They found that the Shannon entropy analysis of FA histograms was a better at differentiating between concussion and control patients compared to mean FA. It also was more effective at differentiating between those with and without post-traumatic migraine.

The concussion patients had much lower Shannon entropy than the control patients and the patients with post-traumatic migraines had significantly lower Shannon entropy than other concussion patients. They also found that the patients with lower entropy look a longer amount of time to recover.


If this approach continues to show promise, it may have the potential to change how concussion patients are assessed with imaging. Alhilali believes that Shannon entropy can succeed where conventional measures of FA have failed — accurately characterizing the multidimensional white matter changes in concussion injuries.

"Shannon entropy can completely change the way neuroimaging approaches the evaluation of concussion because it can be performed simply, in an automated fashion without additional labor, is easily implemented as part of all MRI vendor platforms, is quantitative, and has the potential to identify white matter injuries that may go undetected by conventional analysis methods," said Alhilali.

But more research is required to determine if there are other potential applications for Shannon entropy including predicting future cognitive performance in concussion patients.

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