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Posted: 2019-11-07

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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