Johns Hopkins 'digital twin' technology predicts head trauma in athletes

While football, food and commercials will be on the minds of many this coming Sunday for the Super Bowl, biomechanics experts watching the game will be preoccupied with something a little different: head injuries.  

Biomechanical engineers from Johns Hopkins University and the National Institutes of Health are developing a tool to better predict where brain damage from concussions is likely to occur in athletes and ultimately better diagnose concussions, according to a recent press release. 

"You can get a concussion even without being hit in the head," said Kaliat T. Ramesh, PhD, a biomechanics expert Johns Hopkins Whiting School of Engineering, in a statement. "All you need to do is move the head fast enough; the impact is what most people think about, but the rotation may actually be more important in terms of concussion. So, the bigger danger may be when your head gets turned too fast." 

Essentially, Ramesh and colleagues are using MRI technology to create a "digital twin" model created for high school athletes that uses axonal damage to predict head trauma. The hope is for the "digital twin" head of an athlete to calculate brain injuries over an entire career.  

"If we already have a history of scans when an athlete gets a head injury, we can say that, based on the kind of person you are and the kind of event that occurred, it's likely to be this kind of injury, and therefore medical professionals should perhaps use this kind of diagnostic procedure to look at it," Ramesh said.