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RSNA23: AI-Powered Brain Scans May Aid in ADHD Diagnosis, Research Reveals

by Fred Pennic 12/01/2023 Leave a Comment

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What You Should Know:

– Using artificial intelligence (AI) to analyze specialized brain MRI scans of adolescents with and without attention-deficit/hyperactivity disorder (ADHD), researchers found significant differences in nine brain white matter tracts in individuals with ADHD. The results of the study will be presented today at the annual meeting of the Radiological Society of North America (RSNA).

ADHD: A Common and Challenging Disorder

ADHD is a common neurodevelopmental disorder that affects millions of children and adolescents worldwide. Symptoms of ADHD include difficulty paying attention, controlling impulsive behaviors, and regulating activity levels. Early diagnosis and intervention are crucial for managing ADHD and improving outcomes.

Currently, ADHD diagnosis relies on subjective self-reported surveys and clinical assessments, which can be imprecise and may lead to misdiagnosis. The researchers sought to develop an objective and more reliable method for ADHD diagnosis.

AI-Powered Brain Scan Analysis

The researchers utilized deep learning, a type of AI, to analyze diffusion-weighted imaging (DWI) MRI scans of over 1,700 adolescents from the Adolescent Brain Cognitive Development (ABCD) Study. DWI MRI measures the movement of water molecules along white matter tracts in the brain.  Latest research on ADHD has highlighted the need for more objective diagnostic methods, making AI-powered brain scan analysis a promising approach.

Identifying Brain Differences in ADHD

The AI model identified significant differences in FA values, a measure of white matter integrity, between adolescents with and without ADHD. Specifically, nine white matter tracts showed elevated FA values in individuals with ADHD.

The researchers believe that these findings could pave the way for more accurate and objective ADHD diagnosis using brain imaging. This could potentially improve diagnostic accuracy, reduce misdiagnosis, and facilitate early intervention for individuals with ADHD.

“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.”

“Many people feel that they have ADHD, but it is undiagnosed due to the subjective nature of the available diagnostic tests,” Huynh said. “This method provides a promising step towards finding imaging biomarkers that can be used to diagnose ADHD in a quantitative, objective diagnostic framework,” Huynh said.

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Tagged With: Artificial Intelligence

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