摘要
Background An important purpose of orthodontic treatment is to gain the harmonic soft tissue profile. This article describes a novel way to build patient-specific models of facial soft tissues by transforming a standard finite element （FE） model into one that has two stages： a first transformation and a second transformation, so as to evaluate the facial soft tissue changes after orthodontic treatment for individual patients. Methods The radial basis functions （RBFs） interpolation method was used to transform the standard FE model into a patient-specific one based on landmark points. A combined strategy for selecting landmark points was developed in this study： manually for the first transformation and automatically for the second transformation. Four typical patients were chosen to validate the effectiveness of this transformation method. Results The results showed good similarity between the transformed FE models and the computed tomography （CT） models. The absolute values of average deviations were in the range of 0.375-0.700 mm at the lip-mouth region after the first transformation, and they decreased to a range of 0.116-0.286 mm after the second transformation. Conclusions The modeling results show that the second transformation resulted in enhanced accuracy compared to the first transformation. Because of these results, a third transformation is usually not necessary.
Background An important purpose of orthodontic treatment is to gain the harmonic soft tissue profile. This article describes a novel way to build patient-specific models of facial soft tissues by transforming a standard finite element （FE） model into one that has two stages： a first transformation and a second transformation, so as to evaluate the facial soft tissue changes after orthodontic treatment for individual patients. Methods The radial basis functions （RBFs） interpolation method was used to transform the standard FE model into a patient-specific one based on landmark points. A combined strategy for selecting landmark points was developed in this study： manually for the first transformation and automatically for the second transformation. Four typical patients were chosen to validate the effectiveness of this transformation method. Results The results showed good similarity between the transformed FE models and the computed tomography （CT） models. The absolute values of average deviations were in the range of 0.375-0.700 mm at the lip-mouth region after the first transformation, and they decreased to a range of 0.116-0.286 mm after the second transformation. Conclusions The modeling results show that the second transformation resulted in enhanced accuracy compared to the first transformation. Because of these results, a third transformation is usually not necessary.
基金
This study was supported by grants from the National Natural Science Foundation of China
