Turning Back the Clock with Facelift Surgery: Artificial Intelligence Recognition of Age Reduction and Patient Satisfaction Quantitates Value of Specific Techniques
Kevin Chen, MD1, Alexander Gibstein, BA1, Stephen M. Lu, MD1, Roger Cheng, MS2, Charles H. Thorne, MD1, James P. Bradley, MD1.
1Hofstra Northwell School of Medicine, New York, NY, USA, 2Microsoft, Redmond, WA, USA.
INTRODUCTION: Patients desire facelifting procedures primarily to look younger, more refreshed, and attractive. Since there are few objective studies assessing the success of facelift surgery and various facelifting techniques, we utilized artificial intelligence, in the form of convolutional neural network algorithms, alongside FACE-Q patient-reported outcomes to evaluate perceived age reduction and patient satisfaction following various techniques of facelift surgery.
METHODS: Standardized preoperative and postoperative (1 year) images of 90 consecutive patients who underwent facelift procedures were used by four neural networks (trained to identify age based on facial features) to estimate age reduction after surgery. In addition, FACE-Q surveys were used to measure patient-reported facial aesthetic outcome. We specifically compared the following groups: 1) fat grafting vs no fat grafting (to malar region), 2) Necklift: Submental liposuction with lateral platysmal pull vs Corset-style platysmoplasty vs Martin necklift (submental lipectomy, submandibular gland resection, partial digastric resection); 3) SMAS-ectomy vs SMAS-plication vs Skin-only lift. Groups outcomes were based on complications, age-reduction, and patient satisfaction.
RESULTS: The neural network Preoperative Age Accuracy Score demonstrated that all four neural networks were accurate in identifying ages (mean score=100.8). Patient Self-Appraisal Age Reduction reported a greater age reduction than Neural Network Age Reduction after a facelift (-6.7years vs-4.3years). FACE Q scores demonstrated a high level of patient satisfaction for facial appearance (75.1+8.1), quality of life (82.4+8.3), and satisfaction with outcome (79.0+6.3). 1) Fat grafting had a positive benefit with -2.1year more age reduction, greater patient satisfaction (82.0+5.2 vs 74.1+6.0). without increased complications. 2) Neck lift groups had similar age reduction and patient satisfaction but submandibular gland resection group had more complications (bleeding (12%), revisions (25%); 3) SMAS-ectomy and SMAS-plication had greater age reduction with 2.9 and 2.4years more age reduction, better patient satisfaction but similar complications (6%, 5%, 5%).
CONCLUSION: Artificial intelligence algorithms can reliably estimate the reduction in apparent age after facelift surgery; specific techniques like malar fat grafting and SMAS-ectomy or SMAS-plication were found to enhance facelifting outcomes.
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