RhinoplastyNCT07580573
AI in Assessing Aesthetic Outcomes in Rhinoplasty
A study testing AI in people with Rhinoplasty and AI (Artificial Intelligence), run by Assiut University.
Trial summary
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 Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Rhinoplasty, AI (Artificial Intelligence)
- What is being tested?
- AI
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 20 participants
- Where
- No sites listed yet
- Study dates
- 1 Jun 2026to 1 Jul 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Patients age> 18 years old.
- patients schedule for rhinoplasty surgery
Who cannot join
- Pervious nasal trauma that affect anatomical land mark
- pervious nasal surgery (rhinoplasty or others)
- patients with psychological disorders.
- patients with any coagulopathy disorders
About this study
Official title: 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
Read the detailed 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.
- Conditions
- Rhinoplasty, AI (Artificial Intelligence)
- Being tested
- AI
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AIOther
using AI-driven simulations which enable the generation of realistic preoperative predictions, thereby improving surgical planning and patient communication.
| Study group | Role | What they receive |
|---|---|---|
| AI-Based Assessment | Other | Not described Receives: Other: AI |
What is being measured
The primary outcome is the main question the study is designed to answer.
Agreement between ImageJ and AI application measurements
Measured: basline
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
Measured: basline
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted12 May 2026
- Study start1 Jun 2026 (estimated)
- Primary completion1 Jun 2027 (estimated)
- Study completion1 Jul 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for RhinoplastyStudies of the same condition, open and under way.
- More trials run by Assiut UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Screening
- Allocation
- Randomised
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 20 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Assiut University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Menntallah ahmad kamal ahmad, Assiut University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07580573
- Sponsor's protocol ID
- UAIAAOR
- Status last verified
- May 2026
- First submitted
- 21 Apr 2026
- Last updated
- 12 May 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
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.
PubMed 39157708Zhao 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.
PubMed 35099579
Study at a glance
From the registry record, last updated by the sponsor on 12 May 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Use of Artificial Intelligence in Assessment of Aesthetic Outcomes in Rhinoplasty
- ClinicalTrials.gov ID
- NCT07580573
- Acronym / sponsor ID
- UAIAAOR
- Conditions
- Rhinoplasty, AI (Artificial Intelligence)
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 20 participants (estimated)
- Lead sponsor
- Assiut UniversityUniversity, hospital or other
- Study start
- 1 Jun 2026 (estimated)
- Primary completion
- 1 Jun 2027 (estimated)
- Study completion
- 1 Jul 2027 (estimated)
- First posted
- 12 May 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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
Detailed 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.
Study design
- Primary purpose
- Screening
- Allocation
- Randomised
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| AI-Based Assessment | Other | Other: AI |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- Patients age> 18 years old.
- patients schedule for rhinoplasty surgery
Key exclusion criteria (4 listed)
- Pervious nasal trauma that affect anatomical land mark
- pervious nasal surgery (rhinoplasty or others)
- patients with psychological disorders.
- patients with any coagulopathy disorders
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AIusing AI-driven simulations which enable the generation of realistic preoperative predictions, thereby improving surgical planning and patient communication. | Other | AI-Based Assessment |
Primary outcome
Agreement between ImageJ and AI application measurements
Time frame: basline
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
Time frame: basline
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 May 2026.
- Background: PubMed 39157708Omer 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.
- Background: PubMed 35099579Zhao 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.
- Automated Assessment of Aesthetic Outcomes in Facial Plastic SurgeryLink provided by the sponsor.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
The record lists no contact. Use the official record to reach the sponsor.
Questions about this trial
What is this clinical trial studying?
A study testing AI in people with Rhinoplasty and AI (Artificial Intelligence), run by Assiut University.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 12 May 2026. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Agreement between ImageJ and AI application measurements (time frame: basline). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07580573, which also lists 2 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 12 May 2026; AzTrials last refreshed its copy on 7 Nov 2026.