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

Area of Science:

• Plastic Surgery
• Medical Imaging
• Artificial Intelligence

Background:

• Zygoma reduction surgery addresses midfacial protrusion for an oval facial shape.
• Cheek soft-tissue ptosis is a potential complication of zygoma reduction.
• Previous ptosis evaluations were subjective, lacking objective metrics.

Purpose of the Study:

• To objectively evaluate cheek soft-tissue sagging post-zygoma reduction surgery.
• To utilize artificial intelligence (AI) for quantitative assessment of facial changes.
• To compare pre- and post-operative cheek tissue behavior.

Main Methods:

• AI-driven analysis of facial landmarks and cheek curvature.
• Assessment of nasolabial fold and marionette line changes using AI.
• Statistical validation of AI-derived numerical results for significance.

Main Results:

• AI analysis showed no statistically significant differences in pre- and post-surgery evaluations.
• The study concluded that soft-tissue ptosis did not occur in the evaluated patient cohort.
• AI provided objective, quantifiable data on cheek tissue changes.

Conclusions:

• AI enables objective evaluation of zygoma reduction outcomes for patients and surgeons.
• Future research can refine AI tools for predicting pre-operative sagging.
• Machine learning applications can enhance pre-surgical assessment of facial aesthetics.