Wellens Hans L L, Kuijpers-Jagtman Anne M
Department of Orthodontics and Craniofacial Biology, Radboud University Nijmegen Medical Centre, The Netherlands
Department of Orthodontics and Craniofacial Biology, Radboud University Nijmegen Medical Centre, The Netherlands.
Eur J Orthod. 2016 Dec;38(6):569-576. doi: 10.1093/ejo/cjv096. Epub 2016 Jan 5.
The combination of generalized Procrustes superimposition (GPS) and principal component analysis (PCA) has been hypothesized to solve some of the problems plaguing traditional cephalometry. This study demonstrates how to establish the currently unclear relationship between the shape space defined by the first two principal components to the ANB angle, Wits appraisal, and GoGnSN angle, and to elucidate possible clinical applications thereof.
Digitized landmarks of 200 lateral cephalograms were subjected to GPS and PCA, after which the sample mean shape was deformed along/parallel to principal components (PC) 1 and 2, recording the ANB, Wits, and GoGnSN value at each location. Trajectories were then calculated through the PC1-PC2 space connecting locations with the same values. These were finally utilized to renormalize the PC1-PC2 space.
The trajectories for the Wits appraisal were almost straight and parallel to PC1.Those for the ANB angle were angled approximately 20degrees downward relative to PC1, with a more accentuated curvature. The GoGnSN curves were mildly angled relative to the PC2 axis, their curvature increasing slightly with increasing PC1 scores. By combining the aforementioned trajectories, it was possible to delineate the region of the PC1-PC2 shape space which would be regarded as normodivergent and skeletal Class I in traditional cephalometry. Geometric distortion could be avoided by assigning patients the ANB, Wits, or GoGnSN value of the sample mean shape, deformed to the patient's position within the PC1-PC2 plot.
The methodology successfully relates the shape space resulting from the GPS-PCA results with traditional cephalometric variables.
有人假设广义普洛透斯叠加（GPS）和主成分分析（PCA）相结合可以解决困扰传统头影测量的一些问题。本研究展示了如何建立由前两个主成分定义的形状空间与ANB角、Wits值和GoGnSN角之间目前尚不清楚的关系，并阐明其可能的临床应用。
对200张头颅侧位片的数字化标志点进行GPS和PCA分析，然后将样本平均形状沿主成分（PC）1和2方向或与其平行方向变形，记录每个位置的ANB、Wits和GoGnSN值。接着通过PC1-PC2空间计算连接具有相同值的位置的轨迹。这些轨迹最终用于对PC1-PC2空间进行重新归一化。
Wits值的轨迹几乎是直的，且与PC1平行。ANB角的轨迹相对于PC1向下倾斜约20度，曲率更大。GoGnSN曲线相对于PC2轴有轻微倾斜，其曲率随着PC1分数的增加而略有增加。通过结合上述轨迹，可以描绘出PC1-PC2形状空间中在传统头影测量中被视为正常发散和骨骼I类的区域。通过为患者指定样本平均形状的ANB、Wits或GoGnSN值，并将其变形到患者在PC1-PC2图中的位置，可以避免几何失真。
该方法成功地将GPS-PCA结果产生的形状空间与传统头影测量变量联系起来。
