Young Nathan M, Sherathiya Krunal, Gutierrez Luis, Nguyen Emerald, Bekmezian Sona, Huang John C, Hallgrímsson Benedikt, Lee Janice S, Marcucio Ralph S
Assistant professor, Department of Orthopaedic Surgery, School of Medicine, University of California at San Francisco, San Francisco, Calif.
Resident, Department of Orofacial Sciences, School of Dentistry, University of California at San Francisco, San Francisco, Calif.
Am J Orthod Dentofacial Orthop. 2016 Apr;149(4):501-8. doi: 10.1016/j.ajodo.2015.09.028.
The regular collection of 3-dimensional (3D) imaging data is critical to the development and implementation of accurate predictive models of facial skeletal growth. However, repeated exposure to x-ray-based modalities such as cone-beam computed tomography has unknown risks that outweigh many potential benefits, especially in pediatric patients. One solution is to make inferences about the facial skeleton from external 3D surface morphology captured using safe nonionizing imaging modalities alone. However, the degree to which external 3D facial shape is an accurate proxy of skeletal morphology has not been previously quantified. As a first step in validating this approach, we tested the hypothesis that population-level variation in the 3D shape of the face and skeleton significantly covaries.
We retrospectively analyzed 3D surface and skeletal morphology from a previously collected cross-sectional cone-beam computed tomography database of nonsurgical orthodontics patients and used geometric morphometrics and multivariate statistics to test the hypothesis that shape variation in external face and internal skeleton covaries.
External facial morphology is highly predictive of variation in internal skeletal shape ([Rv] = 0.56, P <0.0001; partial least squares [PLS] 1-13 = 98.7% covariance, P <0.001) and asymmetry (Rv = 0.34, P <0.0001; PLS 1-5 = 90.2% covariance, P <0.001), whereas age-related (r(2) = 0.84, P <0.001) and size-related (r(2) = 0.67, P <0.001) shape variation was also highly correlated.
Surface morphology is a reliable source of proxy data for the characterization of skeletal shape variation and thus is particularly valuable in research designs where reducing potential long-term risks associated with radiologic imaging methods is warranted. We propose that longitudinal surface morphology from early childhood through late adolescence can be a valuable source of data that will facilitate the development of personalized craniodental and treatment plans and reduce exposure levels to as low as reasonably achievable.
定期收集三维(3D)成像数据对于面部骨骼生长精确预测模型的开发和应用至关重要。然而,反复接触基于X射线的成像方式,如锥形束计算机断层扫描,存在未知风险,其风险超过了许多潜在益处,尤其是在儿科患者中。一种解决方案是仅使用安全的非电离成像方式从外部3D表面形态推断面部骨骼。然而,外部3D面部形状作为骨骼形态准确替代指标的程度此前尚未量化。作为验证该方法的第一步,我们检验了面部和骨骼3D形状的群体水平变异显著共变的假设。
我们回顾性分析了先前收集的非手术正畸患者横断面锥形束计算机断层扫描数据库中的3D表面和骨骼形态,并使用几何形态计量学和多变量统计来检验外部面部和内部骨骼形状变异共变的假设。
外部面部形态高度预测内部骨骼形状的变异([Rv]=0.56,P<0.0001;偏最小二乘法[PLS]1-13=98.7%协方差,P<0.001)和不对称性(Rv=0.34,P<0.0001;PLS 1-5=90.2%协方差,P<0.001),而与年龄相关的(r(2)=0.84,P<0.001)和与大小相关的(r(2)=0.67,P<0.001)形状变异也高度相关。
表面形态是用于表征骨骼形状变异的替代数据的可靠来源,因此在有必要降低与放射成像方法相关的潜在长期风险的研究设计中特别有价值。我们提出,从幼儿期到青春期后期的纵向表面形态可以成为有价值的数据来源,这将有助于制定个性化的颅面牙科和治疗计划,并将暴露水平降低到合理可行的最低程度。