Facial Plast Surg 2024; 40(05): 615-622
DOI: 10.1055/a-2216-5099
Original Research

Artificial Intelligence in Facial Plastic and Reconstructive Surgery: A Systematic Review

Jorge Alberto Espinosa Reyes
1   Department of Otolaryngology and Facial Plastic & Reconstructive Surgery, The Face & Nose Institute, Private Practice Clínica INO, Bogotá, DC, Colombia
,
2   Department of Otolaryngology and Facial Plastic & Reconstructive Surgery, Private Practice Clínica Sebastían de Belalcázar, Cali, Valle del Cauca, Colombia
,
3   Department of Otolaryngology and Facial Plastic & Reconstructive Surgery, The Face & Nose Institute, Private Practice at Clínica Imbanaco, Cali, Valle del Cauca Colombia
,
Nicolas Heredia
4   Department of Otolaryngology and Facial Plastic & Reconstructive Surgery, The Face & Nose Institute, Bogotá, DC, Colombia
,
Luis Alberto Solís Ruiz
5   Department of Otolaryngology and Facial Plastic & Reconstructive Surgery, Private Practice, Chihuahua, Chihuahua, México
,
Diego Andres Corredor Zuluaga
6   Department of Otolaryngology and Facial Plastic & Reconstructive Surgery, Private Practice, Pereira, Risaralda, Colombia
› Author Affiliations

Abstract

Artificial intelligence (AI) is a technology that is evolving rapidly and is changing the world and medicine as we know it. After reviewing the PROSPERO database of systematic reviews, there is no article related to this topic in facial plastic and reconstructive surgery. The objective of this article was to review the literature regarding AI applications in facial plastic and reconstructive surgery.

A systematic review of the literature about AI in facial plastic and reconstructive surgery using the following keywords: Artificial Intelligence, robotics, plastic surgery procedures, and surgery plastic and the following databases: PubMed, SCOPUS, Embase, BVS, and LILACS. The inclusion criteria were articles about AI in facial plastic and reconstructive surgery. Articles written in a language other than English and Spanish were excluded. In total, 17 articles about AI in facial plastic met the inclusion criteria; after eliminating the duplicated papers and applying the exclusion criteria, these articles were reviewed thoroughly. The leading type of AI used in these articles was computer vision, explicitly using models of convolutional neural networks to objectively compare the preoperative with the postoperative state in multiple interventions such as facial lifting and facial transgender surgery.

In conclusion, AI is a rapidly evolving technology, and it could significantly impact the treatment of patients in facial plastic and reconstructive surgery. Legislation and regulations are developing slower than this technology. It is imperative to learn about this topic as soon as possible and that all stakeholders proactively promote discussions about ethical and regulatory dilemmas.

Authors' Contributions

M.P.R. made a systematic search of the literature; the articles retrieved in this search were distributed between M.P.R., D.A.C.Z., and L.A.S.R., who selected the articles. If there was any doubt, J.A.E.R. decided if the article was or was not suitable for this article. After M.P.R. and J.A.E.R. wrote the article's first draft, R.C. and N.H. finally corrected and adjusted the text in multiple sessions to achieve this document.


Availability of Data and Materials

All the studies reviewed in this article are available online in the following search engines: PubMed, SCOPUS, Embase, and BVS.




Publication History

Accepted Manuscript online:
22 November 2023

Article published online:
22 January 2024

© 2024. Thieme. All rights reserved.

Thieme Medical Publishers, Inc.
333 Seventh Avenue, 18th Floor, New York, NY 10001, USA

