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Predicting the likelihood of migraines in concussion patients

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A mathematical tool could help determine which concussion patients will go on to suffer migraine headaches.

As part of a new study published online in the journal Radiology, researchers assessed the performance of Shannon entropy in analysing MRI results of concussion patients with and without post-traumatic migraines. Shannon entropy is an information theory model that looks at areas of entropy, or disorder, in a complex system like the brain.

“A healthy brain has high entropy, but people with injuries to the white matter from trauma may lose some of that complexity and have less entropy,” explained study author Dr. Lea M. Alhilali from the University of Pittsburgh Medical Center in Pittsburgh.

Results of the study showed that Shannon entropy inversely correlated with time to recovery, meaning that people with lower entropy took longer to recover.

Compared with mean fractional anisotropy, a measure of how easily water moves through the brain, Shannon entropy more accurately revealed concussion and those patients likely to develop post-traumatic migraines.

The findings suggest that Shannon entropy may provide a convenient, reproducible biomarker that can be calculated in automated fashion to help triage patients after initial injury and predict which ones will go on to get more severe symptoms, the Radiological Society of North America (RSNA) said.

“This approach requires just one histogram for the entire brain,” Dr. Alhilali noted. “If it continues to show promise, then it could be added to the regular brain MRI as part of the study.”

Further research will examine other potential applications of Shannon entropy, such as predicting future cognitive performance in concussion patients, Dr. Alhilali added.