AI technique could help diagnose dogs suffering painful disease, researchers say

A new artificial intelligence technique may help veterinarians identify a painful chronic disease in Cavalier King Charles Spaniel dogs.

The U.K.-based University of Surrey announced that its AI technology uses MRI data to help vets identify dogs experiencing pain from Chiari-like malformation. Cavalier King Charles Spaniels are predisposed to the disease, which causes deformity of the skull and neck, and in some cases leads to spinal cord damage, called syringomyelia.

Syringomyelia is straightforward to diagnose, but it’s difficult to diagnose pain from Chiari-like malformation.

Researchers, who published their findings in the Journal of Veterinary Internal Medicine, said their study helped identify biomarkers that characterize the difference in MRI images of healthy dogs versus dogs with clinical signs of pain associated with these chronic diseases. 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 Chiari-like malformation, 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 Spaniels that are suffering from this enigmatic and terrible disease,” Dr. Michaela Spiteri, one of the lead authors of the study, said in the announcement. “We believe that AI can be a useful tool for veterinarians caring for our four-legged family members.”

Identification of these biomarkers led to another study, published in the same journal, finding that dogs with pain associated with Chiari-like malformation 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 analyzed in diagnostic tests,” said co-lead author Dr. Penny Knowler. “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.”