 
  • References

  • 1 Jarvis T, Thornburg D, Rebecca AM, Teven CM. Artificial intelligence in plastic surgery: current applications, future directions, and ethical implications. Plast Reconstr Surg Glob Open 2020; 8 (10) e3200
  • 2 Haug CJ, Drazen JM. Artificial intelligence and machine learning in clinical medicine, 2023. Drazen JM, Kohane IS, Leong TY, eds. N Engl J Med 2023; 388 (13) 1201-1208
  • 3 Rokhshad R, Keyhan SO, Yousefi P. Artificial intelligence applications and ethical challenges in oral and maxillo-facial cosmetic surgery: a narrative review. Maxillofac Plast Reconstr Surg 2023; 45 (01) 14
  • 4 Beam AL, Drazen JM, Kohane IS, Leong TY, Manrai AK, Rubin EJ. Artificial intelligence in medicine. N Engl J Med 2023; 388 (13) 1220-1221
  • 5 Atiyeh B, Emsieh S, Hakim C, Chalhoub R. A narrative review of artificial intelligence (AI) for objective assessment of aesthetic endpoints in plastic surgery. Aesthet Plast Surg 2023; 47 (06) 2862-2873
  • 6 Liang X, Yang X, Yin S. et al. Artificial intelligence in plastic surgery: applications and challenges. Aesthet Plast Surg 2021; 45 (02) 784-790
  • 7 Moglia A, Georgiou K, Morelli L, Toutouzas K, Satava RM, Cuschieri A. Breaking down the silos of artificial intelligence in surgery: glossary of terms. Surg Endosc 2022; 36 (11) 7986-7997
  • 8 Nicholson CV. Symbolic reasoning (symbolic AI) and machine learning. Accessed at: https://wiki.pathmind.com/symbolic-reasoning#:~:text=One%20of%20the%20main%20differences,are%20created%20through%20human%20intervention
  • 9 Eldaly AS, Avila FR, Torres-Guzman RA. et al. Simulation and artificial intelligence in rhinoplasty: a systematic review. Aesthet Plast Surg 2022; 46 (05) 2368-2377
  • 10 Robotnik. Use and applications of artificial intelligence in robotics. Accessed 19 April 2023 at: https://robotnik.eu/introduction-to-robotics-and-artificial-intelligence/
  • 11 IBM. What is machine learning? Accessed 19 April 2023 at: https://www.ibm.com/topics/machine-learning
  • 12 IBM. What is deep learning? Accessed 19 April 2023 at: https://www.ibm.com/topics/deep-learning#:∼:text=the%20next%20step-,What%20is%20deep%20learning%3F,from%20large%20amounts%20of%20data
  • 13 Boczar D, Brydges H, Onuh OC. et al. Use of three-dimensional volumetric analysis to monitor acute rejection in a face transplant recipient. Am J Transplant 2022;22(suppl 3). Accessed 4 January 2024 at: https://atcmeetingabstracts.com/abstract/use-of-three-dimensional-volumetric-analysis-to-monitor-acute-rejection-in-a-face-transplant-recipient/
  • 14 Xie K, Yang J, Zhu YM. Fast collision detection based on nose augmentation virtual surgery. Comput Methods Programs Biomed 2007; 88 (01) 1-7
  • 15 Hartman E, Wallblom K, van der Plas MJA. et al. Bioinformatic analysis of the wound peptidome reveals potential biomarkers and antimicrobial peptides. Front Immunol 2021; 11: 620707
  • 16 Borsting E, DeSimone R, Ascha M, Ascha M. Applied deep learning in plastic surgery: classifying rhinoplasty with a mobile app. J Craniofac Surg 2020; 31 (01) 102-106
  • 17 Dorfman R, Chang I, Saadat S, Roostaeian J. Making the subjective objective: machine learning and rhinoplasty. Aesthet Surg J 2020; 40 (05) 493-498
  • 18 Štěpánek L, Kasal P, Měšťák J. Machine-learning and R in plastic surgery – evaluation of facial attractiveness and classification of facial emotions. In: Information Systems Architecture and Technology: Proceedings of 40th Anniversary International Conference on Information Systems Architecture and Technology 2019. (pp. 243–252) DOI: 10.1007/978-3-030-30604-5_22
  • 19 Chinski H, Lerch R, Tournour D, Chinski L, Caruso D. An artificial intelligence tool for image simulation in rhinoplasty. Facial Plast Surg 2022; 38 (02) 201-206
