Facial surface morphology predicts variation in internal skeletal shape

Abstract

Introduction The regular collection of three-dimensional (3D) imaging data is critical to the development and implementation of accurate predictive models of facial skeletal growth. However, repeated exposure to x-ray based modalities such as cone-beam computed tomography (CBCT) have unknown risks that outweigh many potential benefits, especially in pediatric patient populations. One solution is to make inferences about the facial skeleton from external 3D surface morphology captured using safe non-ionizing imaging modalities alone. However, the degree to which external 3D facial shape is an accurate proxy of skeletal morphology has not been previously quantified. As a first step in validating this approach, here we test the hypothesis that population-level variation in the 3D shape of the face and skeleton significantly covary. Methods We retrospectively analyzed 3D surface and skeletal morphology from a previously collected cross-sectional CBCT database of non-surgical orthodontics patients, and used geometric morphometrics and multivariate statistics to test the hypothesis that shape variation in external face and internal skeleton covary. Results External facial morphology is highly predictive of variation in internal skeletal shape (Rv=0.56, p<0.0001; PLS1-13=98.7% covariance, p<0.001) and asymmetry (Rv=0.34, p<0.0001; PLS1-5=90.2% covariance, p<0.001), while age (r2=0.84, p<0.001) and size-related (r2=0.67, p<0.001) shape variation are also highly correlated. Conclusions Surface morphology is a reliable source of proxy data for the characterization of skeletal shape variation, and thus is particularly valuable in research designs where reducing potential long-term risks associated with radiological imaging methods is warranted. We propose that longitudinal surface morphology from early childhood through late adolescence has the potential to be a valuable source of data that will facilitate the development of personalized craniodental planning and treatment plans while reducing exposure levels to “as low as reasonably achievable” (ALARA).

Midfacial growth patterns in males from newborn to 5 years old based on computed tomography

“…Some authors define an arbitrary threshold for each specimen which allows an apparently better visualization of bone tissue (Bastir & Rosas, ; Delye et al, ; Park, Yu, Kim, Lee, & Baik, ; Heuzé et al, ; Kim et al, ; Stull et al, ; Titiz, Laubinger, Keller, Hertrich, & Hirschfelder, ). Others define one standard threshold for all specimens which can then be manually adjusted to better visualize the anatomy of a particular individual (Anzelmo, Barbeito‐Andres, Ventrice, Pucciarelli, & Sardi, ; Barbeito‐Andrés et al, 2012; Barbeito‐Andres, Anzelmo, Ventrice, Pucciarelli, & Sardi, ; Cavalcanti et al, ; Chen, Por, Liou, & Chang, ; Decker, ; Hassan et al, ; Hwang et al, ; Kragskov et al, ; Morimoto, Ogihara, Katayama, & Shiota, ; Van Cauter et al, ; Young et al, ).…”

Facial shape manifestations of growth faltering in Tanzanian children

“…Surface facial shape from 3D imaging and underlying skeletal morphology are very highly correlated (Young et al. ). Our results suggest that differences in face‐stature allometry across time or among related groups may provide evidence for differences related to growth faltering.…”

Combined soft and skeletal tissue modelling of normal and dysmorphic midface postnatal development

“…These papers provide important evidence supporting virtual planning of surgery but are limited to nonsyndromic adults and adolescents. More recently, Young et al also used CT images to extract soft tissue and skeletal 3D surfaces of the face in patients aged 7 to 58 (n = 175) (Young et al, 2016). Using geometric morphometrics, they analysed skeletal and soft tissue shape to show significant covariation, providing evidence that skeletal shape can be predicted using soft tissue morphology.…”