Advertisement

Biometry, a New Method to Objectively Evaluate Results After Facelift Surgery

  • Jed Bouguila
    Correspondence
    Address correspondence and reprint requests to Dr Bouguila: Department of ENT, Maxillo-Facial and Aesthetic Surgery. La Rabta Academic Hospital, Tunis 1007, Tunisia
    Affiliations
    Associate Professor, La Rabta Hospital, Tunis, Tunisia Ibn Aljazzar Medical School, Sousse, Tunisia Tunis Medical School, Tunis, Tunisia Laboratory of Oral Health and Facial Rehabilitation (LR12ES11), University of Mounastir. Mounastir, Tunisia
    Search for articles by this author
  • Mohamed Atef Souissi
    Affiliations
    Resident, Department of ENT, Maxillo-Facial and Aesthetic Surgery, La Rabta Hospital, Tunis, Tunisia
    Search for articles by this author
  • Marouen Ben Rejeb
    Affiliations
    Assistant Professor, Tunis Medical School, Tunis-El Manar University, Tunisia Department of Maxillofacial Surgery, Charles Nicolle Hospital, Tunis, Tunisia
    Search for articles by this author
  • Habib Khochtali
    Affiliations
    Professor and Department Head, Department of Surgery, Ibn Aljazzar Medical School, Sousse, Tunisia Department of Maxillofacial and Aesthetic Surgery, Sahloul Hospital, Sousse, Tunisia
    Search for articles by this author
Published:November 11, 2021DOI:https://doi.org/10.1016/j.joms.2021.10.023

      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.
      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic and Personal
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Journal of Oral and Maxillofacial Surgery
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Li S.Z.
        • Chu R.
        • Liao S.
        • Zhang L.
        Illumination invariant face recognition using near-infrared images.
        IEEE Trans Pattern Anal Mach Intell. 2007; 29: 627
        • Zuo K.J.
        • Saun T.J.
        • Forrest C.R.
        Facial recognition technology: A primer for plastic surgeons.
        Plast Reconstr Surg. 2019; 143: 9
        • Zacharopoulos G.V.
        • Manios A.
        • Kau C.H.
        • et al.
        Anthropometric analysis of the face.
        J Craniofac Surg. 2016; 27: e71
        • Farkas L.G.
        Anthropometry of the Head and Face in Medicine.
        Elsevier, 1981: 293
      1. Anthropometry of the head and face (Livre, 1994) [WorldCat.org] [Internet].
        • Ahonen T.
        • Hadid A.
        • Pietikäinen M.
        Face description with local binary patterns: Application to face recognition.
        IEEE Trans Pattern Anal Mach Intell. 2006; 28: 2037
        • Moeini A.
        • Faez K.
        • Moeini H.
        Face recognition across makeup and plastic surgery from real-world images.
        J Electron Imaging. 2015; 24053028
        • Liu X.
        • Shan S.
        • Chen X.
        Face recognition after plastic surgery: A comprehensive study.
        in: Asian Conference on Computer Vision. Springer, 2012: 565-576
        • Ramana N.
        • Chellappa R.
        Face verification across age progression.
        IEEE Trans Image Process. 2006; 15: 3349
        • Kaur M.
        • Garg R.K.
        • Singla S.
        Analysis of facial soft tissue changes with aging and their effects on facial morphology: A forensic perspective.
        Egypt J Forensic Sci. 2015; 5: 46
        • Bhatt H.S.
        • Bharadwaj S.
        • Singh R.
        • Vatsa M.
        Recognizing surgically altered face images using multiobjective evolutionary algorithm.
        IEEE Trans Inf Forensics Secur. 2013; 8: 89
        • Ryan P.J.
        • Turner M.J.A.
        • Gibbons A.J.
        • Ricanek K.
        Orthognathic surgery and the biometric e-passport: A change in surgical practice.
        Br J Oral Maxillofac Surg. 2014; 52: 384
        • Chauhan N.
        • Warner J.P.
        • Adamson P.A.
        Perceived age change after aesthetic facial surgical procedures quantifying outcomes of aging face surgery.
        Arch Facial Plast Surg. 2012; 14: 258
        • Singh R.
        • Vatsa M.
        • Bhatt H.S.
        • et al.
        Plastic surgery: A new dimension to face recognition.
        IEEE Trans Inf Forensics Secur. 2010; 5: 441
        • Niamtu J.
        The aging face.
        in: Cosmetic Facial Surgery [Internet]. Elsevier, 2018: 1-14
        • Albert M.
        • Sethuram A.
        • Ricanek K.
        Implications of adult facial aging on biometrics.
        in: Albert M. Biometrics - Unique and Diverse Applications in Nature, Science, and Technology [Internet]. InTech, 2011
        • Heo J.
        • Savvides M.
        3-D generic elastic models for fast and texture preserving 2-D novel pose synthesis.
        IEEE Trans Inf Forensics Secur. 2012; 7: 563
        • Fortes HN da R.
        • Guimarães T.C.
        • Belo I.M.L.
        • da Matta E.N.R.
        Photometric analysis of esthetically pleasant and unpleasant facial profile.
        Dent Press J Orthod. 2014; 19: 66
        • Zimm A.J.
        • Modabber M.
        • Fernandes V.
        • et al.
        Objective assessment of perceived age reversal and improvement in attractiveness after aging face surgery.
        JAMA Facial Plast Surg. 2013; 15: 405
        • Ideta S.
        • Ota Y.
        • Yuki K.
        • et al.
        Evaluation of surgical outcomes for ptosis surgery by face recognition software.
        Asia Pac J Ophthalmol (Phila). 2015; 4: 14