A new technique could help diagnose dogs suffering from chronic pain.

The new artificial intelligence (AI) approach was developed by the University of Surrey in England.

Researchers hope it could eventually help veterinarians quickly identify dogs with a chronic disease that causes crippling pain.

This would be particularly relevant to Cavalier King Charles Spaniels.

The same technique identified unique biomarkers which inspired further research into the facial changes in dogs affected by Chiari-like malformation (CM).

Cavalier King Charles are predisposed to CM - a disease which causes deformity of the skull, neck and in some extreme cases can lead to spinal cord damage called syringomyelia (SM).

While SM is straightforward to diagnose, pain associated with CM is difficult to confirm.

In a paper published by the Journal of Veterinary Internal Medicine, researchers detail how they used a completely automated, image mapping method to discover patterns in MRI data that could help vets identify dogs that suffer from CM associated pain.

A Cavalier King Charles Spaniel greets people a dog show in January 2019 | Image: Alex Milan Tracy/SIPA USA/PA Images

The research helped identify features that characterise the differences in the MRI images of dogs with clinical signs of pain associated with CM, and those with syringomyelia, from healthy dogs.

Dr Michaela Spiteri is lead author of the study: "The success of our technique suggests machine learning can be developed as a diagnostic tool to help treat Cavalier King Charles Spaniel's that are suffering from this enigmatic and terrible disease.

"We believe that AI can be a useful tool for veterinarians caring for our four-legged family members."

Identification of these biomarkers inspired a further study, which found that dogs with pain associated with CM had more brachycephalic features - having a relatively broad, short skull - with reduction of nasal tissue and a well-defined stop.

Lead author Dr Penny Knowler said: "This study suggests that the whole skull, rather than just the hindbrain, should be analysed in diagnostic tests.

"It also impacts on how we should interpret MRI from affected dogs and the choices we make when we breed predisposed dogs and develop breeding recommendations."

Professor Adrian Hilton from the University of Surrey added: "This project demonstrates the potential for AI using machine learning to provide new diagnostic tools for animal health.

"Collaboration between experts in CVSSP and Surrey's School of Veterinary Medicine is pioneering new approaches to improve animal health and welfare."