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| ID | Type | Description | Link |
|---|---|---|---|
| R44EY031202 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| National Institutes of Health (NIH) | NIH |
| National Eye Institute (NEI) | NIH |
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The purpose of this study is to perform a pivotal trial of iPredict, an automated AI-based system for early diagnosis and prediction of late AMD in primary care and ophthalmology settings. Patients will be invited to participate in this study by having non-dilated photos of their eyes taken by an FDA approved fundus camera (DRSPlus from Centervue Inc., CA), at their primary care doctor's office or general ophthalmologist office. The photos will then be transmitted securely and analyzed by computer in the cloud (telemedicine features). Sufficient accuracy of the automatic system has been established compared to the ophthalmologist's diagnosis. In this study, we aim to validate the system against the prospectively taken OCT image and color fundus images.
The purpose of this study is to perform a pivotal trial of iPredict, an automated AI-based system for early diagnosis and prediction of late AMD in primary care and ophthalmology settings. Patients will be invited to participate in this study by having non-dilated photos of their eyes taken by an FDA approved fundus camera (DRSPlus from Centervue Inc., CA), at their primary care doctor's office or general ophthalmologist office. The photos will then be transmitted securely and analyzed by computer in the cloud (telemedicine features). Sufficient accuracy of the automatic system has been established compared to the ophthalmologist's diagnosis. In this study, we aim to validate the system against the prospectively taken OCT image and color fundus images.
Background AMD affects 15 million Americans, with 200,000 new cases diagnosed each year. At present, there is no treatment for dry AMD. Besides blindness, AMD has other indirect complications such as depression, social dependency, and the risk of fall and injury. The prevalence of this disease is expected to grow substantially as life expectancy continues to increase and record numbers of Baby Boomers enter their senior years. The total direct cost of AMD is $220 billion per year and is expected to increase ~1.5 fold. The Age-Related Eye Disease Study (AREDS) showed that specific vitamin supplementation protocols can reduce the risk of progression from intermediate to late AMD by ~25% which in turn could lower the cost of AMD 17.6% if fully implemented. To accomplish this, it is crucial to perform large scale population screening to identify the individuals with early- or intermediate-stage of AMD and better predict those at risk of developing late AMD, but such a system is currently not available. Although articles have been published on automatic AMD pathology detection, none of these systems are available for screening due to lack of validation and commercial readiness. Considering this urgent need, we aim to develop an automated tool iPredict for early diagnosis and prediction of AMD, and make it widely available in both urban and remote/rural areas and for large- scale screening (through its telemedicine features), and thereby prevent blindness.
Primary and Secondary Study Endpoints The accuracy of the iPredict software developed by iHealthScreen system in early diagnosis of AMD using color retinal photos vs. that of human expert graders for AMD. Also, the prediction of late AMD progression in 1 or two years.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| One group | One Cohort |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| No intervention. | Device | No intervention. Evaluate the automated AMD screening software. |
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| Measure | Description | Time Frame |
|---|---|---|
| Referable and non-referable AMD. And Predict the Incidence of AMD in 1 year or 2-year. | Referable and non-referable AMD. And Predict the Incidence of AMD in 1 year or 2-year. | 1 year or 2-year |
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Inclusion Criteria:
Exclusion Criteria:
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This study will be carried at the primary care and general ophthalmology clinic. The total number of patients to be recruited is 1076. Subjects will be recruited during their routine ophthalmology visit, and each subject will be identified by their ophthalmologist as appropriate to take part in the study. After a short verbal explanation, the ophthalmologist may ask the subject to take part in the study. Patients will be recruited without selection by eye diagnosis from the clinics.
Both males and females will be invited to participate. Patients will be over 50 since AMD is overwhelmingly a disease of this population.
It is anticipated that the subjects will be of all races and ethnic origins, in line with our diverse clinic populations in New York city. Provided that they fit the study criteria, all subjects are invited to participate. However, we aim to recruit the majority as white ethnicity as AMD is a disease for predominantly white ethnicity.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Alauddin Bhuiyan | Contact | 718-926-9000 | bhuiyan@ihealthscreen.org | |
| Fariha Nuha, BS (Comp. Biology) | Contact | 718-912-0837 | fariha@ihealthscreen.org |
| Name | Affiliation | Role |
|---|---|---|
| Alauddin Bhuiyan, PhD | iHealthScreen Inc | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| iHealthScreen Inc. | Recruiting | Richmond Hill | New York | 11418 | United States |
In the future we will share the data.
after 5 years
To be enrolled in the NIH data sharing portal - dbGAP.
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| ID | Term |
|---|---|
| D008268 | Macular Degeneration |
| ID | Term |
|---|---|
| D012162 | Retinal Degeneration |
| D012164 | Retinal Diseases |
| D005128 | Eye Diseases |
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