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Diabetic Peripheral Neuropathy: £1.4m awarded to create early test for

Scientists from the University of Liverpool and Manchester Metropolitan University have been awarded £1.4m to create an early test for Diabetic Peripheral Neuropathy (DPN), a complication caused by diabetes and which currently costs the NHS billions of pounds.

Diabetes is a major global problem, currently affecting over 4.9 million people in the UK and which costs the NHS more than £10 billion every year. 80% of these costs are due to diabetes complications, of which DPN is the most common and is responsible for 50-75% of non-traumatic limb amputations in people with diabetes.

Soon work will start on this collaborative project that will see investigators from both universities working alongside Aintree University Hospital and international collaborators such as Weill Cornell Medicine – Qatar. Together they’re developing this innovative solution to screen for DPN enabling early accurate diagnosis and helping doctors to intervene when it can be more easily treated with further damage stopped – well in advance of severe complications such as foot ulcers and amputations. Investigators include Dr Uazman Alam, Institute of Life Course and Medical Sciences, Prof Yaochun Shen, Electrical Engineering Department, Prof Yalin Zheng, Professor of Artificial Intelligence (AI) in Healthcare, Department of Eye and Vision Sciences at the University of Liverpool and Prof Liangxiu Han, Professor of Computational Science at Manchester Metropolitan University.

Professor Zheng said: “There is currently no effective early screening programme for DPN so we have brought together a group of world-class engineers, scientists, clinicians with extensive experience in their respective fields to develop the first kind of integrated intelligent imaging solution tailored to the needs of DPN screening.”

Starting this summer, the funded research will focus on the development of an ultra-high-resolution optical coherence tomography (OCT) device to detect DPN, specifically in the cornea – at the front of the eyes, and the development of novel AI solutions for the prediction of DPN using corneal OCT images. Early detection relies on being able to see small nerve fibres, which are affected first. The cornea is the only organ in which small nerve fibres can be directly visualised and therefore where early signs of DPN can be detected. Importantly, the new device will allow for non-contact rapid imaging of the corneal nerves, making the procedure non-invasive.

Dr Alam has previously pioneered the use of corneal nerves as a marker of DPN. Dr Alam said: “Unfortunately, current clinically utilised tools to diagnose for DPN are crude and as such diagnosis is late, putting patients at risk. The ability to assess small nerve fibres of the cornea has been a major advancement but widespread use has been limited as the current technique requires direct contact with the cornea. The development of a new OCT non-contact, rapid scanning of the cornea with embedded AI would be a major advancement allowing for more widespread use.”

The long-term study, which is expected to conclude in 2027, will ultimately result in a pilot clinical validation study in healthy volunteers and people with diabetes at Aintree University Hospital.

Professor Zheng concluded: “This is an ambitious project where we hope to create an innovative DPN screening solution that can ultimately be fully clinically utilised. I hope that early detection and timely treatment of DPN by our innovations will prevent disability and save lives with substantial benefit to the UK’s society and economy.”

The Engineering & Physical Sciences Research Council (EPSRC) has awarded more than £1m to the University of Liverpool for the study. Chief investigator Professor Zheng, will lead chief engineer Prof Yaochun Shen, and international expert in DPN, Dr Uazman Alam on this study. Manchester Metropolitan University has been awarded £380k for the project and Prof Liangxiu Han, along with Professor Yalin Zheng will develop the AI component of this study.

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