Concussion is the most common form of traumatic brain injury. While serious concussions present with overt symptoms, the diagnosis of mild concussions remains a clinical difficulty. Researchers recently developed two novel methods for the diagnosis of concussion that may aid in the identification of less severe traumatic brain injuries.
A concussion is a relatively common traumatic brain injury caused by a fall or blow to the head that results in a temporary impairment of brain function. Loss of consciousness is common, but contrary to popular belief, it is not a requirement for diagnosis. Typical indicators include drowsiness, dizziness, confusion, headache, and memory impairment, among other neurological symptoms. These symptoms usually persist for a few months, but some patients continue to experience cognitive and behavioral manifestations long after the initial injury.
The detection of concussion using objective, quantitative methods remains a clinical challenge. Traditional brain imaging techniques, such as computed tomography and magnetic resonance imaging, are not sensitive enough for this application. Therefore, diagnosis is usually made using non-objective methods such as patient interviews and self-assessments.
A group of researchers led by Margot Taylor at Simon Fraser University have developed a new method for detecting mild traumatic brain injuries using magnetoencephalographic (MEG) imaging. The results were published in the journal PLOS Computational Biology. Taylor and colleagues are members of the Behavioral and Cognitive Neuroscience Institute and the ImageTech Lab at SFU, home to the only research-dedicated MEG scanners in western Canada.
MEG imaging is a technique that measures the magnetic fields generated by brain activity. It has excellent spatial and temporal resolution and can identify events with millimeter and millisecond precision. MEG imaging can be used to map the interaction among various brain areas. Importantly for clinical applications, MEG imaging is completely noninvasive, and can be used in both adults and children without harmful radiation exposure, or the need to inject isotopes.
Mild traumatic brain injury is associated with damage to the white matter of the brain, made up of bundles of nerve axons that connect one brain area to another. When two brain areas are connected, they show activity pattern synchronization, referred to as oscillatory network synchrony. The researchers hypothesized that by using MEG imaging to measure network synchrony, they could identify small disruptions in the connections between brain areas that result from traumatic brain injuries.
MEG scans were performed on patients who were diagnosed with a mild traumatic brain injury (concussion) in the prior three months, and on healthy controls. Computer analyses were performed to calculate several indices of network connectivity, and significant differences were found between patients and controls. The differences were stronger when less time had elapsed between the injury and the imaging procedure. Overall, MEG imaging was able to detect the presence of a mild concussion with 88% accuracy.
In another 10.1038/srep39009″>groundbreaking study, a group of researchers led by Nina Kraus and Cynthia LaBella of the Auditory Neuroscience Laboratory at Northwestern University have developed an approach for diagnosing concussion using an auditory biomarker. Their work was recently published in the journal Scientific Reports.
The processing of sound by the brain is a complex process that involves interaction among the cognitive, sensory, and limbic systems. Damage to any of these brain systems should therefore interrupt auditory processing, the researchers proposed. The question Kraus and colleagues asked was whether concussion-induced changes in sound processing would be large enough to distinguish between patients with a concussion and controls.
To test this question, the researchers measured speech-evoked frequency-following responses (FFRs) in 40 children with and without a concussion. The FFR is generated by the auditory center of the brain, and it incorporates cognitive, sensory, and reward input. Changes in the FFR have previously been associated with other clinical syndromes. Importantly, the FFR can be easily measured by placing electrodes on the scalp and delivering a sound stimulus into the ear. The FFR measurement is highly reliable and is consistent across the lifespan within an individual.
The children who had sustained concussion were tested an average of 27 days after their injury. Neurophysiological responses were measured in terms of the magnitude, timing, accuracy, and pitch processing of the fundamental frequency of speech (F0). Children with concussion exhibited on average a 35% smaller response to the F0 than the controls. They also showed impaired pitch coding, and smaller and slower brain responses to speech. These measures were correlated with the number of concussion symptoms reported by the patients.
The researchers created a statistical model incorporating these data. Their model was able to classify subjects into concussion or control groups with 90% sensitivity and 95% specificity, suggesting that the observed changes in auditory processing are an accurate biomarker of concussion.
The researchers cite the portability, reliability, and accuracy of their test as major advantages for its clinical application in diagnosing new injuries. Baseline readings could be made in athletes who participate in impact sports, and repeat measures could be taken at the end of the season or following an injury.
Together with MEG imaging, this method provides an objective and quantitative means for diagnosing brain dysfunction after mild traumatic brain injury. These methods will be useful both for identifying patients with mild injuries, and for developing guidelines for recovery and the return to work and play following an injury.
Dimou S. and Lagopoulos J. (2014). Toward objective markers of concussion in sport: a review of white matter and neurometabolic changes in the brain after sports-related concussion. J Neurotrauma. 1;31(5):413-24. DOI: 10.1089/neu.2013.3050
Vakorin V.A., Doesburg S.M., Da Costa L., Jetly R., Pang E.W., Taylor M.J. (2016) Detecting Mild Traumatic Brain Injury Using Resting State Magnetoencephalographic Connectivity. PLOS Computational Biology 12(12):e1004914. DOI: 10.1371/journal.pcbi.1004914
Nina Kraus N., Thompson E.C., Krizman J., Cook K., White-Schwoch T., LaBella, C.R. (2016) Auditory biological marker of concussion in children. Sci Rep. 6:39009. DOI: 10.1038/srep39009
Kraus, N. and White-Schwoch, T. (2015) Unraveling the biology of auditory learning: A cognitive-sensorimotor-reward framework. Trends Cogn Sci. 19:642–654. DOI: dx.doi.org/10.1016/j.tics.2015.08.017
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