Researchers have identified specific neurological biomarkers for ADHD in the brain, their study revealing that children with this disorder had abnormal connectivity in areas associated with memory processing and auditory processing, as well as thinning of the cortex.
The team, which analysed data from MRI exams on nearly 8 000 children, said these biomarkers revealed a possible role for neuroimaging machine learning to help with the diagnosis, treatment planning and surveillance of ADHD.
The results of the study were presented this week (27-30 November) at the annual meeting of the Radiological Society of North America (RSNA).
According to the US Centres for Disease Control and Prevention, ADHD is one of the most common neurodevelopmental disorders in childhood, affecting some 6m American children aged between three and 17.
Children with the disorder may have trouble paying attention and controlling impulsive behaviour, or they may be overly active. Diagnosis relies on a checklist completed by the child’s caregiver to rate the presence of ADHD symptoms.
“There’s a need for a more objective methodology for a more efficient and reliable diagnosis,” said study co-author Huang Lin, a post-graduate researcher at the Yale School of Medicine in New Haven, Connecticut.
“ADHD symptoms are often undiagnosed or misdiagnosed because the evaluation is subjective.”
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 from 21 centres across the country to represent the sociodemographic diversity in the US.
“The demographics of our group mirror the population, making our results clinically applicable to the general population,” Lin said.
Neuroscience reports that after exclusions, Lin’s study group included 7 805 patients, including 1 798 diagnosed with ADHD, all of whom underwent structural MRI scans, diffusion tensor imaging and resting-state functional MRI.
The researchers performed a statistical analysis of the imaging data to determine the association of ADHD with neuroimaging metrics including brain volume, surface area, white matter integrity and functional connectivity.
“We found changes in almost all of the regions of the brain we investigated,” Lin said. “The pervasiveness throughout the whole brain was surprising since many prior studies have identified changes in selective regions.”
In the patients with ADHD, the researchers observed abnormal connectivity in the networks involved in memory processing and auditory processing, a thinning of the brain cortex, and significant white matter microstructural changes, especially in the frontal lobe of the brain.
“The frontal lobe is the area of the brain involved in governing impulsivity and attention or lack thereof – two of the leading symptoms of ADHD,” Lin said.
She said 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 analyse large amounts of MRI data.
“Our study underscores that ADHD is a neurological disorder with neuro-structural and functional manifestations in the brain, not just a purely externalised behaviour syndrome,” she said.
Lin said the population-level data from the study offer reassurance that the MRI biomarkers give a solid picture of the brain.
“At times when a clinical diagnosis is in doubt, objective brain MRI scans can help to clearly identify affected children,” Lin said. “Objective MRI biomarkers can be used for decision making in ADHD diagnosis, treatment planning and treatment monitoring.”
Senior author Dr Sam Payabvash, a neuroradiologist and assistant professor of radiology at the Yale School of Medicine, with co-authors Stefan Haider, Clara Weber and Simone Kaltenhauser, noted that recent trials have reported microstructural changes in response to therapy among ADHD children.
“Our study provides novel and multimodal neuroimaging biomarkers as potential therapeutic targets in these children,” Payabvash said.
Neuroscience News article – Brain Markers of ADHD in Children Identified (Open access)
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