GlaucomaGRaSSNCT06882356
The Glaucoma and Retinopathy Screening Study
A study testing AI-based glaucoma screening, IOP measurement and Virtual Reality Visual Field Testing in people with Glaucoma, run by Massachusetts Eye and Ear Infirmary at 7 sites in United States.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 40 years and older
- Conditions the study is for
- Glaucoma
- What is being tested?
- AI-based glaucoma screening, IOP measurement and Virtual Reality Visual Field Testing
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 2,000 participants
- Where
- 7 sitesUnited States
- Study dates
- 16 Jul 2025to Sep 2030
- 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 40 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
- Individuals with diabetes undergoing AI-based screening for diabetic retinopathy using the LumineticsCore (Digital Diagnostics) system at primary care centers.
- Individuals who are able and willing to provide informed consent for participation in the study.
Trial locations and contacts
7 sites in 1 country. Contact the study team or a site near you to ask about taking part.
7 sites in 1 country
United States7 sites, 7 recruiting
- Recruiting
Massachusetts General Hospital Internal Medicine Associates
Boston, Massachusetts, 02114
David S Friedman, MD, PhD, MPH, 617-573-3094, grass@mgb.org
- Recruiting
Brigham and Women's Primary Care Associates of Longwood
Boston, Massachusetts, 02115
David S Friedman, MD, PhD, MPH, 617-573-3094, grass@mgb.org
- Recruiting
Massachusetts General Hospital Broadway Primary Care-Revere
Boston, Massachusetts, 02151
David S Friedman, MD, PhD, MPH, 617-573-3094, grass@mgb.org
- Recruiting
MGH Chelsea HealthCare Center
Chelsea, Massachusetts, 02150
David S Friedman, MD, PhD, MPH, 617-573-3094, grass@mgb.org
- Recruiting
NSPG Lynn
Lynn, Massachusetts, 01904
David S Friedman, MD, PhD, MPH, 617-573-3094, grass@mgb.org
- Not yet recruiting
NSPG Salem
Salem, Massachusetts, 01970
David S Friedman, MD, PhD, MPH, 617-573-3094, grass@mgb.org
- Recruiting
NSPG Saugus
Saugus, Massachusetts, 01906
David S Friedman, MD, PhD, MPH, 617-573-3094, grass@mgb.org
About this study
Official title: 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
Read the 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.
- Conditions
- Glaucoma
- Being tested
- AI-based glaucoma screening, IOP measurement, Virtual Reality Visual Field Testing
- Medical subject headings
- Glaucoma
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-based glaucoma screeningDevice
AI analysis of fundus photographs to detect signs of glaucoma, added to AI-based diabetic eye disease screening
IOP measurementDevice
Intraocular pressure measurement by Icare tonometer
Virtual Reality Visual Field TestingDevice
Virtual Reality Visual Field Testing by the Olleyes device for participants suspected of having glaucoma
| Study group | Role | What they receive |
|---|---|---|
| Combined DED and Glaucoma Screening | Experimental | Participants in this arm will have fundus photographs taken for diabetic eye disease screening analyzed by AI for signs of glaucoma. They will also have intraocular pressure measured. If glaucoma is suspected, participants will undergo virtual perimetry testing for further assessment. Receives: Device: AI-based glaucoma screening; Device: IOP measurement; Device: Virtual Reality Visual Field Testing |
| DED Screening Only (Control Arm) | No intervention | 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 being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 1 year from initial screening
Secondary outcomes (3)
Cost-Effectiveness of Combined Screening vs. DED-Only Screening
Measured: 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.
Measured: 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).
Measured: Day of screening
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted18 Mar 2025
- Study start16 Jul 2025
- Primary completionSep 2030 (estimated)
- Study completionSep 2030 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for GlaucomaStudies of the same condition, open and under way.
- 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
- Non-randomised
- Intervention model
- Parallel groups
- Model description
- This study uses a prospective interventional model to evaluate the effectiveness of integrating AI-based glaucoma screening with existing diabetic eye disease (DED) screening among diabetic patients. Participants will have fundus images assessed by AI for glaucoma in addition to DED, and have intraocular pressure measurement measured. Suspected glaucoma cases will receive virtual perimetry testing for confirmation, and those diagnosed with glaucoma will be referred for follow-up care. This study aims to compare glaucoma detection rates between combined DED and glaucoma screening versus DED-only screening, ultimately supporting early glaucoma detection and enhancing care access in underserved communities.
