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Details of Grant 

EPSRC Reference: EP/V029983/1
Title: Window into the Mind: Handheld Spectroscopic Eye-safe Device (EyeD) for Neurodiagnostics
Principal Investigator: Goldberg Oppenheimer, Dr P
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Queen Elizabeth Hospital Birmingham
Department: Chemical Engineering
Organisation: University of Birmingham
Scheme: Standard Research
Starts: 27 January 2021 Ends: 26 January 2024 Value (£): 562,453
EPSRC Research Topic Classifications:
Artificial Intelligence Med.Instrument.Device& Equip.
Optical Devices & Subsystems
EPSRC Industrial Sector Classifications:
Healthcare
Related Grants:
EP/V029940/1
Panel History:
Panel DatePanel NameOutcome
10 Nov 2020 Healthcare Technologies Investigator Led Panel Nov 2020 Announced
Summary on Grant Application Form
Traumatic brain injury (TBI) is a leading cause of morbidity and mortality worldwide, with a high complication rate requiring long-term care, creates prolonged post-traumatic neurological disorders and is potentially fatal with annual socioeconomic cost in the UK of £7.5 Billion per year. While critical decisions affecting treatment must be made rapidly, TBI is notoriously hard to diagnose pre-hospitalisation, sometimes resulting in incorrect patient management. Timely assessment of injury severity is a priority in the correct treatment of TBI patients. However, this is poorly supported by current technologies, which fall short of the diagnostic needs, exhibiting poor-sensitivity, special-handling requirements and complicated, costly procedures.

A non-invasive portable technique to diagnose and monitor TBI and neurodegenerative diseases is proposed, by measuring changes to the optic nerve, visible at the back of the eye. The optic nerve, bathed in cerebrospinal fluid, which is in continuity with the central nervous system, constitutes an optically clear 'window to the brain'. The aim is to develop a portable technology to detect biochemical changes in cerebrospinal fluid in response to brain injury using specialised optical collected using a technique known as Raman spectroscopy. This provides a non-invasive, highly-sensitive method for the detection of biomarkers in the eye, and yet it can be packaged as a low-cost, hand-held device.

For delivering such a sensitive and rapid diagnostic technology, it is crucial to accurately identify these specialised Raman signals originating from different parts of the eye. To tackle these challenges, advanced computational methods, known as "machine learning", will be developed to embrace the 'noise' from the data and enable a generic framework for intelligent diagnosis. Unlike traditional packages, this method will perform data analysis directly in the web browser using cloud technologies as an open-source. Building upon these, this innovative technology will allow TBI measurements to take place at the point-of-care via a non-ionizing scan of the back-of-the-eye to detect biochemical changes without the need for a painful lumbar puncture (to extract the cerebrospinal fluid) or expensive, dangerous radiological scans.

Our prime objective is to deliver a technology offering improved health, more effective patient-care and a better quality of life for patients suffering from neurotrauma. It will be designed for use on-site by doctors and paramedic crews to provide timely and cost-effective diagnosis and triaging and will be used by ambulance trusts, sports organisations, GPs, hospitals and the Ministry of Defence. Rapid diagnosis in the early-clinical phase in a non-invasive, cost-effective way will lay the platform for a range of improvements in personalised medicine and management. Predominantly focussed on timely TBI-detection, our device would allow for better patient triaging, reducing the strain on the healthcare system. In addition to delivering the timely intervention and organised trauma-care to nearly a million individuals nationally, it will decelerate the patients' cognitive decline, reduce in-hospital mortality, save thousands of lives a year, avoid long-term hospital stays, and reduce a major burden on the NHS and the taxpayer.

Key Findings
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Potential use in non-academic contexts
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Summary
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Organisation Website: http://www.bham.ac.uk