New technology key to better care for whiplash injuries New research is set to
occurred in both men and women, but to a larger extent in women and in the deep muscles, attaching directly to the spine. “Our study demonstrated a game-changing approach which may have significant implications for the diagnosis and treatment of those with a whiplash injury. “The gains in MRI technology and the rapid acquisition techniques mean we are able to diagnose injuries which “There are many personal stories where people have experienced long term constant pain, but no physical changes could be found through imaging. “Importantly, this wouldn’t have been captured in the past.
new process could be incorporated into clinical radiology practice, which would open up new treatment pathways.” Professor Elliott said the findings are significant given that more than 2.6 million Australians and four million Americans suffer a whiplash-associated- disorder every year. “Whiplash disorders are a leading cause of disability worldwide, costing the Australian economy around a $AUD1 billion a year, and the American economy more than $USD100 billion per annum. “We believe this new technological approach will deliver diagnostic, predictive and clinical benefits.”
revolutionise the diagnosis and treatment of whiplash injuries, one of the most common and challenging injuries following a non- catastrophic motor vehicle collision. The longitudinal study, conducted over more than five years, involved researchers from the Kolling Institute along with scientists from Northwestern University, University of Colorado and Stanford University. As part of the trial, more than 80 people underwent MRI scans of their neck two weeks after their crash and then again at 12 months. The scans measured muscle composition, a key indicator of whiplash injury and other disorders of the cervical spine. The Kolling’s Acting Executive Director and NSLHD Professor of Allied Health Jim Elliott said the project took advantage of improvements in high resolution MRI and rapid acquisition and measurement techniques. “We innovatively applied artificial intelligence, dramatically reducing the processing times of measuring muscle composition from hours to seconds,” he said.
“We found changes in muscle composition
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