Establishment of a method for predicting a posed smile from a straight face

Kei Suzuki, Hiroyuki Nakano, Tomohiro Yamada, Sho Mizobuchi, Kousuke Yasuda, Safieh Albouga, Kazuya Inoue, Mayumi Matsumura, Shiho Tajiri, Katsuaki Mishima, Yoshihide Mori, Takaaki Ueno

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Good facial expression is an important goal of orthognathic surgery because facial expression has a considerably greater influence on humans’ aesthetic judgements than facial profile alone. However, to date, no reports have attempted to predict post-operative smiles from straight faces. The aim of this study was to evaluate the effectiveness of different techniques to create a posed smile (virtual) from a straight face (original). Twenty-five volunteers with no medical history that would interfere with a straight face or a posed smile were enrolled. After creating homologous models from the straight face and posed smile models, we assessed the ability of the principal component (PC) method and the improved Manchester (i-M) method to create a posed smile (virtual) from a straight face (original). Positive errors for the PC and i-M were 1.4 ± 0.5 mm, 0.9 ± 0.4 mm, respectively, and there was a significant difference. Although there were significant differences in error, the error of two methods, including homologous modeling techniques and principal component analysis, were clinically small and useful for predicting change in facial expression.

Original languageEnglish
Pages (from-to)221-224
Number of pages4
JournalJournal of Hard Tissue Biology
Issue number3
Publication statusPublished - 2021

All Science Journal Classification (ASJC) codes

  • Medicine (miscellaneous)
  • Biochemistry
  • Biomaterials
  • Orthopedics and Sports Medicine
  • Dentistry(all)
  • Cell Biology


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