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.
http://www.medscape.com/viewarticle/862070
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