Craniofacial growth prediction models based on cephalometric landmarks in Korean and American children.

Jong-Hak Kim, Jun-Ho Moon, Jeffrey Roseth, Heeyeon Suh, Heesoo Oh, Shin-Jae Lee
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Abstract

Objectives: To compare differences in craniofacial growth prediction results for Korean and American children according to growth prediction models developed using Korean and American longitudinal growth data.

Materials and methods: Growth prediction models based on cephalometric landmarks were built for each population using longitudinally taken lateral cephalograms of Korean children and American children of northern European origin. The sample sizes of the serial datasets were 679 and 1257 for Korean and American children, respectively. On each cephalogram, 78 cephalometric landmarks were identified. The prediction models were based on the partial least squares method with 160 input and 154 output variables. For each group, growth was predicted by applying the prediction models developed using data from the same and different populations. The growth prediction results were compared and analyzed.

Results: The growth prediction results obtained with the prediction model developed using data from the same population were more accurate (P < .0001). The results distinctively visualized the discrepancies in the growth prediction results if different population types were not considered.

Conclusions: Applying a growth prediction model generated using data from the same population may be desirable.

基于头颅测量标志的韩国和美国儿童颅面生长预测模型。
目的:比较韩国和美国儿童颅面生长预测结果的差异:根据使用韩国和美国纵向生长数据建立的生长预测模型,比较韩国和美国儿童颅面生长预测结果的差异:利用纵向拍摄的韩国儿童和北欧裔美国儿童的侧位头颅照片,分别建立了基于头颅测量标志的生长预测模型。韩国和美国儿童的序列数据集样本量分别为 679 个和 1257 个。在每张头像照片上,都确定了 78 个头测地标。预测模型基于偏最小二乘法,有 160 个输入变量和 154 个输出变量。对于每个组别,通过使用相同和不同人群的数据所建立的预测模型来预测其生长情况。对生长预测结果进行了比较和分析:结果:使用相同种群数据开发的预测模型得出的生长预测结果更为准确(P < .0001)。如果不考虑不同的人群类型,结果会明显反映出生长预测结果的差异:结论:使用同一人群数据生成的生长预测模型可能是可取的。
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