AI could help diagnose breed of dogs suffering from chronic pain
Researchers from the University of Surrey have developed a new artificial intelligence (AI) technique which could help veterinarians quickly identify Cavalier King Charles Spaniel (CKCS) dogs with a chronic disease that causes them crippling pain.
The same technique identified unique biomarkers which inspired the team to undergo further research into the facial changes in a number of breeds affected by Chiari-like malformation (CM). CKCSs are prone to CM: a disease that causes deformity of the skull, the neck (cranial cervical vertebrae), and – in some extreme cases – lead to spinal cord damage known as syringomyelia.
Furthermore, while syringomyelia is straightforward to diagnose in spaniels, pain associated with CM is considered a challenge for veterinarians to confirm.
CM does not only occur in Cavalier King Charles Spaniels; other breeds, including Chihuahuas, Yorkshire Terriers, Pomeranians and other toy breed are known to have the condition. Furthermore, Boston Terriers and Staffordshire Bull Terriers may occasionally suffer from the condition.
In a paper published by Journal of Veterinary Internal Medicine, the team from Surrey’s Centre for Vision, Speech and Signal Processing (CVSSP) and the School of Veterinary Medicine (SVM), detailed 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.
As part of the research, the team 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. The AI identified the floor of the third ventricle and its close neural tissue, and the region in the sphenoid bone as biomarkers for pain associated with CM and the presphenoid bone and the region between the soft palate and the tongue for syringomyelia.
“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,” said Dr Michaela Spiteri from CVSSP. “We believe that AI can be a useful tool for veterinarians caring for our four-legged family members.”
Identification of these biomarkers also stirred a further study by the researchers. Here, they 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.
“This study suggests that the whole skull, rather than just the hindbrain, should be analysed in diagnostic tests,” said Dr Penny Knowler of Surrey’s Canine Chiari team at SVM. “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.”
“This project demonstrates the potential for AI using machine learning to provide new diagnostic tools for animal health,” said Adrian Hilton, a distinguished professor from the University of Surrey.
Hilton, who is also the director of CVSSP added: “Collaboration between experts in CVSSP and Surrey’s School of Veterinary Medicine is pioneering new approaches to improve animal health and welfare.”
In May, longest-running cat café in the UK, Lady Dinah’s Cat Emporium in London, announced plans to trial digital pet health monitoring technology to provide insights into the behaviour, rest and activity patterns of its cats.