Eye-tracking tool may help diagnose autism more quickly and accurately, new studies suggest

Originally Published: 05 SEP 23 11:09 ET

Updated: 05 SEP 23 11:36 ET

By Jacqueline Howard and Deidre McPhillips, CNN

(CNN) — Most families of children with autism may face long wait times to diagnose their child with the disorder, and once a diagnosis is made, it sometimes may not be definitive.

But now, two studies released Tuesday suggest that a recently developed eye-tracking tool could help clinicians diagnose children as young as 16 months with autism – and with more certainty.

“This is not a tool to replace expert clinicians,” said Warren Jones, director of research at the Marcus Autism Center at Children’s Healthcare of Atlanta and Nien Distinguished Chair in Autism at Emory University School of Medicine, who was an author on both studies.

Rather, he said, the hope with this eye-tracking technology is that “by providing objective measurements that objectively measure the same thing in each child,” it can help inform the diagnostic process.

The tool, called EarliPoint Evaluation, is cleared by the US Food and Drug Administration to help clinicians diagnose and assess autism, according to the researchers.

Traditionally, children are diagnosed with autism based on a clinician’s assessment of their developmental history, behaviors and parents’ reports. Evaluations can take hours, and some subtle behaviors associated with autism may be missed, especially among younger children.

“Typically, the way we diagnose autism is by rating our impressions,” said Whitney Guthrie, a clinical psychologist and scientist at the Children’s Hospital of Philadelphia’s Center for Autism Research. She was not involved in the new studies, but her research focuses on early diagnosis of autism.

It will always be important to take into account what the family and specialist observe in the child, but families may reflect on a child’s behaviors differently based on their unique backgrounds or experiences, Guthrie said.

“Some of these new technologies are more objective. They don’t rely on humans who are imperfect by nature,” she said. “They’re also potentially more scalable and feasible.”

How tracking eyes may help

The technology works by tracking the eye movements of children as they watch videos of other children’s social interactions.

A child without autism may focus their attention on the hand gestures of one child in the video who’s pointing toward something for another child in the video to look at. That child also may look at the face of another child who looks sad or smiling. But a child with autism would not pay attention to the hand gestures or facial expressions at all, and this can be identified in their eye movements.

“We use scenes like that to test whether or not children are paying attention to the information that we expect typically developing children of that same age to,” Jones said.

In one of the new studies, published in the medical journal JAMA, 475 children ages 16 to 30 months were assessed for autism at six specialty clinics in the United States. The children were enrolled in the study between April 2018 and May 2019, and the eye-tracking tool was included in the assessments.

The researchers found that, relative to expert clinical diagnosis alone, measurements of the children’s eye-tracking and social engagements with the videos had a 71% sensitivity, meaning they helped accurately diagnosis autism 71% of the time, and 80.7% specificity, meaning they helped designate a child without autism about 80% of the time.

Among the children, 335 had an autism diagnosis that their clinicians were “certain” of without using the eye-tracking tool. When the eye-tracking tool was used for just this group, the researchers found that it showed a sensitivity of 78%, and specificity was 85.4% when expert clinicians were certain of their diagnoses.

The findings suggest that using measurements of how children look at and learn from the social interactions in the videos may offer a biomarker for diagnosing autism, helping shorten the time needed to make a diagnosis and accelerate the child’s treatment.

The other study, published in JAMA Network Open, found that among 719 children ages 16 to 30 months, eye-tracking-based measurements had a sensitivity of 81.9% and specificity of 89.9%. In another group of 370 children, ages 16 to 45 months, the eye-tracking measurements had a sensitivity of 80.6% and specificity of 82.3%.

In that study, 14 video scenes were presented to the children, each about 54 seconds long, on average.

Overall, the researchers told CNN, the data shows the technology to have about 80% sensitivity and specificity.

In the studies, the eye-tracking measurements – which collected data at 120 times per second and within 12 minutes of video watching – predicted expert clinician assessments “with a high degree of accuracy,” according to a news release, and were consistent with gold standard expert clinical diagnoses.

“To me, there is no other return of investment for what we do in science and in public health than giving access to families to early diagnosis that will make possible early intervention and support that are going to optimize the outcomes of the children for the rest of their lives,” said Ami Klin, director of the Marcus Autism Center and division chief of autism and developmental disabilities at the Emory University School of Medicine, who was an author of both studies.

“In our health care system, those families are thinking about the concerns that they have about their children – and they go to bed every night for months, if not years, waiting for an answer, knowing very well that the earlier they get to that answer the earlier their child is going to benefit from the kinds of treatments that can improve their lives,” Klin said. “For the first time, we have an objective biomarker-based tool that can increase access. And my greatest hope is that this is going to be one of the tools that we can use to decrease the health care disparities that affect minority, low-income and rural families.”

‘The equity issue … is very significant’

Medical experts have long known that autism evaluation, and subsequent diagnosis, have been “really, really suboptimal” for children of color, as well as those living in rural and underserved communities, including urban areas, said Dr. Kristin Sohl, professor of pediatrics at the University of Missouri School of Medicine and chair of the autism subcommittee for the American Academy of Pediatrics.

Children in those groups disproportionately are diagnosed with autism later than their non-minority or non-rural peers.

“The equity issue in autism is very significant,” Sohl said.

“When you have a little child who is showing characteristics of autism very early but they are not able to even be remotely identified – meaning no one has even thought about it until they’re in kindergarten – that is a huge disadvantage for that individual child,” said Sohl, who was not involved in the new research.

Diagnostic tools like eye-tracking technology and other clinician resources may help reduce those disparities – and improve rates of early diagnosis overall – by enabling specialists to build more capacity into their practices and by helping broaden the pool of doctors who feel equipped to diagnose autism.

“There are many, many children who are very well-served by their community clinicians. And yet we’ve got to help our primary care clinicians have a much better appreciation for autism,” Sohl said. “Diagnostic age is often a reflection of the time that a parent has waited.”

Studies from the US Centers for Disease Control and Prevention have found that early detection of autism in children has improved, but disparities remain in practices to identify and diagnose the condition.

“Devices like this can be so helpful in the hands of a skilled generalist, because they can take that piece of information and use it to look at the other data that they have and then say, ‘Yes, I’m confident that this is autism,’ or ‘No, this isn’t, and here’s what I need to do,’” Sohl said.

But more work is needed before an eye-tracking test becomes commonplace, Geraldine Dawson of the Duke Center for Autism and Brain Development in North Carolina wrote in an editorial published Tuesday alongside the new studies.

“There remains work to be done before an eye-tracking test is used in clinical practice. Demonstrating that an eye-tracking test improves diagnostic certainty would require following children whose diagnosis was uncertain longitudinally to determine whether the test improves prediction of a later definitive autism diagnosis,” she wrote.

“The intended use of the eye-tracking test is to aid clinicians in making an autism diagnosis in young children who have been referred to a specialty clinic for evaluation,” Dawson wrote. “By integrating multiple sources of information— including the eye-tracking test, parent report, and clinical observations—the accuracy, certainty, and efficiency of autism diagnostic assessment could potentially be improved, resulting in fewer missed cases and allowing more children to receive empirically validated early therapies from which they could benefit.”

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