When physicians want to know more about a patient’s risk of cardiovascular disease, they can order a cardiac stress test. But when it comes to risk of stroke, there is no equivalent scalable and cost-effective test of the brain’s function to help physicians counsel patients on their potential risk. A questionnaire that asks patients about contributing risk factors is currently the best tool for estimating such risk.

Now a team of engineers and scientists from Caltech and the Keck School of Medicine of USC has developed a headset-based device that can be used to noninvasively assess a patient’s stroke risk by monitoring changes in blood flow and volume while a participant holds their breath. The device incorporates a laser-based system and has shown promising results in terms of differentiating between individuals at low and high risk of stroke.

Stroke affects nearly 800,000 Americans each year and is the leading cause of serious, long-term disability in the United States. It is caused by the blockage or rupture of an artery in the brain, which results in a reduction in blood flow. Starved of oxygen, the brain’s cells die rapidly—about 2 million every minute during a stroke.

“With this device, for the first time, we are going to have a way of knowing if the risk of someone having a stroke in the future is significant or not based on a physiological measurement,” says Simon Mahler, a co-lead author of a paper describing the new technique and device, and a postdoctoral scholar in the lab of Changhuei Yang, the Thomas G. Myers Professor of Electrical Engineering, Bioengineering, and Medical Engineering at Caltech and a Heritage Medical Research Institute Investigator.

“We think this can really revolutionize the way stroke risk is assessed and will eventually help doctors determine if a patient’s risk is stable or worsening.”

“Our optical technology to noninvasively measure blood flow is expected to be useful for a number of brain disease applications,” says Yang, who is also the executive officer for electrical engineering at Caltech. He noted that this project is part of a larger collaboration effort with Dr. Charles Liu, professor of clinical neurological surgery, surgery, psychiatry and the behavioral sciences and biomedical engineering at the Keck School of Medicine of USC, and his team.

The paper, titled “Correlating stroke risk with non-invasive cerebrovascular perfusion dynamics using a portable speckle contrast optical spectroscopy laser device,” appears in Biomedical Optics Express.

Speckle contrast optical spectroscopy for stroke-risk assessment

In general, blood vessels become stiffer as a person ages, meaning they have a harder time dilating to allow blood through. This, in turn, means the person is more prone to stroke.

The Caltech team developed a compact device that shines infrared laser light through the skull and into the brain in one location and then uses a special camera nearby to collect the light that bounces back after it is scattered by blood flowing within the blood vessels.

The approach, called speckle contrast optical spectroscopy (SCOS), measures the decrease in the light’s intensity from the spot where it enters the skull to the place where the bounced-back light is collected to determine the volume of blood in the brain’s blood vessels; it also looks at the way light scatters and creates speckles in the camera’s field of view.

The speckles fluctuate in images depending on the rate of blood flow in the blood vessels. The faster the blood is flowing, the more rapidly the speckle field changes.

The researchers can use those measurements to calculate a ratio of the flow over the volume of blood streaming through the vessel to get an idea of that patient’s stroke risk.

The team conducted a study of 50 participants. They used the currently used stroke risk questionnaire, the Cleveland Stroke Risk Calculator, to divide the participants into two groups: one low risk and one high risk. They then measured blood flow in each volunteer for three minutes, quantifying the flow rate and volume of blood reaching the brain. After one minute, they asked the participants to hold their breath.

Holding your breath stresses your brain as it begins to notice that it is taking in too much carbon dioxide and not enough oxygen. It goes into what Mahler refers to as “panic mode,” and starts to pump oxygen from the rest of the body to itself. This greatly increases blood flow in the brain.

Once you stop holding your breath, oxygen levels return to baseline. While this happens in both people at low and high risk of stroke, the researchers found that there were differences between the groups in terms of how the blood moved through the vessels.

The SCOS technique allows the researchers to measure how much the blood vessels expand while the subject holds their breath and how much faster blood flows through the vessels in response. “These reactive measurements are indicative of vessel stiffness,” Yang says. “Our technology makes it possible to make these type of measurements noninvasively for the first time.”

“What we found is clear, striking evidence of a different reaction of blood flow and blood volume between the two groups,” says Yu Xi Huang, a co-lead author of the new paper and a graduate student in Yang’s lab.

In the low-stroke-risk group, the researchers observed a smaller increase in blood flow during the breath-holding exercise compared to the high-stroke-risk group, but a greater increase in blood volume—an indication that more blood is able to flow through the widened blood vessels.

“We can clearly see that the higher risk group has a higher flow-to-volume ratio, where they have faster flow but a lower volume of blood during breath holding,” Mahler says. This is caused by the stiffness of the blood vessels and indicates a higher chance of rupture. “If someone came in with an extremely high flow-to-volume ratio value, we might suspect that this person will have a stroke in the near future.”

A promising future

The team is conducting additional research using the current prototype of the imaging device on patients at a hospital in Visalia, California, to gather additional data from a larger, more diverse population. The researchers also plan to incorporate machine learning into the device’s data collection process and to conduct a clinical trial that would involve patient tracking over more than two years to enhance the technology.

They hope the device might eventually be used broadly not only for stroke risk prescreening but also to help detect where exactly in the brain a stroke might have already occurred.