The future role of the ophthalmologist in diabetic retinopathy (DR) care will be focused on consultations of difficult and complicated cases and their treatment. |
Telemedicine augmented by artificial intelligence (AI) will make the DR screening system more effective and cheaper, with better coverage of the diabetic population. |
The screening of DR will be done by eye technicians, general practitioners or by patients themselves supported by AI. |
Digital Features
Introduction
Methods
Results
Techniques
Stable, Classic Non-mydriatic Fundus Cameras
Mobile Classic Non-mydriatic Fundus Cameras (moved from location to location)
Mobile, On-Vehicle Hard-Mounted Diagnostic Sets
Ultra-Wide-Field (UWF) Diagnostic Sets
Optical Coherence Tomography (OCT)-Based Diabetic Retinopathy Screening
Portable Fundus Cameras
Smartphone-Based Retinal Imaging
Method | Main features | References |
---|---|---|
Stable fundus camera | Fundus camera (narrow angle) located in one place | |
Mobile fundus camera | Fundus camera (narrow angle) moved from location to location; mounted in offices; more effective | [63] |
Mobile, on-vehicle hard-mounted diagnostic sets | Diagnostic sets (fundus camera [narrow- and wide-field] and software) hard-mounted on specially adapted vehicles; moved from one location to another | |
Ultra-wide-field (UWF) diagnostic sets | Ultra-wide fundus cameras hard-mounted in offices or on vehicles | |
OCT based diabetic retinopathy screening | Screening with use of OCT (method of choice for diabetic macular edema) | |
Portable fundus cameras | Screening with portable handheld camera (low cost, possible in-home testing) | |
Adopted smartphones | Screening with commercially available smartphones with proper adapters (low cost, possible in-home testing |
The Process of Photograph-Taking
Grading Methods
Human Grading
Artificial Intelligence
Remote Grading
Limitations and Positive Aspects of Telescreening of DR
Limitation | Reason | Solution | References |
---|---|---|---|
Poor quality of images | Small pupil | Mydriasis | |
Poor transparency of optic media | Cataract extraction | ||
Screening program organizational problems | Need for trained photographers, graders and retina specialists | Training of technicians, nurses and general practitioners In-home testing with self-preliminary images reading AI grading | |
High cost of screening | Expensive screening devices and software, crew costs | Mobile screening sets Cheap portable cameras Smartphone screening Telescreening AI-assisted screening | |
Poor sensitivity of DR detection | 1-, 2- or 3-field images- with too small coverage of retina | Ultra-wide fundus cameras use | |
Low percentage of follow-up | Social and educational factors | Basic diabetic education | |
No positive results of telescreening | Small widespread in population | Diabetic education | |
Need for co-pay | Better social insurance | ||
The more advanced the diagnosis, the more expensive | Expensive and complex screening schemes | Common use of AI | [39] |
Long waiting time for final diagnosis | Insufficient screening system | AI grading | |
Lack of an integrated virtual platform for DR screening | Lack of proper software | Development of screening software | [70] |
Positive aspect | References |
---|---|
High accuracy in diabetic retinopathy diagnosis | |
Prevention of unnecessary referrals (reduction by as much as 75%) | |
High percentage (70%) of screening of diabetics in rural regions | |
Improved medical care in remote regions | |
More diabetics receiving eye care with telemedicine than with traditional direct care scheme | |
High satisfaction rate of screened patients | |
High satisfaction rate of medical staff | |
Recommendation for follow-up given to diabetics | |
Diagnosis of non-ocular problems or other incidental eye findings | |
Computer-assisted screening more cost-effective | |
Highly effective AI-assisted process of image reading | |
Optimization of current resource use and lower total costs of telescreening than when virtual (driven) clinics were used |