Picture Perfect? Reliability of Craniofacial Anthropometry Using Three-Dimensional Digital Stereophotogrammetry

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Abstract

Background:

Quantification of facial characteristics is important for research in dysmorphology, otolaryngology, oral and maxillofacial, and plastic surgical disciplines, among others. Three-dimensional surface imaging systems offer a quick and practical method for quantifying craniofacial variation and appear to be highly reliable. However, some sources of measurement error have not yet been thoroughly evaluated.

Methods:

The authors assessed the reliability of using stereophotogrammetry for measuring craniofacial characteristics in 40 individuals, including 20 without craniofacial conditions and 20 with 22q11.2 deletion syndrome. The authors recruited staff and relatives of staff, and individuals with a laboratory-confirmed 22q11.2 deletion. Thirty anthropometric measurements were obtained on participants and on three-dimensional images.

Results:

Intrarater and interrater reliability for most interlandmark distances on three-dimensional images had intraclass correlation coefficients greater than 95 percent, mean absolute differences of less than 1 mm, relative error measurement less than 5, and technical error of measurement less than 1 mm. The Pearson correlation coefficients of greater than 0.9 for most distances suggest high intermethod reliability between direct and image-based measurements. Three-dimensional image-based measurements were systematically larger for the head length and width, forehead, and skull base widths, and upper and lower facial widths.

Conclusions:

This study provides further evidence of the high reliability of three-dimensional imaging systems for several craniofacial measurements, including landmarks and interlandmark distances not included in previous studies. The authors also discuss possible errors introduced with palpable landmarks and when working with less compliant participants, such as children. The authors offer guidelines for establishing protocols that can be tailored to each population and research question to maximize the accuracy of image-based measurements.

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