Diabetic RetinopathyNCT05324189
Automated AI-based System for Early Diagnosis of Diabetic Retinopathy
An observational study of Diabetic Retinopathy, run by The New York Eye & Ear Infirmary at 1 site in United States.
Trial summary
In this pivotal trial, we aim to perform a prospective study to find the efficacy of iPredict, an artificial intelligence (AI) based software tool on early diagnosis of Diabetic Retinopathy (DR)in the primary care, optometrist and other diabetes-screening clinics. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Diabetic Retinopathy
- What is being tested?
- Referable versus Non Referable Diabetic Retinopathy diagnostic test
- How many people
- 1,000 participants
- Where
- 1 siteUnited States
- Study dates
- 18 Apr 2022to 1 Dec 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
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 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Participants who fit the eligibility inclusion criteria and not the exclusion criteria.
Who may be able to join
- Age of Subjects: Patients ≥ 18 years of age.
- Gender of Subjects: Both males and females will be invited to participate.
- Subjects with diabetes (A1C level 6.5 or higher) or Fasting Plasma Glucose (blood sugar level) 126 mg/dL (≥7.0 mmol/L)
- Subjects must be willing and are able to comply with clinic visit, understand the study-related procedures/provisions, and provide signed informed consent.
- asymptomatic patients with DR.
Who cannot join
- Subject has retinal degenerations and retinal vascular diseases such as age-related macular degeneration or having undergone prior retinal surgery.
- History of ocular injections,
- Subject has persistent visual impairment in any eye;
- History of macular edema or retinal vascular (vein or artery) occlusion;
- laser treatment of the retina, or intraocular surgery other than cataract surgery without complications;
- Subject is currently enrolled in an interventional study of an investigational device or drug;
- Subject has ungradable clinical reference standard photographs (i.e., not gradable quality image). If the patient image is not gradable automatically, we will suggest the patient to refer the ophthalmologist.
Trial locations and contacts
1 site in 1 country.
United States1 site
New York Eye and Ear Infirmary of Mount Sinai
New York, New York, 10003
About this study
Official title: Pivotal Trial of Automated AI-based System for Early Diagnosis of Diabetic Retinopathy Using Retinal Color Imaging
In this pivotal trial, we aim to perform a prospective study to find the efficacy of iPredict, an artificial intelligence (AI) based software tool on early diagnosis of Diabetic Retinopathy (DR)in the primary care, optometrist and other diabetes-screening clinics. DR is one of the leading causes of blindness in the United States and other developed countries. Every individual with diabetes is at risk of DR. It does not show any symptom until the disease is progressed to advanced stages. If the disease is caught at an early stage, it can be prevented, managed or treated effectively. Currently, screening for DR is done by the Ophthalmologists, which is limited to areas with limited availability. This is also time-consuming and expensive. All of these can be complemented by automated screening and set up the screening in the primary care clinics.
Read the detailed description
In this pivotal trial, we aim to invite diabetic patients to participate in the trial by having non-dilated photos of their eyes taken by an FDA-approved DRS plus camera at their own doctor's office which will test the feasibility of our proposed automated AI based DR diagnosis software solution,. The color fundus photos will be captured and then be transmitted securely and analyzed by iHealthScreen's HIPAA compliant server at Amazon cloud. The deep learning module will analyze the image for finding the disease severity. The automated report will be generated which will report as referable DR or more than mild (mtm) DR detected i.e., moderate DR, severe DR - proliferative or non-proliferative DR or Non-referable DR or mtm DR not detected, i.e., mild DR or no DR.
The same images will be evaluated by 3 ophthalmologists and will be adjudicated if any disagreement between the gradings. The automatic and expert evaluation will be compared to compute the sensitivity, specificity and AUC.
- Conditions
- Diabetic Retinopathy
- Being tested
- Referable versus Non Referable Diabetic Retinopathy diagnostic test
- Medical subject headings
- Diabetic Retinopathy
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Referable versus Non Referable Diabetic Retinopathy diagnostic testDiagnostic test
Artificial intelligence read reports Referable versus Non Referable Diabetic Retinopathy
| Study group | Role | What they receive |
|---|---|---|
| More than mild (mtm) Diabetic Retinopathy (DR) Not Detected or Non referable DR | More than mild Diabetic Retinopathy (mtm DR) not detected or non referable DR using the iPredict's AI-based DR screening software utilizing color fundus imaging. Receives: Diagnostic Test: Referable versus Non Referable Diabetic Retinopathy diagnostic test | |
| More than mild (mtm) Diabetic Retinopathy (DR) Detected or Referable DR | More than mild Diabetic Retinopathy (mtm DR), moderate to severe DR detected, non proliferative DR detected, proliferative DR detected or referable DR using the iPredict's AI-based DR screening software utilizing color fundus imaging. Receives: Diagnostic Test: Referable versus Non Referable Diabetic Retinopathy diagnostic test |
What is being measured
The primary outcome is the main question the study is designed to answer.
