Abstract ID: 26-528
Artificial Intelligence for Preoperative Simulation in Upper Blepharoplasty: Clinical Application, Validation and Ethical Considerations
Author: Krzysztof Czosnyka Base Hospital / Institution: University Hospital no 2 in Bydgoszcz
Presentation Type: ePoster Presentation
Purpose
This study evaluated the clinical utility of an AI-based simulation tool to predict aesthetic outcomes after upper blepharoplasty. The system generates realistic previews of postoperative eyelid contour and supratarsal crease from patient photographs to improve patient-surgeon communication and expectation management.
Methods
A deep learning-based AI simulation platform was integrated into routine preoperative consultations by a single experienced oculoplastic surgeon. Standardized frontal and lateral photographs were used as input, allowing interactive adjustment of surgical parameters (skin resection, crease height, fat management). Simulated images were compared with 3-month postoperative photographs using clinical assessment and landmark measurements. All data processing followed GDPR requirements with strict data security, anonymization, and explicit patient consent.
Results
The tool provided immediate visual feedback during consultations, facilitating active patient participation in surgical planning. It was particularly useful for discussing eyelid symmetry, crease position, and realistic surgical limitations in cases with brow asymmetry or skin laxity.
Conclusion
Generative AI enables realistic prediction of soft-tissue changes in oculoplastic surgery. This technology serves as a valuable adjunct bridging the gap between surgical planning and patient visualization.Ethical aspects and data security are paramount — patient photographs are sensitive biometric data. Processing was performed on secure, certified medical platforms with end-to-end encryption and mandatory informed consent. No images were used for AI training without approval.Validation of simulation accuracy remains challenging and requires future quantitative analysis and larger studies. While useful, AI simulation must complement, not replace, surgical expertise and clinical judgment.