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Snapshot Science: Can Brain Imaging at Birth Predict Developmental Disorders?
shafere1 [at] chop.edu (By Emily Shafer)
Researchers at Children’s Hospital of Philadelphia found that whole-brain cortical microstructure at birth, quantified by diffusion magnetic resonance imaging (MRI), may predict cognitive and language functions assessed at age 2. The cortical microstructure is the foundation for the formation and function of neurons as the brain matures, playing a significant role in children’s behavioral development.
Why it matters:
Diagnosis for neuropsychiatric disorders, such as autism spectrum disorder (ASD), can only be reliably made around age 2 or later; behavioral problems can be difficult to recognize prior to this time. Because early intervention, even before age 2, can potentially improve outcomes in children with ASD and other developmental disorders, researchers want to identify effective methods for diagnosis before this age.
Who conducted the study:
Hao Huang, PhD, research scientist in the Department of Radiology at CHOP, and research associate professor of Radiology at Perelman School of Medicine at University of Pennsylvania, was the senior author. Other CHOP authors include Minhui Ouyang, PhD; Qinmu Peng, PhD; and Tina Jeon, PhD. Researchers from the University of Texas Southwestern Medical Center also contributed to the study.
How they did it:
The study included 87 infants who underwent MRI after birth, specifically for study purposes. Among those infants, 46 completed follow-up neurodevelopmental assessment at age 2. The researchers used the Bayley-III test to measure cognitive, language, and motor development. Next, they performed a pattern analysis using a machine learning prediction model. The study team determined that neonate cortical microstructure robustly predicted individual cognitive and language functions assessed at age 2.
“If kids have autism or other developmental disorders, you want to know as early as possible, so that you can hopefully have early intervention to change the progression of the disorder,” Dr. Huang said. “We can use this artificial intelligence model to determine if there is any risk of autism or other disorders in infants as they get older, and the model can even tell us the severity of the disorder. With this information, professionals can begin appropriate intervention, and not waste a precious two-to-three-year window to help these children.”
Where the study was published:
The study appeared in eLife.