A Comprehensive Assessment of Soft-tissue Sagging after Zygoma Reduction Surgery through Artificial Intelligence Analysis

Abstract

Background: Overdevelopment of zygomatic bones often results in protrusion and flaring of the midfacial region. This makes the face appear squarer than the more favorable oval shape. Therefore, zygoma reduction surgery has become a commonly performed procedure in patients seeking to obtain an ideal facial shape. Facial soft-tissue ptosis is one of the main complications of zygoma reduction surgery. Previously, the evaluation of cheek soft-tissue ptosis was subjectively based on patients and surgeons. Our study aimed to provide an objective evaluation of soft-tissue sagging in the cheek region after zygoma reduction surgery using artificial intelligence (AI). Methods: We used AI to evaluate cheek sagging in a series of patients who underwent zygoma reduction surgery. We used four methods: tracking facial landmarks, detecting changes in the cheek curvature, and examining changes in the nasolabial fold and marionette lines. Then, the obtained numerical results were assessed for statistically significant differences using statistical validation methods. Results: Use of AI with the four methods demonstrated no statistically significant differences between the pre- and postsurgery evaluations. AI analysis demonstrated that soft-tissue ptosis did not occur in our series of patients. Conclusions: AI offers objective evaluation for both patients and doctors. Future research could build on this application to examine various influencing factors and develop new tools using machine learning to evaluate and predict the extent of cheek sagging in patients before surgery.