Ashley Kies, PhD LPA NCSP is one of the autism expert psychologists at the Child and Family Development- Midtown office. Recently, she reviewed an article in Nature magazine: International weekly journal of science titled “Brain Scans Detect Early Signs of Autism in Babies”.
The study was led by researchers Joseph Piven and Heather Cody Hazlett at University of North Carolina and scanned the brains of 106 “high-risk” infants at age 6, 12, and 24 months using magnetic resonance imaging (MRI). They also followed 42 low-risk infants. Results revealed that 15 of the high-risk infants were diagnosed with autism at 24 months. MRI scans revealed that the volume of these infants’ brains grew faster between 12 and 24 months, compared with children who were not diagnosed with ASD, and that this accelerated growth occurred at the same time that behavioral signs of autism appeared. The researchers also found brain changes between 6 and 12 months, before ASD symptoms appeared. The cortical surface area — a measure of the size of folds on the outside of the brain — grew faster in infants later diagnosed with autism, compared with those who did not receive a diagnosis.
Hazlett and Piven’s team then used a deep-learning neural network, a form of machine learning, to ask if MRI scans at 6 and 12 months in a larger set of high-risk infants could predict an autism diagnosis at age 2. The algorithm correctly predicted 30 out of the 37 autism diagnoses (81 percent), while producing false-positives in 4 out of the 142 infants who were not later diagnosed. “We now have this finding in these high familial risk infants that we can predict 8 out of 10 that we think will get autism,” says Piven, adding that behavior-based predictions do no better than 50–50 at that age. “This has tremendous clinical implications.”
Read the full article here.
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