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Brain MRIs Can Identify ADHD and Distinguish Among Subtypes

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Brain magnetic resonance imaging (MRI) can be used to identify people with attention-deficit/hyperactivity disorder from patients without the condition, according to a new study.

Brain magnetic resonance imaging (MRI) can be used to identify people with attention-deficit/hyperactivity disorder (ADHD) from patients without the condition, according to a new study published in Radiology. Information from brain MRIs may also help to distinguish among subtypes of ADHD.

ADHD affects 5% to 8% of children and 4% of adults worldwide, but it is diagnosed through subjective evaluations. The authors sought to identify cerebral radiomics features related to ADHD to improve diagnostic power and treat patients quicker.

“Although the etiology and neurobiological substrate of ADHD remain unclear, converging evidence from imaging studies suggests that individuals with ADHD have alterations in brain volume, cortical morphometric features, and diffusion properties of white matter tracts when compared with typically developing individuals,” the authors explained.

They studied 83 age- and sex-matched children in China who had newly diagnosed and never-treated ADHD and 87 healthy control subjects who underwent anatomic and diffusion-tensor MRI. They found that there was no overall difference between the 2 groups in total brain volume or total gray and white matter volume.

However, researchers found differences when they looked at specific regions within the brain. Alterations in the shape of the left temporal lobe, bilateral cuneus, and areas around the left central sulcus distinguish ADHD from typically developing patients.

Radiomics signatures allowed the researchers to identify patients with ADHD with an average accuracy of 73.7% and to discriminate between ADHD inattentive and ADHD combined subtypes with 80% accuracy.

Among the limitations that the researchers identified was the low prevalence of the hyperactivity impulsive subtype of ADHD in China and their restrictive inclusion criteria, as well as the large age range of children included in the study.

"This imaging-based classification model could be an objective adjunct to facilitate better clinical decision making," study co-author Qiyong Gong, MD, PhD, said in a statement. "Additionally, the present study adds to the developing field of psychoradiology, which seems primed to play a major clinical role in guiding diagnostic and treatment planning decisions in patients with psychiatric disorders."

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