PROJECT SUMMARY
The goal of the proposed postdoctoral fellowship is to provide the candidate, Dr. Hardin, with the
background and skills necessary to become a successful, independent craniofacial researcher with the ability
to translate basic research for clinical application. The proposed research will improve treatment planning for
patients with craniofacial anomalies. Dr. Hardin has organized a multi-disciplinary mentoring team at the
University of Missouri and Case Western Reserve University comprised of clinicians and researchers with
expertise in highly-effective translational biomedical research. The training plan utilizes tailored one-on-one
sessions with mentors, promotes networking with multidisciplinary biomedical researchers, and provides
structured training in research conduct.
Dr. Hardin will use growth curves from high-quality longitudinal 2D data analyzed through the University of
Missouri Craniofacial Growth Study (MUCGS) to model 3D craniofacial growth in individuals with rare
craniofacial anomalies under a Bayesian framework. 2D coordinates (x,y) of cephalometric landmarks from
over 15,000 lateral cephalographs representing 2,049 individuals have been collected through MUCGS, and
the applicant will collect 3D coordinates (x,y,z) of cephalometric landmarks from CBCT images representing 36
individuals with craniofacial anomalies and 64 individuals exhibiting normal craniofacial growth, each with at
least 2 CBCT images collected at least one year apart. Models of normal craniofacial growth based on 2D
cephalometric data will inform growth models of the CBCT data using a Bayesian statistical framework. The
representation of diverse craniofacial anomalies in the sample will allow for comparison of craniofacial growth
parameters. Ontogenetic integration in the skull will be assessed in the population without craniofacial
anomalies and compared to subsamples of individuals with craniofacial anomalies. Through this research, Dr
Hardin will receive detailed methodological training in traditional cephalometric analyses, current approaches
to growth modeling, and the Bayesian statistical framework in the context of craniofacial research.
The proposed research addresses NIDCR’s goal of integrating “basic, clinical, and population science to
devise new tools and approaches to improve oral health.” Characterizing the effects of craniofacial anomalies
on patterns of craniofacial growth will aid clinicians in determining optimal care plans for patients with rare
craniofacial anomalies. The mentoring team assembled by the candidate will provide training in translating this
basic research to improve clinical treatment of craniofacial anomalies, fulfilling NIDCR’s mission to “fund
research training and career development programs to ensure an adequate number of talented, well-prepared,
and diverse investigators.” This research will establish a foundation to evaluate and predict patterns of 3D
craniofacial growth to assist clinicians in providing precise, evidence-based treatment.