Two graduate students from Western University have developed a ground-breaking method for predicting which intensive care unit (ICU) patients will survive a severe brain injury.
Matthew Kolisnyk and Karnig Kazazian combined functional magnetic resonance imaging (fMRI) with state-of-the art machine learning techniques to tackle one of the most complex issues in critical care.
Whether it is the result of a stroke, cardiac arrest or traumatic brain injury, lives can forever be changed by a serious brain injury. When patients are admitted to the ICU, families are faced with tremendous uncertainty. Will my loved one recover? Are they aware of what is going on? Will they ever be the same again? Despite these essential questions, health-care professionals are equally uncertain about the potential of a good recovery.
The graduate students are PhD candidates at Schulich School of Medicine & Dentistry in the lab of renowned neuroscientist Adrian Owen.
“For years we’ve lacked the tools and techniques to know who is going to survive a serious brain injury,” said Owen.
An interdisciplinary team of researchers from Western, in collaboration with neurologists at London Health Sciences Centre and Lawson Health Research Institute sought to find a solution to this problem. They were led by Loretta Norton, a psychology professor at King’s University College at Western, who was one of the first researchers in the world to measure brain activity in the ICU.
The team measured brain activity in 25 patients at one of London’s two ICUs in the first few days after a serious brain injury and tested whether it could predict who would survive and who would not.