- Masking
- None (open label)
- Enrolment
- 2,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Massachusetts Eye and Ear Infirmary
- Sponsor type
- University, hospital or other
- Collaborators
- Centers for Disease Control and Prevention
- Responsible party
- Principal investigator, David Steven Friedman, Massachusetts Eye and Ear Infirmary
- Investigators
- David S Friedman, MD, PhD, MPH, Principal investigator, Massachusetts Eye and Ear
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06882356
- Sponsor's protocol ID
- 2024p003709
- Acronym
- GRaSS
- Status last verified
- Aug 2026
- First submitted
- 10 Mar 2025
- Last updated
- 27 Aug 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Deidentified study data
Study at a glance
From the registry record, last updated by the sponsor on 27 Aug 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Glaucoma and Retinopathy Screening Study (GRaSS)
- ClinicalTrials.gov ID
- NCT06882356
- Acronym / sponsor ID
- GRaSS / 2024p003709
- Conditions
- Glaucoma
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 2,000 participants (estimated)
- Lead sponsor
- Massachusetts Eye and Ear InfirmaryUniversity, hospital or other
- Collaborators
- Centers for Disease Control and Prevention
- Study start
- 16 Jul 2025 (actual)
- Primary completion
- Sep 2030 (estimated)
- Study completion
- Sep 2030 (estimated)
- First posted
- 18 Mar 2025 (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.
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
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 design
- Primary purpose
- Screening
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- This study uses a prospective interventional model to evaluate the effectiveness of integrating AI-based glaucoma screening with existing diabetic eye disease (DED) screening among diabetic patients. Participants will have fundus images assessed by AI for glaucoma in addition to DED, and have intraocular pressure measurement measured. Suspected glaucoma cases will receive virtual perimetry testing for confirmation, and those diagnosed with glaucoma will be referred for follow-up care. This study aims to compare glaucoma detection rates between combined DED and glaucoma screening versus DED-only screening, ultimately supporting early glaucoma detection and enhancing care access in underserved communities.
| Arm | Type | Receives |
|---|---|---|
| Combined DED and Glaucoma Screening | Experimental | Device: AI-based glaucoma screening, Device: IOP measurement, Device: Virtual Reality Visual Field TestingParticipants in this arm will have fundus photographs taken for diabetic eye disease screening analyzed by AI for signs of glaucoma. They will also have intraocular pressure measured. If glaucoma is suspected, participants will undergo virtual perimetry testing for further assessment. |
| DED Screening Only (Control Arm) | No intervention | –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. |
Who may qualify
- Ages
- 40 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
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 |
|---|---|---|
| AI-based glaucoma screeningAI analysis of fundus photographs to detect signs of glaucoma, added to AI-based diabetic eye disease screening | Device | Combined DED and Glaucoma Screening |
| IOP measurementIntraocular pressure measurement by Icare tonometer | Device | Combined DED and Glaucoma Screening |
| Virtual Reality Visual Field TestingVirtual Reality Visual Field Testing by the Olleyes device for participants suspected of having glaucoma | Device | Combined DED and Glaucoma Screening |
Primary outcome
Glaucoma detection
Time frame: 1 year from initial screening
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.
3 secondary outcomes
Cost-Effectiveness of Combined Screening vs. DED-Only Screening
Time frame: 1 year from initial screening
Participant Satisfaction with Screening Process
Time frame: Day of screening
Participant knowledge about glaucoma
Time frame: Day of screening
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 27 Aug 2026.
- Individual participant dataSharing planned: Yes. Deidentified study data
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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.
David S Friedman, MD, PhD, MPH principal investigator
Massachusetts Eye and Ear
7 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI-based glaucoma screening, IOP measurement and Virtual Reality Visual Field Testing in people with Glaucoma, run by Massachusetts Eye and Ear Infirmary at 7 sites in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
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: looking for participants now, as of the sponsor's last update on 27 Aug 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 7 sites in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
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?
Contact David S Friedman, MD, PhD, MPH (617-573-3094, grass@mgb.org), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Glaucoma detection (time frame: 1 year from initial screening). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 27 Aug 2026; AzTrials last refreshed its copy on 1 Nov 2026.