AI in Assessing Aesthetic Outcomes in Rhinoplasty

Assiut University

Status: Not yet enrolling

Conditions: Rhinoplasty; AI (Artificial Intelligence)

Treatments: Other: AI

Study type: Interventional

Funder types: Other

Identifiers

NCT07580573

UAIAAOR

Details and patient eligibility

About

This study aims to thoroughly assess the predictive accuracy of artificial intelligence-based nasal outcome simulations by comparing AI-generated preoperative predictions with objective postoperative nasal morphology using digital image analysis.

To assess accuracy of AI-image measurement compared with imageJ software

Full description

Rhinoplasty is a surgical procedure that aims to enhance nasal aesthetics while preserving structural integrity and function. It focuses on minimizing tissue disruption through techniques such as cartilage reshaping, selective preservation, and grafting to maintain support. The primary goal is to achieve natural-looking outcomes while ensuring adequate nasal breathing and reducing postoperative complications.

Despite its widespread application, rhinoplasty remains one of the most complex procedures in aesthetic surgery due to the variability in individual anatomy and patient expectations. Conventional standardized approaches often fail to fully address these differences. Subjective assessment tools, including patient-reported outcome measures, provide insight into satisfaction with aesthetic and functional results; however, they are limited by lack of objectivity. Zojaji et al. demonstrated no strong correlation between objective facial proportion changes and Rhinoplasty Outcome Evaluation (ROE) scores, emphasizing the discrepancy between perceived and measured outcomes.

Recent advances in artificial intelligence (AI) have introduced innovative solutions to these challenges. AI-driven simulations enable the generation of realistic preoperative predictions, thereby improving surgical planning and patient communication.Furthermore, AI-based image analysis applications allow for precise and automated measurement of nasal parameters, including linear distances, angles, proportions, and symmetry, using standardized digital photographs. These tools provide objective and reproducible data, reduce observer variability, and enhance the accuracy of postoperative outcome assessment.

Enrollment: 20 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Patients age> 18 years old.
• patients schedule for rhinoplasty surgery

Exclusion criteria

• Pervious nasal trauma that affect anatomical land mark
• pervious nasal surgery (rhinoplasty or others)
• patients with psychological disorders.
• patients with any coagulopathy disorders

Trial design

Primary purpose: Screening

Allocation: Randomized

Interventional model: Single Group Assignment

Masking: None (Open label)

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20 participants in 1 patient group

AI-Based Assessment

Other group

Treatment:

Other: AI