RESUMO
PURPOSE: The increasing popularity of cosmetic surgery and its effect on facial recognition software has attracted the attention of many researchers. Indeed, after having undergone cosmetic surgery procedures, nonlinear modifications that are made to facial biometric landmarks may lead to difficulty in recognizing individuals, who received a surgery, by facial biometric systems. This finding motivated us to discuss this topic differently and take advantage of these modifications to objectively study the results of cosmetic surgery. In this study, we propose facial biometry as a new method to objectively describe face changes after facelift surgery. PATIENTS AND METHODS: For this study, 37 women, aged between 50 and 80 years old, were selected. These patients underwent facelift surgery between January 2013 and December 2017. For comparison of the biometric facial features before and after facelift surgery, 7 direct measurements (4 linear and 3 angular) were performed. RESULTS: There was no significant difference between real and preoperative apparent age as per the face recognition software: (63.35 years +/- 6.52 vs 64.54 years +/- 7.49, P = .188 > 0.05). The postoperative apparent age was significantly lower than the preoperative apparent age as per the face recognition software (58.97 years +/- 7.19 vs 64.54 years +/- 7.49; P < 10-3). We found a statistically significant increase in the mean of the 3 ratios of the linear measures and a statistically significant modification in the means of the 3 angular measurements. CONCLUSIONS: Biometry enabled us to evaluate the preoperative and postoperative facial features of patients before and after facelift surgery and to determine objectively whether the estimated age was improved by the surgery.
