Brain imaging for infants may help detect development of autism

New research from JAMA indicates that an MRI can detect signs of autism developing in infants during a "presymptomatic period.”

Published online Oct. 3, the study, conducted by Tracy Hampton, PhD, suggests early brain scans in infants earlier than 24 months could predict signs of autism spectrum disorder (ASD).

"The findings point to a noninvasive method to detect autism at its earliest stages, when interventions may provide the most benefits," said Hampton. "Because the defining features of ASD tend to emerge over the latter part of the first year and into the second year, a diagnosis is not typically made until 24 months of age and beyond."

Hampton examined two prospective neuroimaging studies published earlier this year in Nature and Science Translational Medicine to support her claim. Both studies utilized algorithms using longitudinal MRI data from infants who expressed a high risk of developing ASD to predict accurate autism diagnosis.

The first study, published on Feb. 15 in Nature, is by Joseph Piven, MD, the director of the Carolina Institute for Developmental Disabilities (CIDD) at the University of North Carolina Chapel Hill School of Medicine. Piven conducted brain scans of 106 infants at high-risk for getting ASD and 42 low-risk infants.

Findings taken directly from this study include:

• Hyperexpansion of the cortical surface area between six and 12 months of age precedes brain volume overgrowth observed between 12 and 24 months in 15 high-risk infants.
• Brain volume overgrowth was linked to the emergence and severity of autistic social deficits.
• A deep-learning algorithm that uses surface area information from MRI of the brains of six 12-moth-old infants predicted autism in individual high-risk children at 24 months (with a positive predictive value of 81 percent and a sensitivity of 88 percent).

The second study is by Piven and a myriad of his colleagues, published in Science Translational Medicine on June 7.

“Using prospective neuroimaging of 56 six month old infants with a high familial risk for ASD, we show that functional connectivity MRI correctly identified which individual children would receive a research clinical best-estimate diagnosis of ASD at 24 months of age," lead author of the study Piven said.

Piven and his colleagues’ conclusions from this study included the following:

• Functional brain connections were defined in 6-month-old infants that correlated with 24 month scores on measures of social behavior, language, motor development and repetitive behavior, which are all features common to the diagnosis of ASD.
• A fully cross-validated machine learning algorithm applied at age six months had a positive predictive value of 100 percent [95 percent confidence interval (CI), 62.9 to 100], correctly predicting nine of 11 infants who received a diagnosis of ASD at 24 months (sensitivity, 81.88 percent; 95 percent CI, 47.8 to 96.8).
• All 48 6-month-old infants who were not diagnosed with ASD were correctly classified [specificity, 100 percent (95 percent CI, 90.8 to 100); negative predictive value, 96.0 percent (95 percent CI, 85.1 to 99.3)].

Overall, Hampton claims in the JAMA article that the imaging data suggest that increased cerebral growth in infants between the ages of six and 12 months may predict autism diagnoses when the children are 24 months old.