Development of an AI Solution to Evaluate Clinical Activity of TAO Using Periocular Images Taken by Smartphones in Patients With Thyroid Dysfunction

Study Overview
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Brief Summary
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This study was conducted to develop an AI solution to evaluate clinical activity score (CAS) of thyroid associated orbitopathy (TAO) using periocular selfie images taken by smartphones in patients with thyroid dysfunction. An AI solution to evaluate CAS in TAO was developed in previous retrospective study using periorbital digital images taken by DSLR camera in the studio. This AI solution will be adjusted to show its best performance with periocular selfie images taken by smartphones.

Official Title
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Development of an Artificial Intelligence Solution to Evaluate Clinical Activity of Thyroid Associated Orbitopathy Using Periocular Selfie Images Taken by Smartphones in Patients With Thyroid Dysfunction

Conditions
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Thyroid Eye Disease

Intervention / Treatment
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* Other: taking periorbital selfie images using smartphones


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Patients with thyroid eye disease Exclusion Criteria: Patients who have prior facial anomaly or surgery Patients who cannot use smartphone camera app

Ages Eligible for Study
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Minimum Age: 19 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| thyroid eye disease group<br>Patients who were diagnosed as thyroid eye disease. Periorbital images are taken by DSLR camera in the studio. Periorbital selfie images are taken by the patients with 6 smartphones including various camera modules. CAS of TAO is evaluated by 3 ophthalmologists based on the periorbital digital images taken by DSLR camera and symptoms. | Other: taking periorbital selfie images using smartphones<br>* taking periorbital selfie images using smartphones<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Accuracy for clinical activity score (CAS) of thyroid eye disease (TED) | Accuracy of AI solution using smartphone selfie images for CAS of TED. | baseline (this study has no intervention) | 
| Diagnostic accuracy for active thyroid eye disease | Accuracy of AI solution using smartphone selfie images for active thyroid eye disease (TED) which is defined as 3 or more of clinical activity score | baseline (this study has no intervention) | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Accuracy for redness of eyelids | Accuracy of AI solution using smartphone selfie images for redness of eyelids | baseline (this study has no intervention) | 
| Accuracy for redness of conjunctiva | Accuracy of AI solution using smartphone selfie images for redness of conjunctiva | baseline (this study has no intervention) | 
| Accuracy for swelling of eyelids | Accuracy of AI solution using smartphone selfie images for swelling of eyelids | baseline (this study has no intervention) | 
| Accuracy for swelling of conjunctiva | Accuracy of AI solution using smartphone selfie images for swelling of conjunctiva | baseline (this study has no intervention) | 
| Accuracy for swelling of caruncle | Accuracy of AI solution using smartphone selfie images for swelling of caruncle | baseline (this study has no intervention) | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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thyroid eye disease, artificial intelligence, machine learning, smartphone