AI-Powered Eye Scans Revolutionize Diabetic Nerve Damage Detection
Researchers from the University of Liverpool and Manchester Metropolitan University are revolutionizing the detection of diabetic peripheral neuropathy (DPN) by utilizing AI-powered eye scans. The team is enhancing the equipment currently used by high street optometrists to identify this major complication of diabetes, which is responsible for the most limb amputations in diabetic patients.
Traditionally, optometrists scan the back of the eye using optical coherence tomography (OCT) devices. However, the researchers discovered that scanning the nerves at the front of the eye can reflect nerve damage occurring elsewhere in the body. By optimizing the device’s resolution and incorporating AI technology, the team aims to predict future nerve damage and enhance sensitivity in detecting DPN.
Dr. Uazman Alam from the University of Liverpool’s Institute of Life Course and Medical Sciences explained that the current method of assessing sensory loss in diabetic individuals, called the 10 gram monofilament test, is quite crude and can miss potential cases of DPN. The objective of this project is to develop a more accurate screening tool that is both sensitive and efficient.
By utilizing AI algorithms embedded in the eye scanning device, clinicians can save time and potentially reduce healthcare costs for the National Health Service (NHS). Dr. Alam highlighted the increasing prevalence of diabetes worldwide and emphasized the economic burden associated with individually conducting the 10 gram monofilament test to detect nerve damage in patients.
A recent study published in The Lancet Diabetes and Endocrinology journal projected that by 2050, there could be more than 1.3 billion people globally living with diabetes, more than double the current number. Therefore, the need to improve diagnostic methods for diabetic complications, such as DPN, is paramount.
Dr. Alam expressed confidence in the potential role of AI in healthcare systems, as OCT devices are already being used in clinical settings and on the high street. While acknowledging the need for further development and ethical considerations, he suggested that AI could become an integral part of medical education and healthcare systems.
The research project, led by Dr. Alam and in collaboration with Prof Yaochun Shen, Prof Yalin Zheng, and Prof Liangxiu Han, aims to conclude in 2027 with a pilot clinical validation trial at Aintree University Hospital in Liverpool. If successful, this groundbreaking technology could significantly improve the early detection and prediction of nerve damage in diabetic patients.
In conclusion, the utilization of AI-powered eye scans has the potential to revolutionize the detection of diabetic peripheral neuropathy. By scanning the nerves at the front of the eye and using AI algorithms, clinicians may be able to predict future nerve damage and enhance the sensitivity of DPN detection. This development could prove invaluable in reducing the number of limb amputations caused by diabetic complications while saving time for healthcare professionals and optimizing healthcare resources.