Sensitivity of identification of referable and non-referable Diabetic Retinopathy (DR) for early diagnosis of DR
iPredict DR can detect non-referable DR (normal retina or mild DR) and referable DR (moderate or severe DR including non-proliferative, proliferative DR and diabetic macular edema) at a similar level of expert ophthalmologists. The output of AI model and ophthalmologists' grading will be compared for image level and subject level accuracy measurement.
Using the gold standard (i.e., the ophthalmologist's grading following ETDRS protocol), the sensitivity, specificity, precision, recall, accuracy, F-measure, positive predictive value and negative predictive value are calculated as: Sens=TP/(TP+FN) Spec=TN/(TN+FP) where TP is the number of true positives (referable DR subjects correctly classified), FN is the number of false negatives (referable DR subjects incorrectly classified as non-referable), TN is the number of true negatives (non-referable subjects correctly classified), and FP is the number of false positives (non-referable DR subjects incorrectly classified as referable DR).
Measured: 2 years
Specificity of identification of referable and non-referable Diabetic
iPredict DR can detect non-referable DR (normal retina or mild DR) and referable DR (moderate or severe DR including non-proliferative, proliferative DR and diabetic macular edema) at a similar level of expert ophthalmologists. The output of AI model and ophthalmologists' grading will be compared for image level and subject level accuracy measurement.
Measured: 2 years
Secondary outcomes (1)
The accuracy of identification of referable and non-referable DR for early diagnosis of DR
The accuracy of the iPredict-DR software developed by iHealthScreen system in early diagnosis of DR using color retinal photos vs. that of human expert graders/ophthalmologist for DR.
Performance thresholds were defined at 85.0% for sensitivity and 82.5% for specificity.
Measured: 2 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted12 Apr 2022
- Study start18 Apr 2022 (estimated)
- Primary completion1 Dec 2023 (estimated)
- Study completion1 Dec 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Diabetic RetinopathyStudies 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
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- The New York Eye & Ear Infirmary
- Sponsor type
- University, hospital or other
- Collaborators
- iHealthScreen Inc
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05324189
- Sponsor's protocol ID
- 21-00371
- Status last verified
- Nov 2021
- First submitted
- 8 Nov 2021
- Last updated
- 12 Apr 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
- Individual data sharing
- No: There is no IPD sharing plan at this time.
Study at a glance
From the registry record, last updated by the sponsor on 12 Apr 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Pivotal Trial of Automated AI-based System for Early Diagnosis of Diabetic Retinopathy Using Retinal Color Imaging
- ClinicalTrials.gov ID
- NCT05324189
- Acronym / sponsor ID
- 21-00371
- Conditions
- Diabetic Retinopathy
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 1,000 participants (estimated)
- Lead sponsor
- The New York Eye & Ear InfirmaryUniversity, hospital or other
- Collaborators
- iHealthScreen Inc
- Study start
- 18 Apr 2022 (estimated)
- Primary completion
- 1 Dec 2023 (estimated)
- Study completion
- 1 Dec 2024 (estimated)
- First posted
- 12 Apr 2022 (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.
In this pivotal trial, we aim to perform a prospective study to find the efficacy of iPredict, an artificial intelligence (AI) based software tool on early diagnosis of Diabetic Retinopathy (DR)in the primary care, optometrist and other diabetes-screening clinics. DR is one of the leading causes of blindness in the United States and other developed countries. Every individual with diabetes is at risk of DR. It does not show any symptom until the disease is progressed to advanced stages. If the disease is caught at an early stage, it can be prevented, managed or treated effectively. Currently, screening for DR is done by the Ophthalmologists, which is limited to areas with limited availability. This is also time-consuming and expensive. All of these can be complemented by automated screening and set up the screening in the primary care clinics.
Detailed description
In this pivotal trial, we aim to invite diabetic patients to participate in the trial by having non-dilated photos of their eyes taken by an FDA-approved DRS plus camera at their own doctor's office which will test the feasibility of our proposed automated AI based DR diagnosis software solution,. The color fundus photos will be captured and then be transmitted securely and analyzed by iHealthScreen's HIPAA compliant server at Amazon cloud. The deep learning module will analyze the image for finding the disease severity. The automated report will be generated which will report as referable DR or more than mild (mtm) DR detected i.e., moderate DR, severe DR - proliferative or non-proliferative DR or Non-referable DR or mtm DR not detected, i.e., mild DR or no DR.
