Artificial Intelligence in Surgical Evaluation: A Study of Facial Rejuvenation Techniques

Abstract

Background: Aesthetic facial surgeries historically rely on subjective analysis in determining success; this limits objective comparison of surgical outcomes.

Objectives: This case study exemplifies the use of an artificial intelligence software on objectively analyzing facial rejuvenation techniques with the aim of reducing subjective bias.

Methods: Retrospectively, all patients who underwent facial rejuvenation surgery with concomitant procedures from 2015 to 2017 were included (n = 32). Patients were categorized into Groups A to C: Group A-10 superficial musculoaponeurotic system (SMAS) plication facelift (n = 10), Group B-SMASectomy facelift (n = 7), and Group C-high SMAS facelift (n = 15). Neutral repose images preoperatively and postoperatively (average >3 months) were analyzed using artificial intelligence for emotion and action unit alterations.

Results: Postoperatively, Group A experienced a decrease in happiness by 0.84% and a decrease in anger by 6.87% (P >> .1). Group B had an increase in happiness by 0.77% and an increase in anger by 1.91% (P >> .1). Both Group A and Group B did not show any discernable action unit patterns. In Group C, the lip corner puller AU increased in average intensity from 0% to 18.7%. This correlated with an average increase in detected happiness from 1.03% to 13.17% (P = .008). Conversely, the average detected anger decreased from 14.66% to 0.63% (P = .032).

Conclusions: This study provides the first proof of concept for the use of a machine learning software application to objectively assess various aesthetic surgical outcomes in facial rejuvenation. Due to limitations in patient heterogeneity, this study does not claim one technique's superiority but serves as a conceptual foundation for future investigation.

Figure 1.

Preoperative and postoperative repose images. Group A: exemplary (A) preoperative and (B) 3-month postoperative images of an 89-year-old female who underwent a SMAS plication with fat grafting and a blepharoplasty. Group B: (C) preoperative and (D) 4-month postoperative images of a 78-year-old female who underwent a SMASectomy facelift with fat grafting, dermabrasion, and lip augmentation. Group C: (E) preoperative and (F) 3-month postoperative images of a 49-year-old female who underwent a high SMAS facelift with browlift, canthopexy, and fat grafting. SMAS, superficial musculoaponeurotic system.

Figure 2.

Representative images of the FaceReader (Noldus Information Technology BV, Wageningen, the Netherlands) analysis. The facial images are overlayed with a virtual mesh with labeled action units with their respective functioning. A 49-year-old female patient who underwent high SMAS facelift with a lateral temporal endoscopic browlift, bilateral canthopexy, and fat transfer to the lower eyelids, midface face, jawline, chin, and upper and lower lip is shown (A) preoperatively and (B) 3 months postoperatively. SMAS, superficial musculoaponeurotic system.

Figure 3.

Graphical representation of the change in perceived emotional expression at neutral repose after surgery relative to before. Inflections below the x-axis represent decreases after surgery, while positive inflections represent increases after surgery. SMAS, superficial musculoaponeurotic system.

Figure 4.

Outputted analysis of the perceived emotions and action unit of interest postoperatively relative to preoperatively. Inflections below the x-axis represent decreases after surgery, while positive inflections represent increases after surgery. An asterisk denotes a statistically significant P value <.05. SMAS, superficial musculoaponeurotic system.