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dc.contributor.authorBotchevar, Ellaen_US
dc.date.accessioned2018-01-18T15:18:32Z
dc.date.available2018-01-18T15:18:32Z
dc.date.issued2017
dc.identifier.urihttps://hdl.handle.net/2144/26204
dc.description.abstractBACKGROUND: Orthodontists rely heavily on cephalometric analysis to assess growth potential and direction. Geometric morphometrics examines shape and can help the clinician reach more accurate diagnoses and predict future growth. PURPOSE: The aims of this study are: 1) Determine principle components describing craniofacial shape changes; 2) Assess shape changes in growing subjects; 3) Develop a model for craniofacial growth prediction using geometric morphometrics. RESEARCH DESIGN: The Cranial base, maxilla and mandible were digitized on 330 lateral cephalograms from ages 6-16 (n=33). Generalized Procrustes analysis was performed on the longitudinal data sample. Principle Component, Discriminant Function and Two-Block Partial Least Squares analysis were assessed against changes in individual structures to determine if changes in the maxillary, mandibular or cranial base are related to changes in shape of the overall craniofacial form. RESULTS: PCA shows that the first six principle components account for 67.7 – 77.0% of the observed shape variance in each region and 56.0% of the whole form. Multivariate regression analysis predicts the shape of the entire craniofacial complex at 16 years old based on the shape observed at 6 years old with 94% certainty. An intraclass correlation coefficient of 0.98 confirms reliability. CONCLUSION: Morphometric analyses indicate that changes in maxillofacial morphology during skeletal maturation are linear. The shape of the craniofacial complex does not change significantly and growth pattern is maintained. Our model can predict the craniofacial shape at 16 years of age based on the shape observed at 6 years of age.en_US
dc.language.isoen_US
dc.subjectDevelopmental biologyen_US
dc.subjectProcrustesen_US
dc.subjectGeometric morphometricsen_US
dc.subjectGrowth and developmenten_US
dc.subjectGrowth predictionen_US
dc.titleA morphometric approach to facial growth predictionen_US
dc.typeThesis/Dissertationen_US
dc.date.updated2017-10-25T18:32:40Z
etd.degree.nameMaster of Science in Designen_US
etd.degree.levelmastersen_US
etd.degree.disciplineOrthodontics and Dentofacial Orthopedicsen_US
etd.degree.grantorBoston Universityen_US


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