The same images will be evaluated by 3 ophthalmologists and will be adjudicated if any disagreement between the gradings. The automatic and expert evaluation will be compared to compute the sensitivity, specificity and AUC.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| More than mild (mtm) Diabetic Retinopathy (DR) Not Detected or Non referable DR | – | Diagnostic Test: Referable versus Non Referable Diabetic Retinopathy diagnostic testMore than mild Diabetic Retinopathy (mtm DR) not detected or non referable DR using the iPredict's AI-based DR screening software utilizing color fundus imaging. |
| More than mild (mtm) Diabetic Retinopathy (DR) Detected or Referable DR | – | Diagnostic Test: Referable versus Non Referable Diabetic Retinopathy diagnostic testMore than mild Diabetic Retinopathy (mtm DR), moderate to severe DR detected, non proliferative DR detected, proliferative DR detected or referable DR using the iPredict's AI-based DR screening software utilizing color fundus imaging. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Participants who fit the eligibility inclusion criteria and not the exclusion criteria.
Key inclusion criteria (5 listed)
- Age of Subjects: Patients ≥ 18 years of age.
- Gender of Subjects: Both males and females will be invited to participate.
- Subjects with diabetes (A1C level 6.5 or higher) or Fasting Plasma Glucose (blood sugar level) 126 mg/dL (≥7.0 mmol/L)
- Subjects must be willing and are able to comply with clinic visit, understand the study-related procedures/provisions, and provide signed informed consent.
- asymptomatic patients with DR.
Key exclusion criteria (7 listed)
- Subject has retinal degenerations and retinal vascular diseases such as age-related macular degeneration or having undergone prior retinal surgery.
- History of ocular injections,
- Subject has persistent visual impairment in any eye;
- History of macular edema or retinal vascular (vein or artery) occlusion;
- laser treatment of the retina, or intraocular surgery other than cataract surgery without complications;
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 |
|---|---|---|
| Referable versus Non Referable Diabetic Retinopathy diagnostic testArtificial intelligence read reports Referable versus Non Referable Diabetic Retinopathy | Diagnostic test | More than mild (mtm) Diabetic Retinopathy (DR) Detected or Referable DR, More than mild (mtm) Diabetic Retinopathy (DR) Not Detected or Non referable DR |
Primary outcome
Sensitivity of identification of referable and non-referable Diabetic Retinopathy (DR) for early diagnosis of DR
Time frame: 2 years
iPredict DR can detect non-referable DR (normal retina or mild DR) and referable DR (moderate or severe DR including non-proliferative, proliferative DR and diabetic macular edema) at a similar level of expert ophthalmologists. The output of AI model and ophthalmologists' grading will be compared for image level and subject level accuracy measurement. Using the gold standard (i.e., the ophthalmologist's grading following ETDRS protocol), the sensitivity, specificity, precision, recall, accuracy, F-measure, positive predictive value and negative predictive value are calculated as: Sens=TP/(TP+FN) Spec=TN/(TN+FP) where TP is the number of true positives (referable DR subjects correctly classified), FN is the number of false negatives (referable DR subjects incorrectly classified as non-referable), TN is the number of true negatives (non-referable subjects correctly classified), and FP is the number of false positives (non-referable DR subjects incorrectly classified as referable DR).
Specificity of identification of referable and non-referable Diabetic
Time frame: 2 years
iPredict DR can detect non-referable DR (normal retina or mild DR) and referable DR (moderate or severe DR including non-proliferative, proliferative DR and diabetic macular edema) at a similar level of expert ophthalmologists. The output of AI model and ophthalmologists' grading will be compared for image level and subject level accuracy measurement.
1 secondary outcome
The accuracy of identification of referable and non-referable DR for early diagnosis of DR
Time frame: 2 years
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 Apr 2022.
- Individual participant dataSharing planned: No. There is no IPD sharing plan at this time.
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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. This study is not recruiting at the moment.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Diabetic Retinopathy, run by The New York Eye & Ear Infirmary at 1 site 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?
The sponsor lists 5 inclusion and 7 exclusion criteria. 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: status not confirmed, as of the sponsor's last update on 12 Apr 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact R. Theodore Smith, MD, PHD (646-943-7925, rolandtheodore.smith@mssm.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Sensitivity of identification of referable and non-referable Diabetic Retinopathy (DR) for early diagnosis of DR (time frame: 2 years). The study lists 2 primary outcomes in all. 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 12 Apr 2022.