According to the Centers for Disease Control and Prevention, attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders in childhood.
It affects approximately 6 million American children between the ages of 3 and 17 years.
In a study from Yale University, scientists found new brain markers of ADHD in children.
They analyzed the data from MRI exams on nearly 8,000 children and identified biomarkers of ADHD and a possible role for neuroimaging machine learning to help with the diagnosis, treatment planning, and surveillance of the disorder.
Children with the disorder may have trouble paying attention and controlling impulsive behaviors, or they may be overly active.
Diagnosis relies on a checklist completed by the child’s caregiver to rate the presence of ADHD symptoms.
In the study, the researchers used MRI data from the Adolescent Brain Cognitive Development (ABCD) study, the largest long-term study of brain development and child health in the United States.
The ABCD study involves 11,878 children aged 9-10 years from 21 centers across the country to represent sociodemographic diversity in the U.S.
The research included 7,805 patients, including 1,798 diagnosed with ADHD, all of whom underwent structural MRI scans, diffusion tensor imaging, and resting-state functional MRIs.
In the patients with ADHD, the researchers observed abnormal connectivity in the brain networks involved in memory processing and auditory processing, a thinning of the brain cortex, and strong white matter microstructural changes, especially in the frontal lobe of the brain.
The team says the MRI data was significant enough that it could be used as input for machine learning models to predict an ADHD diagnosis.
Machine learning, a type of artificial intelligence, makes it possible to analyze large amounts of MRI data.
The study underscores that ADHD is a neurological disorder with neuro-structural and functional manifestations in the brain, not just a purely externalized behavior syndrome.
The population-level data from the study offers reassurance that the MRI biomarkers give a solid picture of the brain.
If you care about child development, please read studies that strange eating habits may signal autism, and cats may help decrease anxiety for kids with autism.
For more information about health, please see recent studies about a new cause of autism, and results showing COVID-19 infection may increase the risk of type 1 diabetes in children.
The study was conducted by Huang Lin et al and presented at the annual meeting of the Radiological Society of North America (RSNA).
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