Detecting concussion is typically not possible with current clinically used brain imaging, such as MRI and CT scans. However, research coming out of Canada suggests that magnetoencephalographic (MEG) imaging is able to measure brain activity mapping how various areas of the brain interact which can then be analysed to diagnose a concussion.
A pilot study led by Vasily Vakorin from Simon Fraser University found that magnetoencephalographic imaging can map how different areas of the brain interact, and by using machine learning tools, researchers were able to compare images from individuals who had suffered a concussion, as well as control subjects who had not. Using the imaging data, the researchers were able to detect concussion with 88% accuracy.
Details of the research is available at Computational Biology.
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