In search of answers on neuropathic pain

Scientists are working on a machine learning algorithm that can help to predict and prevent debilitating pain after spinal cord injury (SCI).

A UK study will track brain activity in SCI survivors as early as possible after injury, monitoring how central neuropathic pain (CNP) develops over time.

Using electroencephalograph (EEG) prediction techniques, the ultimate aim is to develop a machine learning algorithm that determines whether a newly injured person with SCI is likely to go on to suffer from CNP.

This will help to shape preventative measures, researchers say.

Stoke Mandeville Spinal Research (SMSR), based at the National Spinal Injuries Centre in Aylesbury, is funding the study alongside the charity, Spinal Research.

The research is being led by the University of Glasgow, and involving patients at the National Spinal Injuries Centre, Stoke Mandeville, and the National Spinal Injuries Unit (NSIU) in Glasgow.

Neuropathic pain is believed to be a consequence of a gradual build-up of hyperexcitability in the nerves, eventually leading to this debilitating condition.

Lead researcher at the University of Glasgow, Dr Aleksandra Vuckovic, says: “Neuropathic pain is extremely hard to treat. We propose to define predictive markers of CNP based on related brain activity accurately measured by EEG.

“Early EEG markers of pain will be used to create a machine learning system used to identify the risks to each newly injured patient enabling us to recommend effective preventive treatment.

“We will record EEG in more than 60 people across two spinal units in Scotland and England early after their spinal cord injuries and analyse brain activity of those who have and have not developed pain within the first six months.

“With this data, we create a ‘machine learning algorithm’ able to predict the risks of any patient in the future developing CNP. This will provide clinicians with the ability to better prescribe preventive treatments.”

SMSR trustee chair Richard Tolkien says: “We hope [this] will make a big difference to improving the everyday lives of people living with spinal cord injury.”