Craniofacial morphology is affected by the growth, development, and three-dimensional (3D) relationship of mineralized structures including the skull, jaws, and teeth. Despite fulfilling different purposes within this region, cranial bones and tooth dentin are derived from mesenchymal cells that are affected by perturbations within the TGF-β signaling pathway. encodes a transmembrane receptor that is part of the canonical, SMAD-dependent TGF-β signaling pathway and mutations within this gene are associated with Loeys-Dietz syndrome, a condition which often presents with craniofacial signs including craniosynostosis and cleft palate.
View Article and Find Full Text PDFAm J Orthod Dentofacial Orthop
February 2020
This case report presents the unique treatment of a patient with varying asymmetries at different levels within the face. The patient was a 17-year-old male with a diagnosis of right unilateral coronal synostosis. He had frontal and superior orbital retrusion on the fused side, and bossing of the contralateral side.
View Article and Find Full Text PDFBackground: Age is a frequent consideration for surgical timing in pediatric craniofacial surgery for optimal psychosocial development. However, systematic evaluations of the effects of age in children under active treatment have not been thoroughly evaluated.
Methods: Ninety-nine patients (age, 8 to 17 years; 46.
Advances in precision medicine portend similar progress in orthodontics and will be increasingly harnessed to achieve customized treatment approaches and enhance treatment efficiencies. Our goal is to provide a background on emerging advances in computer technologies and biomedicine and highlight their current and likely future applications to precision orthodontics. A review of orthodontically relevant technologies and advances in pertinent biological research was undertaken.
View Article and Find Full Text PDFOrthod Craniofac Res
June 2017
The recent prevalence of three dimensional (3D) images of soft and hard tissues provides a wealth of new data from which the clinician can evaluate these changes. However, evaluating this new data presents new and significant challenges. Current approaches utilizing multi-dimensional data for the precise evaluation of changes related to treatment and growth sets are reviewed.
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