The Glaucoma and Retinopathy Screening Study (GRaSS)

The Glaucoma and Retinopathy Screening Study (GRaSS)

The goal of this clinical trial is to learn if a new screening approach including an artificial intelligence algorithm that analyzes fundus photographs, measurement of eye pressure and visual field testing works to screen for glaucoma.

Participants will:

Have an image of their fundus (back of the eye) taken as part of their diabetic eye screening Have a measurement of their eye pressure If needed, have a test of their side vision using a headset

Study Overview

• Status: Recruiting
• Conditions: Glaucoma
• Intervention / Treatment: Device: AI-based glaucoma screening; Device: IOP measurement; Device: Virtual Reality Visual Field Testing

Detailed Description

Study Overview: This study is a prospective, interventional clinical trial designed to evaluate the effectiveness of an artificial intelligence (AI)-based screening program within community health settings. This study targets especially diabetic patients because they have higher risks of developing glaucoma. By integrating glaucoma screening into existing diabetic eye disease (DED) screenings, the study aims to identify cases of glaucoma earlier, thereby preventing or delaying progression to blindness.

Background: Glaucoma is a chronic eye disease that causes progressive optic nerve damage, often leading to irreversible vision loss. Early detection is critical, as glaucoma is typically asymptomatic in its early stages. Individuals with diabetes are at an elevated risk for glaucoma, making it crucial to develop accessible screening methods. Current DED screening programs already utilize fundus photography for diabetic retinopathy. Adding glaucoma screening to these existing DED screenings may provide an efficient and cost-effective solution to reach high-risk populations without requiring additional clinic visits.

Study Hypothesis: The hypothesis of this study is that incorporating AI-driven glaucoma screening into standard DED screenings will increase the detection rate of glaucoma in high-risk populations compared to DED screening alone. This combined approach is expected to yield better clinical outcomes by enabling early diagnosis and treatment while being cost-effective.

Expected Outcomes and Impact: This study is expected to provide valuable insights into the effectiveness of integrating AI-based glaucoma screening into existing screening programs for diabetic eye disease. If successful, this combined screening approach could be a cost-effective model for other community health settings, leading to earlier detection of glaucoma and improved patient outcomes. By making glaucoma screening more accessible the study aims to reduce health disparities and support preventive eye care.

• Study Type: Interventional
• Enrollment (Estimated): 2000
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: David S Friedman, MD, PhD, MPH; Phone Number: 617-573-3094; Email: grass@mgb.org

Study Locations

• United States
  • Massachusetts
    • Boston, Massachusetts, United States, 02115
      • Recruiting
      • Brigham and Women's Primary Care Associates of Longwood
      • Contact: David S Friedman, MD, PhD, MPH; Phone Number: 617-573-3094; Email: grass@mgb.org
    • Chelsea, Massachusetts, United States, 02150
      • Recruiting
      • MGH Chelsea HealthCare Center
      • Contact: David S Friedman, MD, PhD, MPH; Phone Number: 617-573-3094; Email: grass@mgb.org
    • Lynn, Massachusetts, United States, 01904
      • Recruiting
      • NSPG Lynn
      • Contact: David S Friedman, MD, PhD, MPH; Phone Number: 617-573-3094; Email: grass@mgb.org
    • Salem, Massachusetts, United States, 01970
      • Not yet recruiting
      • NSPG Salem
      • Contact: David S Friedman, MD, PhD, MPH; Phone Number: 617-573-3094; Email: grass@mgb.org
    • Saugus, Massachusetts, United States, 01906
      • Recruiting
      • NSPG Saugus
      • Contact: David S Friedman, MD, PhD, MPH; Phone Number: 617-573-3094; Email: grass@mgb.org

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

Description

• Individuals with diabetes undergoing AI-based screening for diabetic retinopathy using the LumineticsCore (Digital Diagnostics) system for clinical care at primary care centers.
• Individuals who are able and willing to provide informed consent for participation in the study.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Screening
• Allocation: Non-Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Combined DED and Glaucoma Screening; Participants in this arm will have fundus photographs that are taken as a part of standard clinical care analyzed by AI for signs of glaucoma in addition to for diabetic retinopathy. They will also have intraocular pressure measured. If the AI detects possible glaucoma, participants will undergo virtual perimetry testing for further assessment.	Device: AI-based glaucoma screening; AI analysis of fundus photographs to detect signs of glaucoma, added to AI-based diabetic eye disease screening performed for routine clinical care; Device: IOP measurement; Intraocular pressure measurement by Icare tonometer; Device: Virtual Reality Visual Field Testing; Virtual Reality Visual Field Testing by the Olleyes device for participants suspected of having glaucoma
No Intervention: DED Screening Only (Control Arm); Participants in this arm will undergo diabetic eye disease (DED) screening only for routine clinical care. This includes fundus photography for AI assessment of signs of diabetic retinopathy.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Glaucoma detection	This primary outcome measure will assesses the proportion of participants who receive a glaucoma diagnosis in the combined DED and glaucoma screening group compared to the DED-only screening group. Glaucoma diagnosis in the intervention group is based on AI-assisted analysis of fundus photography, intraocular pressure, and virtual reality perimetry testing for confirmation.	1 year from initial screening

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Cost-Effectiveness of Combined Screening vs. DED-Only Screening		1 year from initial screening
Participant Satisfaction with Screening Process	This measure assesses participant satisfaction with the glaucoma screening process. Satisfaction will be evaluated through a participant satisfaction survey.	Day of screening
Participant knowledge about glaucoma	This measure assesses participants' knowledge about glaucoma. Knowledge will be assessed through a questionnaire (NEI Glaucoma Eye-Q test).	Day of screening

Collaborators and Investigators

• Sponsor: Massachusetts Eye and Ear Infirmary
• Collaborators: Centers for Disease Control and Prevention
• Investigators: Principal Investigator: David S Friedman, MD, PhD, MPH, Massachusetts Eye and Ear

Study record dates

Study Major Dates

• Study Start (Actual): July 16, 2025
• Primary Completion (Estimated): September 1, 2030
• Study Completion (Estimated): September 1, 2030

Study Registration Dates

• First Submitted: March 10, 2025
• First Submitted That Met QC Criteria: March 12, 2025
• First Posted (Actual): March 18, 2025

Study Record Updates

• Last Update Posted (Estimated): August 28, 2025
• Last Update Submitted That Met QC Criteria: August 26, 2025
• Last Verified: June 1, 2025

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Eye Diseases; Ocular Hypertension; Glaucoma
• Other Study ID Numbers: 2024p003709

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: Deidentified study data
• IPD Sharing Time Frame: After study completion
• IPD Sharing Access Criteria: Data sharing will require adherence to Mass General Brigham institutional and IRB policies. External researchers will need to contact the Principal Investigator to request data and complete a Data Use Agreement. Only deidentified data will be shared.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No