AI in Assessing Aesthetic Outcomes in Rhinoplasty
Use of Artificial Intelligence in Assessment of Aesthetic Outcomes in Rhinoplasty
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
研究概览
详细说明
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.
研究类型
注册 (估计的)
阶段
- 不适用
参与标准
资格标准
适合学习的年龄
- 成人
- 年长者
接受健康志愿者
描述
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
学习计划
研究是如何设计的?
设计细节
- 主要用途:放映
- 分配:随机化
- 介入模型:单组作业
- 屏蔽:无(打开标签)
武器和干预
参与者组/臂 |
干预/治疗 |
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其他:AI-Based Assessment
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using AI-driven simulations which enable the generation of realistic preoperative predictions, thereby improving surgical planning and patient communication.
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研究衡量的是什么?
主要结果指标
结果测量 |
大体时间 |
|---|---|
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Agreement between ImageJ and AI application measurements
大体时间:basline
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basline
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Evaluate the accuracy of AI-based simulation in predicting postoperative aesthetic outcomes following structural rhinoplasty by comparing AI-generated preoperative simulations with actual postoperative nasal morphology using objective digital image a
大体时间:basline
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basline
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合作者和调查者
出版物和有用的链接
一般刊物
- Omer G, Girolamo S, Hamatofiq B, Tofiq S, Mohammed MA, Abdulkarim D, Mohammed S, Gubari M, Habibullah I, Mustafa A, Fatah M, Ahmed S, Kakamad F. Functional, Cosmetic, and Psychological Outcomes after Rhinoplasty. Plast Reconstr Surg Glob Open. 2024 Aug 16;12(8):e6057. doi: 10.1097/GOX.0000000000006057. eCollection 2024 Aug.
- Zhao R, Chen K, Tang Y. Effects of Functional Rhinoplasty on Nasal Obstruction: A Meta-Analysis. Aesthetic Plast Surg. 2022 Apr;46(2):873-885. doi: 10.1007/s00266-021-02741-2. Epub 2022 Jan 31.
研究记录日期
研究主要日期
学习开始 (估计的)
初级完成 (估计的)
研究完成 (估计的)
研究注册日期
首次提交
首先提交符合 QC 标准的
首次发布 (实际的)
研究记录更新
最后更新发布 (实际的)
上次提交的符合 QC 标准的更新
最后验证
更多信息
与本研究相关的术语
其他研究编号
- UAIAAOR
药物和器械信息、研究文件
研究美国 FDA 监管的药品
研究美国 FDA 监管的设备产品
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