Scientist's Simple Test Detects Brain Ills

(August 22, 2007) -- A University of Minnesota scientist says he has discovered a way to detect Alzheimer's disease, schizophrenia and other brain disorders by using a device that tracks magnetic signals in the brain.

Professor Apostolos Georgopoulos calls it an "elegantly simple test" that has been surprisingly accurate so far in assessing nearly 300 patients and healthy volunteers.

Although the research is still in its early stages, it could lead to a relatively quick and painless test for a wide range of conditions that affect the brain, experts say.

Georgopoulos and his research team used a technology known as MEG (magnetoencephalography) at the VA Medical Center in Minneapolis to study people's brains as they stared at a point of light for 45 to 60 seconds.

In a study published online Wednesday by the British Journal of Neural Engineering, they found they were able to identify six types of disorders "with 100 percent accuracy" - Alzheimer's, chronic alcoholism, schizophrenia, multiple sclerosis, Sjogren's syndrome (an autoimmune disease) and facial pain.

What they found, Georgopoulos said, is that each disease affects the brain differently and alters the way brain cells communicate with one another.

There are no such tests for most brain diseases, which can be difficult to diagnose. They're usually identified over time by observing behavior, such as memory loss in Alzheimer's patients, and other external symptoms.

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Georgopoulos, who is internationally known for his work on how the brain affects movement, said even he was surprised by the apparent accuracy of the test. But the results have continued to hold up, he said, even after they concluded the initial study, which involved 142 patients.

"We're approaching our 300th subject," he said, "and it looks better and better."

If it pans out, the new test could be used to diagnose brain disorders earlier, monitor their progress and track the effectiveness of new treatments.

By: Maura Lerner
Source: Denverpost.com

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