A sophisticated transcranial Doppler ultrasound device appears able to help diagnose concussion by analyzing subtle variations in blood flow through the brain, a new study suggests.
"At present, concussion is diagnosed by assessing symptoms, but these can be very variable and difficult to interpret," lead author Robert Hamilton, PhD, cofounder of Neural Analytics, the company developing the device, told Medscape Medical News. "Analyzing blood flow patterns with transcranial Doppler and using a computer algorithm to quantify injury could be the first physiologic measure of concussion."
At this time, the technology is contained in a device about the size of a briefcase, but the company is working on incorporating it into an automated headset that could be used on the sports field or in the military to make a quick assessment of whether the individual is able to continue with his or her activity or not, Dr Hamilton said.
He noted that transcranial Doppler, which measures mean velocity of blood flow, pulsatility index, and cerebrovascular reactivity index, has been around since the 1980s and is used for the diagnosis of severe brain injury, where there is more marked variation in blood flow, but it only has limited diagnostic utility in mild brain injury. "We wanted to look at more subtle variations in blood flow in mild brain injury," he said…
Subsequent work will focus on how flood flow improves as the patent recovers and whether this measurement could be the first physiologic marker of recovery after injury. "Our current results would help clinicians decide if a patient was concussed and we are hoping our future results will show the device could help make the decision as to when the patient can return to normal activities," Dr Hamilton said.
For the current study, the researchers used the transcranial Doppler device and new platform to study cerebral blood flow in 66 high school contact sports athletes within 12 days of head injury, and in 169 age-matched control participants. The initial diagnosis of concussion was made by the treating physician by neurocognitive and symptom evaluation.
Each measurement included bilateral monitoring of the middle cerebral artery, using the transcranial Doppler device, whereas the subject followed a cerebrovascular reactivity protocol (breath-holding). Arterial blood pressure, end-tidal CO2, and concussion evaluations were also collected. Conventional transcranial Doppler metrics were compared with morphological analysis performed by the machine learning platform, using receiver operating characteristic curves.
Results showed that the morphological analysis was much more successful in differentiating between healthy and concussed individuals, with an area under the receiver operating characteristic curve (AUC) of 83% (71% sensitivity and 83% specificity). In contrast, conventional transcranial Doppler was little better than the flip of a coin in discerning those with concussion, with AUC values between 53% and 60% for measures of mean velocity, pulsatility index, and cerebrovascular reactivity index.
Asked to comment on the study for Medscape Medical News, Ramon Diaz-Arrastia, MD, PhD, professor of neurology at the Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Rockville, Maryland, seemed enthusiastic about the new technology.
"It has long been known that the cerebral vasculature is damaged after concussion and more severe forms of traumatic brain injury," he said. "What has been missing are reliable and noninvasive ways to assess cerebrovascular function, and a rigorous assessment of sensitivity, specificity, and validity.
American Academy of Neurology (AAN) 2016 Annual Meeting: Abstract 9151. Presented April 19, 2016.