The AI method shows promise in identifying imaging biomarkers for diagnosing ADHD.
By employing artificial intelligence (AI) for the analysis of specialized brain MRI scans in adolescents, researchers identified notable distinctions in nine brain white matter pathways between individuals with and without //attention-deficit/hyperactivity disorder (ADHD). Results of the study will be presented today at the annual meeting of the Radiological Society of North America (RSNA). (1✔ ✔Trusted Source
AI May Aid in Diagnosing Adolescents with ADHD
Go to source) ADHD is a common disorder often diagnosed in childhood and continuing into adulthood, according to the Centers for Disease Control and Prevention. In the U.S., an estimated 5.7 million children and adolescents between the ages of 6 and 17 have been diagnosed with ADHD.
‘The AI approach represents a promising advancement in identifying imaging biomarkers that could serve in diagnosing attention-deficit/hyperactivity disorder. #adhd #AI #ML #artificialintelligence ’
“ADHD often manifests at an early age and can have a massive impact on someone’s quality of life and ability to function in society,” said study co-author Justin Huynh, M.S., a research specialist in the Department of Neuroradiology at the University of California, San Francisco, and medical student at the Carle Illinois College of Medicine at Urbana-Champaign. “It is also becoming increasingly prevalent in society among today’s youth, with the influx of smartphones and other distracting devices readily accessible.” Children with ADHD may have trouble paying attention, controlling impulsive behaviors or regulating activity. Early diagnosis and intervention are key to managing the condition.
“ADHD is extremely difficult to diagnose and relies on subjective self-reported surveys,” Huynh said. “There is definitely an unmet need for more objective metrics for diagnosis. That’s the gap we are trying to fill.”
Use of Deep Learning in Identifying ADHD Markers
Huynh said this is the first study to apply deep learning, a type of AI, to identify markers of ADHD in the multi-institutional Adolescent Brain Cognitive Development (ABCD) Study, which includes brain imaging, clinical surveys and other data on over 11,000 adolescents from 21 research sites in the U.S. The brain imaging data included a specialized type of MRI called diffusion-weighted imaging (DWI).“Prior research studies using AI to detect ADHD have not been successful due to a small sample size and the complexity of the disorder,” Huynh said.
The research team selected a group of 1,704 individuals from the ABCD dataset, including adolescents with and without ADHD. Using DWI scans, the researchers extracted fractional anisotropy (FA) measurements along 30 major white matter tracts in the brain. FA is a measure of how water molecules move along the fibers of white matter tracts.
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With the help of AI, the researchers discovered that in patients with ADHD, FA values were significantly elevated in nine white matter tracts.
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The researchers intend to continue obtaining data from the rest of the individuals in the ABCD dataset, comparing the performance of additional AI models.
“Many people feel that they have ADHD, but it is undiagnosed due to the subjective nature of the available diagnostic tests,” Huynh said.
Reference:
- AI May Aid in Diagnosing Adolescents with ADHD - (https://press.rsna.org/timssnet/media/pressreleases/14_pr_target.cfm?id=2470)