Researchers at the University of California, Davis have developed a new method to measure blood flow in the brain using light. The method could provide a cheaper and more robust way to assess patients with traumatic brain injuries or stroke.
The technique is based on the principle that shining a laser light through someone’s skull results in photon scattering, due to blood flow in the brain. A detector placed on another region of the skull can measure these scattered photons, and these light fluctuations provide information on blood flow. Scientists have been experimenting with this technique, called diffuse correlation spectroscopy, for some time, but it has several drawbacks.
The light signal from the scattered photons is very weak, meaning that a number of very sensitive and expensive photon detectors are required. However, increasing the light signal comes with the risk of burning a patient’s skin.
To address these limitations, the UC Davis researchers have developed a new approach, which they call interferometric diffusing wave spectroscopy. The technique relies on the principle that overlapping light waves can either reinforce or cancel each other out.
The research team split the laser light beam into “sample” and “reference” paths. The “sample” beam enters the patient’s head, whereas the “reference” beam reconnects with the sample beam as it enters the photon detector, helping to reinforce the signal.
“The strong reference light enhances the weaker signal from the sample,” said Wenjun Zhou, a researcher involved in the study. The result is that only one digital camera chip is required to detect the signal, compared with thousands of dollars worth of expensive photon detectors used in conventional diffuse correlation spectroscopy.
In fact, the technique is so robust that the researchers do not even need to turn off the lights in the room in which they assess a patient. To date, they have tested the technology on human volunteers in the laboratory, but plan to adapt it for commercialization and clinical use.
Via: UC Davis