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AI helps diagnose dogs suffering chronic pain
Pain associated with CM is challenging to confirm
Facial changes associated with Chiari-like malformation identified

Cavalier King Charles spaniel (CKCS) dogs are predisposed to Chiari-like malformation (CM) – a disease that causes deformity of the skull, neck (cranial cervical vertebrae) and, in some extreme cases, leads to spinal cord damage called syringomyelia (SM). While SM is straightforward to diagnose, pain associated with CM is challenging to confirm.

A new artificial intelligence (AI) technique, developed by the University of Surrey, could eventually help veterinary professionals to identify individual dogs with CM. The same technique identified unique biomarkers that have inspired further research into the facial changes in dogs affected by Chiari-like malformation (CM).

In a paper published in the Journal of Veterinary Internal Medicine, researchers from Surrey’s Centre for Vision, Speech and Signal Processing (CVSSP) and the School of Veterinary Medicine (SVM) 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.

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. 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 SM.
 
Identification of these biomarkers inspired further research, that found that dogs with pain associated with CM had more brachycephalic features with reduction of nasal tissue and a well-defined stop.
 
Dr Penny Knowler, the SVM’s lead author of the work, 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."
 
Adrian Hilton, distinguished professor from the University of Surrey and director of CVSSP, said: “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.”
 
Both studies were funded by the Memory of Hannah Hasty Research Fund. The AI study was also supported by the Pet Plan Charitable Trust.

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Practices urged to audit neutering data

News Story 1
 RCVS Knowledge has called on vet practices to audit their post-operative neutering outcomes.

It follows the release of the 2024 NASAN benchmarking report, which collates data from neutering procedures performed on dogs, cats and rabbits.

The benchmarking report enables practices in the UK and Ireland to compare their post-operative outcomes to the national average. This includes the rate of patients lost to follow-up, which in 2024 increased to 23 per cent.

Anyone from the practice can submit the data using a free template. The deadline for next report is February 2026.

Visit the RCVS Knowledge website to complete an audit. 

Click here for more...
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RCVS pays tribute to well-loved equine vet

The RCVS and the Riding Establishments Subcommittee has paid tribute to well-loved veterinary surgeon and riding establishment inspector, Rebecca Hamilton-Fletcher MRCVS.

Linda Belton MRCVS, RCVS President, said: "I, along with my colleagues on the RESC, RCVS Council, RCVS Standards Committee, as well as RCVS staff, was very saddened to hear of the sudden death of Rebecca, or Becca as we knew her, last week.

"She was a true advocate for equine welfare and in her many years on the RESC worked to continually improve the quality and consistency of riding establishment inspections, all in the interests of enhanced horse welfare and rider safety."