Could an Emerging AI System Lead to Earlier Autism Detection with DT-MRI?

Excerpt from the Press Release:

While a recent report issued by the Centers for Disease Control and Prevention (CDC) noted that 30 percent of children with autism were not diagnosed at eight years of age, emerging research suggests that a combination of artificial intelligence (AI) and diffusion tensor magnetic resonance imaging (DT-MRI) facilitates autism detection in children between two to four years of age.^1,2

In a study to be presented at the annual Radiological Society of North America (RSNA) conference next week in Chicago, researchers examined the use of a machine learning-based system that assesses connectivity markers extracted from DT-MRI brain scans that allow visualization of how water travels in white matter tracts. The study cohort was comprised of 126 children with autism and 100 normally developing children. All children in the cohort were between two to four years of age, according to the study.²

The researchers found that the machine learning-based system exhibited a 97 percent sensitivity rate, a 98 percent specificity rate and a 98.5 percent accuracy rate in diagnosing autism spectrum disorder (ASD).²

Noting that the machine learning system provides a detailed report including affected neural pathways, potential impact on brain functionality and grades for autism severity, the study authors suggested the modality could play a significant role in the diagnostic workup of patients with ASD.

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