3D facial imaging could lead to earlier detection of autism in children

In order for treatments for autism in children to be the most effective, early detection is important. Researchers at the University of Missouri-Columbia are using 3D imaging and statistical analysis to look at facial measurements in autistic children, which could eventually give more insight on genetic causes. “We want to detect the specific facial traits […]

In order for treatments for autism in children to be the most effective, early detection is important. Researchers at the University of Missouri-Columbia are using 3D imaging and statistical analysis to look at facial measurements in autistic children, which could eventually give more insight on genetic causes.

“We want to detect the specific facial traits of the face of a child with autism,” said Ye Duan, associate professor of computer science in the College of Engineering at MU. “Doing so might help us define the facial structures common to children with autism and potentially enable early screening for the disorder.”

Duan worked with Judith Miles, professor emerita of child health-genetics in the MU Thompson Center for Autism and Neurodevelopmental Disorders at MU, for the study and generated 3D images of children’s faces with a system of cameras.

Previously, two-dimensional facial images have been analyzed, but this new technique allows the researchers to examine curvature. Two groups of children between the ages of 8 and 12 were involved in the study (one group of kids were diagnosed from the Thompson Center, and the other was made up of kids who were not diagnosed as autistic).

“It all started from a clinical observation,” Miles said. “Over years of treating children, I noticed that a portion of those diagnosed with autism tend to look alike with similar facial characteristics. I thought perhaps there was something more than coincidence at play. The differences were not abnormal, rather they appeared analogous to similarities observed among siblings. Using three-dimensional images and statistical analysis, we created a ‘fine-tuned map’ of children’s faces and compared those measurements to the various symptoms they exhibit. By clustering the groups based on their facial measurements and recording their autism symptoms, we wanted to determine whether subgroups based on facial structure correlate with autism symptoms and severity.”

The researchers did in fact find correlations within different subgroups, which included children with similar facial structure measurements as well as similarities in the type and severity of autism.

Miles believes that with other groups doing the same kind of research and with DNA analysis of these subgroups, they could find genes associated with the types of autism, which could lead to more affective treatment in the future.

[Photo from Flickr user Bellamy]