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.
The proposed project characterizes the effects of rare craniofacial anomalies on the growth and integration of the craniofacial complex. Advanced statistical techniques will be used to model growth curves for three- dimensional measures of the skull that will be compared between individuals with different craniofacial diagnoses and individuals with craniofacial morphology within the normal range of variation. The results will generate an improved understanding of divergent growth patterns associated with craniofacial anomalies and will contribute to the ability of clinicians to determine the appropriate direction and timing of treatment.
