A tensor analysis to evaluate the effect of high-pull headgear on Class II malocclusions.

The inaccuracies inherent in cephalometric analysis of treatment effects are well known. The objective of this article is to present a more reliable research tool in the analysis of cephalometric data. Bookstein introduced a dilation function by means of a homogeneous deformation tensor as a method of describing changes in cephalometric data. His article gave an analytic description of the deformation tensor that permits the rapid and highly accurate calculation of it on a desktop computer. The first part of this article describes the underlying ideas and mathematics. The second part uses the tensor analysis to analyze the cephalometric results of a group of patients treated with high-pull activator (HPA) to demonstrate the application of this research tool. Eight patients with Class II skeletal open bite malocclusions in the mixed dentition were treated with HPA. A control sample consisting of eight untreated children with Class II who were obtained from The Ohio State University Growth Study was used as a comparison group. Lateral cephalograms taken before and at the completion of treatment were traced, digitized, and analyzed with the conventional method and tensor analysis. The results showed that HPA had little or no effect on maxillary skeletal structures. However, reduction in growth rate was found with the skeletal triangle S-N-A, indicating a posterior tipping and torquing of the maxillary incisors. The treatment also induced additional deformation on the mandible in a downward and slightly forward direction. Together with the results from the conventional cephalometric analysis, HPA seemed to provide the vertical and rotational control of the maxilla during orthopedic Class II treatment by inhibiting the downward and forward eruptive path of the upper posterior teeth. The newly designed computer software permits rapid analysis of cephalometric data with the tensor analysis on a desktop computer. This tool may be useful in analyzing growth changes for research data.