Shaffer et al.

    Genome-wide association study reveals multiple loci influencing normal human facial morphology

    PLoS Genet

    (2016)
  • M.K. Lee et al.

    Genome-wide association study of facial morphology reveals novel associations with FREM1 and PARK2

    PLoS One

    (2017)
  • Cited by (13)

    View all citing articles on Scopus

    The author has completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest, and none were reported.

    Funding: National Institute of Dental and Craniofacial Research (U01-DE020078; R01-DE016148) and Centers for Disease Control and Prevention (R01-DD000295). The funders played no part in the design or execution of the work presented here, and the content is solely the responsibility of the author.

    View full text