  • 20 Gil Press. Artificial general intelligence (AGI) is a very human hallucination. Accessed 19 April 2023 at: https://www.forbes.com/sites/gilpress/2023/03/28/artificial-general-intelligence-agi-is-a-very-human-hallucination/?sh=1e8664ad64f2
  • 21 Posnick JC. The future of artificial intelligence in the medical field. J Oral Maxillofac Surg 2022; 80 (06) 978-979
  • 22 Lin L, Xu C, Shi Y. et al. Preliminary clinical experience of robot-assisted surgery in treatment with genioplasty. Sci Rep 2021; 11 (01) 6365
  • 23 Morris MX, Song EY, Rajesh A, Asaad M, Phillips BT. Ethical, legal, and financial considerations of artificial intelligence in surgery. Am Surg 2023; 89 (01) 55-60
  • 24 Spoer DL, Kiene JM, Dekker PK. et al. A systematic review of artificial intelligence applications in plastic surgery: looking to the future. Plast Reconstr Surg Glob Open 2022; 10 (12) e4608
  • 25 Elliott ZT, Bheemreddy A, Fiorella M. et al. Artificial intelligence for objectively measuring years regained after facial rejuvenation surgery. Am J Otolaryngol Head Neck Med Surg 2023; 44 (02) 103775
  • 26 Boonipat T, Hebel N, Zhu A, Lin J, Shapiro D. Using artificial intelligence to analyze emotion and facial action units following facial rejuvenation surgery. J Plast Reconstr Aesthet Surg 2022; 75 (09) 3628-3651
  • 27 O'Sullivan E, van de Lande LS, Papaioannou A. et al. Convolutional mesh autoencoders for the 3-dimensional identification of FGFR-related craniosynostosis. Sci Rep 2022; 12 (01) 2230
  • 28 Boonipat T, Lin J, Bite U. Detection of baseline emotion in brow lift patients using artificial intelligence. Aesthet Plast Surg 2021; 45 (06) 2742-2748
  • 29 Gibstein AR, Chen K, Nakfoor B. et al. Facelift surgery turns back the clock: artificial intelligence and patient satisfaction quantitate value of procedure type and specific techniques. Aesthet Surg J 2021; 41 (09) 987-999
  • 30 Boonipat T, Asaad M, Lin J, Glass GE, Mardini S, Stotland M. Using artificial intelligence to measure facial expression following facial reanimation surgery. Plast Reconstr Surg 2020; 146 (05) 1147-1150
  • 31 Dusseldorp JR, Guarin DL, van Veen MM, Jowett N, Hadlock TA. In the eye of the beholder: changes in perceived emotion expression after smile reanimation. Plast Reconstr Surg 2019; 144 (02) 457-471
  • 32 Tuan HNA, Hai NDX, Thinh NT. Shape prediction of nasal bones by digital 2D-photogrammetry of the nose based on convolution and back-propagation neural network. Comput Math Methods Med 2022; 2022: 5938493
  • 33 McCullough M, Ly S, Auslander A. et al. Convolutional neural network models for automatic preoperative severity assessment in unilateral cleft lip. Plast Reconstr Surg 2021; 148 (01) 162-169
  • 34 Zhang BH, Chen K, Lu SM. et al. Turning back the clock: artificial intelligence recognition of age reduction after face-lift surgery correlates with patient satisfaction. Plast Reconstr Surg 2021; 148 (01) 45-54
  • 35 Bahçeci Şimşek İ, Şirolu C. Analysis of surgical outcome after upper eyelid surgery by computer vision algorithm using face and facial landmark detection. Graefes Arch Clin Exp Ophthalmol 2021; 259 (10) 3119-3125
  • 36 Chen K, Lu SM, Cheng R. et al. Facial recognition neural networks confirm success of facial feminization surgery. Plast Reconstr Surg 2020; 145 (01) 203-209
  • 37 Konofaos P, Hammond S, Ver Halen JP, Samant S. Reconstructive techniques in transoral robotic surgery for head and neck cancer: a North American survey. Plast Reconstr Surg 2013; 131 (02) 188e-197e
  • 38 Garfein ES, Greaney Jr PJ, Easterlin B, Schiff B, Smith RV. Transoral robotic reconstructive surgery reconstruction of a tongue base defect with a radial forearm flap. Plast Reconstr Surg 2011; 127 (06) 2352-2354