Validation of a Smartphone-based Intelligent Diagnosis and Measurement for Strabismus

• Sponsor: Sun Yat-sen University (Other)
• Overall Status: Recruiting
• CT.gov ID: NCT05615519
• Collaborator: (none)
• Enrollment: 300
• Location: 1
• Anticipated Duration (Months): 3.9
• Patients Per Site Per Month: 76.1

Study Details

Study Description

Brief Summary

The current measurement methods of strabismus include the corneal light reflection method, prism alternate covering, etc., which especially rely on the subjective experience of doctors, and there is a large error between different measurers， leading to serious underestimation of strabismus prevalence and insufficient care for strabismus patients. Here, the investigators established and validated an artificial intelligence system to achieve an automatic diagnosis of strabismus based on patient-sourced videos of programmatic cover tests. Three-dimensional reconstruction methods are used to digitize the parameters of head and eye positions. This system has been integrated into a smartphone platform to be further validated through hospital-based and population-based clinical trials.

Condition or Disease	Intervention/Treatment	Phase
Strabismus; Exotropia; Esotropia; Vertical Strabismus	Diagnostic Test: A new technology based on 3D reconstruction and deep learning algorithm to achieve an automatic diagnosis of strabismus based on patient-sourced videos of programmatic cover tests.

Study Design

• Study Type: Observational
• Anticipated Enrollment: 300 participants
• Observational Model: Cohort
• Time Perspective: Prospective
• Official Title: Validation of a Smartphone-based Intelligent Diagnosis and Measurement for Strabismus
• Anticipated Study Start Date: Dec 2, 2022
• Anticipated Primary Completion Date: Mar 1, 2023
• Anticipated Study Completion Date: Apr 1, 2023

Arms and Interventions

Arm	Intervention/Treatment
Eligible participants for smartphone-based strabismus measurement and diagnosis Facial videos dataset Facial videos were collected using smartphone and following the programmatic cover tests.	Diagnostic Test: A new technology based on 3D reconstruction and deep learning algorithm to achieve an automatic diagnosis of strabismus based on patient-sourced videos of programmatic cover tests.; Digital ruler of strabismus

Outcome Measures

Primary Outcome Measures

1. The effectiveness of smartphone-based diagnosis [Baseline]

   The accurate and the area under curve of the smartphone-based diagnosis.

2. The consistency between manual and smartphone measurement [Baseline]

   Agreement between the manual and automated tests was represented in Bland-Altman plots and concordance correlation coefficients.

Eligibility Criteria

Criteria

• Ages Eligible for Study: 3 Years and Older
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: Yes

Inclusion Criteria:

The quality of facial videos should be clinically acceptable.

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	Zhongshan Ophthalmic Center, Sun Yat-sen Univerisity	Guangzhou	Guangdong	China	510060

Sponsors and Collaborators

• Sun Yat-sen University

Investigators

None specified.

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.

• Responsible Party: Haotian Lin, Clinical Professor, Sun Yat-sen University
• ClinicalTrials.gov Identifier: NCT05615519
• Other Study ID Numbers: DRStrabismus2022
• First Posted: Nov 14, 2022
• Last Update Posted: Dec 5, 2022
• Last Verified: Dec 1, 2022

• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No
• Keywords provided by Haotian Lin, Clinical Professor, Sun Yat-sen University: Mobile health; Artificaial intelligence medicine; Pediatric ophthalmology
• Additional relevant MeSH terms: Strabismus; Exotropia; Esotropia

Study Results

No Results Posted as of Dec 5, 2022