Longitudinal Modeling of Craniofacial Growth Trajectories

An important aspect of understanding the craniofacial complex is a comprehensive characterization of the growth and development of the structures involved.   I’m pleased to announce that we recently received funding from the National Institute of Dental and Craniofacial Research for a new project “Longitudinal Modeling of Craniofacial Growth Trajectories.”  This project has only just begun.  Below is the abstract describing this project.  More information will be posted as the project progresses.

The ultimate goal of the proposed research project is to conduct a detailed longitudinal analysis of the growth of the craniofacial complex. Precise characterization of ontogenetic trajectories across the functional/developmental components of the craniofacial complex will provide fundamental baseline information to both basic researchers and clinicians. Craniofacial anomalies are among the most common congenital defects. Additionally, the prevalence of orthodontic treatment exceeds 30% according to national averages. The clinical significance of this region is not restricted to physical health as even small variations in anatomy may significantly impact feelings of self-worth. Fortunately, many craniofacial disorders can be successfully treated during childhood with surgical approaches or orthodontic applications. The success of these treatments can be maximized through a comprehensive understanding of craniofacial growth including general patterns of growth, the timing of changes in the rate of development, and the degree of morphological integration during periods of growth.

The proposed study will leverage the considerable resources created by the NIDCR-funded project “Genetic Architecture of the Human Craniofacial Complex”: (R01DE016692; R.J. Sherwood, P.I.). That project collected craniofacial phenotypes from over 9,000 radiographs available as part of the Fels Longitudinal Study, the world's longest study of human growth and development. The proposed research will analyze measurements from the 6,861 of these radiographs taken from the ages of 1 month to 25 years on 779 individuals, each with from 1 to 30 radiographs over the specified age range.

We will use this rich longitudinal data source to thoroughly characterize the growth trajectories of a comprehensive set of 74 craniofacial phenotypes representing basicranial, splanchnocranial, neurocranial, mixed component, and soft tissue traits. Statistical modeling of each trajectory will be accomplished using linear and non-linear mixed models, providing a detailed analysis of the population-average trajectory, the magnitude of variation in individual-level trajectories, and an assessment of secular trends. For diagnostic and prognostic purposes, we will produce population percentile reference standards relative to both chronological and skeletal age using quantile regression, individualized reference percentiles given a past measurement, and prediction of future growth percentiles given a current measurement. Finally, these clinically useful tools will be made accessible via a web-based application.