Classification of Alar Dynamic Aesthetic in an Asian Female Population: Experts or Automatic Algorithms?

im To provide referenced classifications of alar dynamic aesthetics from both subjective and objective perspectives for determining proper surgical strategies in alarplasty. Methods A total of 150 healthy Asian female participants were instructed to perform two standardized facial movements including a resting pose and a maximum smile while taking care not to show their teeth. The participants were recorded using a dynamic three-dimensional surface imaging system. Frames depicting the resting position and the alar maximum enlargement during the smile were exported separately for anthropometric analysis and classification. The alar dynamic aesthetic was assessed through measurement of the anthropomorphic changes comparing the resting and maximum smile statuses and then transformed into quantitative analysis through the algorithm MOBILITY = WIDTH_smile - WIDTH_rest/WIDTH_rest× 100% . Subjective classification and evaluation of the subject cosmetic deficiencies and proposals for therapeutic interventions to improve the subjects’ alar dynamic aesthetic were performed by three senior plastic surgeons through visualization of the resting and smiling images. The surgeons were asked to divide and classify the subjects into three groups (Class I, Class II and Class III) according to the surgeons’ perceptions of degree of the subjects’ deficiencies in alar dynamic aesthetic. The more deficiency there was in the aesthetic, the higher the class that the subject was assigned into. The surgeons were presented with the full set of images of the patients on two separate occasions each three months apart, to assess interobserver reliability. Clustering analysis, which is based on machine learning, was applied for objective classification of the images. Results According to the senior plastic surgeon experts’ subjective classification, the subjects’ alar flaring mobility was judged as follows: Class I (6.78 ± 3.84