Researchers are working on a prototype device using equipment that is already available.
Scientists are developing a test that will use artificial intelligence (AI) to detect a major complication of diabetes in the hope it could become a standard screening tool for those living with the condition.
Researchers from the University of Liverpool and Manchester Metropolitan University are tweaking equipment currently used by high street optometrists to detect diabetic peripheral neuropathy (DPN).
It will work by scanning nerves at the front of the eye rather than the back, with the AI element of the device able to predict future damage.
Dr Uazman Alam from the Institute of Life Course and Medical Sciences at the University of Liverpool told the PA news agency: “What we know from a body of work which I’ve been very heavily involved in over the past 15 to 20 years, is that the nerves at the front of the eye actually reflect nerve damage elsewhere in the body.”
DPN is a major complication of diabetes and the number one cause of limb amputation in diabetic patients.
It is caused when high blood sugar levels damage the nerves that send messages from the brain and spinal cord to the rest of the body.
The team has been given £1.4 million to develop the new machine, which is essentially a redesigned optical coherence tomography (OCT) device, a tool used by optometrists to scan the back of the eye.
“Our device will scan the front of the eyes,” Dr Alam said. “The nerves are very small and therefore it needs a higher resolution.”
It will also have AI “embedded in it” he added, and could save clinicians time and save the NHS money.
The test currently used to detect sensory loss in the limbs of diabetic people is called the 10 gram monofilament, but Dr Alam described it as “quite crude”.
He said it could “miss a lot of people” who have DPN, adding: “The whole point of this project is really to try to develop it as a screening tool.
“At the moment, [patients] are screened, but the tests we use aren’t sensitive. This we’re hoping will be a lot more sensitive.
“Rather than having to take measurements of the nerves, we can use the entire image to detect the nerve damage and actually predict those who will develop it.”
He added: “In nearly all countries, diabetes is going to increase. For us to have somebody individually undertake the [10 gram monofilament] test and detect nerve damage is quite time consuming and would be a major economic burden to healthcare services.”
In June, a study suggested more than one billion people globally could be living with diabetes in the coming decades.
The paper, published by The Lancet Diabetes and Endocrinology journal, said that by 2050, some 1.3 billion people will have diabetes – more than double the 529 million cases in 2021.
Dr Alam also said AI prediction is an important part of the team’s work.
He added: “I think the importance of it is that OCT is a technology that’s out there and is currently being used in a clinical environment in the high street.
“So it wouldn’t be that far-fetched that this would potentially be used.”
Dr Alam will be working on the project alongside University of Liverpool colleagues Prof Yaochun Shen of the electrical engineering department, and Yalin Zheng, a professor of AI in healthcare in the department of eye and vision sciences, as well as Liangxiu Han, professor of computational science at Manchester Metropolitan University.
It is hoped the study will conclude in 2027 and will ultimately result in a pilot clinical validation trial in healthy and diabetic volunteers at Aintree University Hospital in Liverpool.
Dr Alam predicts that AI it will “be an important facet of all healthcare systems at some point” but “will need developing further” before it is adopted widely.
“I think we have to remember that AI is not just the images that we’re talking about, but it can also be data as well,” he said. “It’s here to stay. We need to develop it in a way that is ethical.
“I think it’s important and I think it probably actually needs to be taught in medical schools as well. It’s going to be entrenched within the healthcare system.”