A Clinical Doctor's Explanation of Health Tech in Asia (Series＃2）
SELENA+, retinal imaging system to assist ophthalmologists in diagnosis
Clinical Doctor, Medical communication
Possible Benefits of Retinal Image Reading Assistance
In recent years, the use of AI in clinical practices to assist with medical interviewing and CT imaging has been attracting attention. Effective use of AI can reduce the burden on physicians, maintain the quality of medical care, allow patients to receive optimal treatment, and reduce medical costs. “SELENA+” by EyRIS, introduced here, is an AI that assists in retinal disease screenings. When a patient's retinal data is submitted through the web platform, “SELENA+” the images are analyzed for signs of diabetic retinopathy, glaucoma suspect, and age-related macular degeneration, and sends back a report with the findings. The three diseases that “SELENA+” is currently able to detect are well known to be the leading causes of blindness.
In particular, the number of patients with diabetes, which can cause diabetic retinopathy, is increasing worldwide. According to the International Diabetes Federation, there will be 537 million people with diabetes in 2021, or one in ten adults. This number is expected to increase by more than 200 million in the next 20 years. It is known that about one in three people with diabetes will develop diabetic retinopathy, a complication of the disease. Diabetic retinopathy can lead to blindness due to the rupturing of blood vessels in the retina, significantly reducing the patient's quality of life. However, it is believed that about 80% of diabetic retinopathy cases can be prevented, or its progression can be delayed. In other words, once diabetes is diagnosed, it is important to have regular fundus examinations to check the condition of the retina to prevent blindness caused by diabetic retinopathy.
Against this background, “SELENA+” was developed by clinicians and technicians from the Singapore Eye Research Institute and the National University of Singapore to detect signs of diabetic retinopathy and reduce the rate of preventable blindness caused by diabetes. If “SELENA+” is used as a screening tool for retinal diseases, it will be possible to identify the patients who need treatment and those who do not, thus reducing the workload of the doctors and nurses in these practices. As for the accuracy of the test, the results showed that “SELENA+” is able to detect 100% of vision-threatening diabetic retinopathy cases, which puts patients at risk of blindness, and achieved sensitivity and specificity of over 90% for glaucoma suspect and age-related macular degeneration.
“SELENA+” has been highly evaluated worldwide and is already being used in clinical settings. For example, in Singapore, the country where the device was developed, it has been selected for a nationwide screening test. In the U.S. state of New Jersey, “SELENA+” was used in conjunction with medical students to provide retinal disease screening tests in telemedicine.
In the future, EyRIS, the company that produced “SELENA+”, plans to develop next-generation products to diagnose the risk of cardiovascular events, detect patient’s chronic kidney diseases, cardiovascular diseases, and dementia. Chronic kidney disease is a disease in which the function of the kidneys declines due to a variety of causes, including lifestyle-related diseases such as diabetes and hypertension, collagen diseases, and infections. When the function of the kidneys deteriorates significantly, the body is unable to eliminate excess water and waste products as urine, and dialysis or a kidney transplant may be necessary. However, as with diabetic retinopathy, there are usually no symptoms in the early stages of chronic kidney disease, and by the time the disease is noticed, it is often far advanced. EyRIS is working on the development of a screening test to diagnose chronic kidney disease based on changes in the blood vessels in the retina. At present, urine tests are used to detect chronic kidney disease at an early stage. Because abnormalities in the blood vessels of the kidneys cause protein to be released in the urine, which should not normally be released, and can be checked by urine tests. It is also possible that a major abnormality in the blood vessels of the kidneys has occurred when protein is found in the urine. Since retinal blood vessels are said to reflect the condition of blood vessels in the whole body, it may be possible to diagnose chronic kidney disease by retinal findings before urine findings.
Therefore, the retinal disease screening test using AI is expected to lead to early detection and early treatment of various systemic diseases and to not only to check for eye diseases.
EyRIS is a Singapore-based startup specializing in the development of AI deep learning systems in the healthcare industry. Their flagship product “SELENA+” is the only Artificial Intelligence deep learning system in the world with regulatory approval for the detection of three diseases (diabetic retinopathy, glaucoma suspect, and age-related macular degeneration). Within 18 months they were able to secure the ISO 13485 recognition and five regulatory approvals, Singapore’s HSA, European CE mark, Malaysia MDA, Indonesian regulatory certification and ANVISA in Brazil. EyRIS has achieved multiple awards and recognitions locally and internationally. With a presence in over 26 countries now, they have built up their customer base significantly.
- EyRIS Pte. Ltd. website https://eyris.io/technology.cfm
- “IDF Diabetes Atlas 10th edition” International Diabetes Federation, https://diabetesatlas.org/
- “Chronic Kidney Disease” By Anna Malkina, MD, University of California, MSD MANUAL Professional Version, Content last modified Oct 2021, https://www.msdmanuals.com/en-jp/professional/genitourinary-disorders/chronic-kidney-disease/chronic-kidney-disease
- ”AI-Rad Companion, Chest CT” Siemens Medical Solutions USA, Inc., https://www.siemens-healthineers.com/en-us/digital-health-solutions/digital-solutions-overview/clinical-decision-support/ai-rad-companio
We have not received any rewards from the publishers for writing this manuscript.
The information contained in this article is compiled by the respective authors based on publicly available information. We assume no responsibility whatsoever for any damage or disadvantage caused by actions taken based on such information. Unauthorized reproduction of articles, photos, charts, etc. is prohibited.
Copyright © 2022 LSMIP office / CM Plus Corporation
A Series of Articles
No information is found.