A new test that is not available to the public appears to allow doctors to spot autism more easily with the help of an MRI scan. Researchers at McLean Hospital in Belmont, Mass., have determined that they can use MRI to detect high-functioning autism with 94 percent accuracy.
The research, conducted in partnership with the University of Utah, involved two groups of subjects. The first had already been diagnosed with autism, and the second consisted of health individuals. Both groups underwent an MRI scanner using diffusion tensor imaging, which showed the microscopic structures of the brain that control things like language, and social and emotional development. By examining the brain scans, researchers found distinct differences between those of autistic children versus nonautistic children. The research is published in the November 29 edition of Autism Research.
“Currently, autism is diagnosed based on a structured four-hour interview with parents and a one-hour observation of the child,” lead study author Dr. Nicholas Lange, associate professor of psychiatry at Harvard Medical School and director of the Neurostatistics Laboratory at McLean Hospital, said AOL Health. “It’s a subjective measurement.”
“This test,” he explains, “if it continues to show good performance in further trials, would be an objective test.” That means it could provide biological confirmation of the disease. Lange thinks it could be used conjointly with the current subjective test to help “rule in or rule out” autism. “In 10 to 12 minutes, parents could see the chances that their child has autism.”
Lange says the new test could prevent misdiagnoses as well as offer diagnoses that have been overlooked in the past. “The search is on around the world for such objective biological measures of autism,” he adds. “It’s a long way coming, and it’s not ready for clinical use yet. We want to rule out that these same brain differences could also be present in ADHD or OCD.”
But Lange is nevertheless excited. He sees this new research as not only helping to diagnose autism but in helping to track how it changes the brain over time in individuals who have it. “That’s really what this is all about,” he says. “We can measure individual change over time and then use that for predictive purposes in the future.”
Lange says it’s also important to keep in mind that if this biological testing model plays out in future trials, it’s something that can be done with existing technology. “We don’t need to build a new machine,” he says. “This does not take new technology. It’s available in scanners around the world. We just measured something that people hadn’t looked at before.”