Artificial Intelligence-assissted Glaucoma Evaluation

Glaucoma Clinical Trial

— AGE  

Official title:

Development of Artificial Intelligence-assissted Diagnostic Program of Glaucoma

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT03268031
• Other study ID #: ProjectAGE
• Status: Completed
• Start date: August 15, 2017
• Est. completion date: February 1, 2020

Study information

• Verified date: October 2020
• Source: Sun Yat-sen University
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Glaucoma is currently the second leading cause of irreversible blindness in the world. Our study intends to combine clinical data of glaucoma patients in Zhongshan Ophthalmic Center with Artificial Intelligence techniques to create programs that can screen and diagnose glaucoma.

Description:

Glaucoma is currently the second leading cause of irreversible blindness in the world, which brings heavy burden to human society. Compared to other ocular diseases, diagnostic process of glaucoma is complicated depends on multiple test results, including visual field test, OCT, etc. How to diagnose glaucoma correctly and fast has always been a hot topic in glaucoma researches. Artificial intelligence is used to study and develop theories and methods that can help simulate and extend human intelligence, which has been utilized in a lot of research fields such as automatic drive and medicine. The study intends to combine clinical data of glaucoma patients in Zhongshan Ophthalmic Center with Artificial Intelligence techniques to create programs that can screen and diagnose glaucoma.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 10800
• Est. completion date: February 1, 2020
• Est. primary completion date: December 1, 2019
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: N/A and older

Eligibility

Inclusion Criteria:

1. BCVA>0.1

2. able to complete reliable visual field test

3. no history of intraocular surgery or fundus laser

Exclusion Criteria:

1. unable to complete visual field test

Related Conditions & MeSH terms

• Artificial Intelligence
• Glaucoma

Intervention

Diagnostic Test:
• Visual field and OCT tests
Visual field test and OCT are commonly used essential tests to make accurate diagnosis of glaucoma. Algorithms to classify Visual field and OCT tests would both be developed and verified.

Locations

Country	Name	City	State
China	Zhongshan Ophthalmic Center	Guangzhou	Guangdong

Sponsors (2)

Lead Sponsor	Collaborator
Sun Yat-sen University	Chinese Academy of Sciences

Country where clinical trial is conducted

China, 

References & Publications (3)

Asaoka R, Murata H, Iwase A, Araie M. Detecting Preperimetric Glaucoma with Standard Automated Perimetry Using a Deep Learning Classifier. Ophthalmology. 2016 Sep;123(9):1974-80. doi: 10.1016/j.ophtha.2016.05.029. Epub 2016 Jul 7. — View Citation

Diprose W, Buist N. Artificial intelligence in medicine: humans need not apply? N Z Med J. 2016 May 6;129(1434):73-6. — View Citation

Quigley HA. Glaucoma. Lancet. 2011 Apr 16;377(9774):1367-77. doi: 10.1016/S0140-6736(10)61423-7. Epub 2011 Mar 30. Review. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Accuracy of diagnosis by artificial intelligence algorithm	Accuracy of diagnosis by artificial intelligence algorithm and compare this result with glaucoma specialists	from August 2017 to February 2021
Secondary	Sensitivity of diagnosis by artificial intelligence algorithm	Sensitivity of diagnosis by artificial intelligence algorithm	from August 2017 to February 2021
Secondary	Specificity of diagnosis by artificial intelligence algorithm	Specificity of diagnosis by artificial intelligence algorithm	from August 2017 to February 2021