Hemispheric brain asymmetry differences in youths with attention-deficit/hyperactivity disorder

Abstract

IntroductionAttention-deficit hyperactive disorder (ADHD) is the most common neurodevelopmental disorder in children. Diagnosis is currently based on behavioral criteria, but magnetic resonance imaging (MRI) of the brain is increasingly used in ADHD research. To date however, MRI studies have provided mixed results in ADHD patients, particularly with respect to the laterality of findings.MethodsWe studied 849 children and adolescents (ages 6–21 y.o.) diagnosed with ADHD (n = 341) and age-matched typically developing (TD) controls with structural brain MRI. We calculated volumetric measures from 34 cortical and 14 non-cortical brain regions per hemisphere, and detailed shape morphometry of subcortical nuclei. Diffusion tensor imaging (DTI) data were collected for a subset of 104 subjects; from these, we calculated mean diffusivity and fractional anisotropy of white matter tracts. Group comparisons were made for within-hemisphere (right/left) and between hemisphere asymmetry indices (AI) for each measure.ResultsDTI mean diffusivity AI group differences were significant in cingulum, inferior and superior longitudinal fasciculus, and cortico-spinal tracts (p < 0.001) with the effect of stimulant treatment tending to reduce these patterns of asymmetry differences. Gray matter volumes were more asymmetric in medication free ADHD individuals compared to TD in twelve cortical regions and two non-cortical volumes studied (p < 0.05). Morphometric analyses revealed that caudate, hippocampus, thalamus, and amygdala were more asymmetric (p < 0.0001) in ADHD individuals compared to TD, and that asymmetry differences were more significant than lateralized comparisons.ConclusionsBrain asymmetry measures allow each individual to serve as their own control, diminishing variability between individuals and when pooling data across sites. Asymmetry group differences were more significant than lateralized comparisons between ADHD and TD subjects across morphometric, volumetric, and DTI comparisons.

Electroencephalographic and Neuroimaging Asymmetry Correlation in Patients with Attention-Deficit Hyperactivity Disorder

“…Shaw et al [ 9 ] found increasing asymmetry in posterior temporooccipital areas due to reduced volume of prefrontal regions, and Dang et al [ 10 ] found structural asymmetry in the caudate nucleus. Douglas et al [ 11 ] reported increased volumetric asymmetry indexes in ADHD, also confirmed by white matter results, particularly in frontoparietal circuitry.…”

A Systematic Review of Imaging Studies in the Combined and Inattentive Subtypes of Attention Deficit Hyperactivity Disorder

“…Although the inclusion of research evidence relating to the effect of medication on structural neuroanatomical substrates are beyond the scope of this review, studies have generally observed smaller ACC and caudate gray matter volumes and deviant cerebellar morphology in treatment naïve relative to treatment experienced in samples of ADHD-C participants and controls (Bussing et al, 2002 ; Semrud-Clikeman et al, 2006 , 2014b ; Bledsoe et al, 2009 ; Villemonteix et al, 2015 ). Similarly, structural asymmetry, i.e., differences in size between left/right brain regions, which has been shown to be a feature in ADHD, was also found to be different in unmedicated vs. medicated patients (Douglas et al, 2018 ). It is likely that the medication disparity between the subtypes could be driving some of the neural findings.…”

“…An example of methodological differences between two studies producing differing results is observed in the Anderson et al (2014) study, which used sophisticated methods, and found the DMN to be associated with the ADHD-I type relative to ADHD-C, ADHD-HI type, and controls, while the DMN was found to be associated with the ADHD-I type relative to ADHD-C, ADHD-HI type, and controls, and was found to distinguish the ADHD-C group from ADHD-I, using the same ADHD-200 dataset in the Fair et al (2012) study. Similarly, other studies using the same dataset were unable to identify neural differences between subtypes (Colby et al, 2012;Douglas et al, 2018). Thus, consideration of the sensitivity of measures to identify biological differences between the ADHD types is warranted as this may bias the results so far in identifying the subtypes.…”

Aberrant gray matter volumes and functional connectivity in adolescent patients with ADHD

“…In 2015, Francx et al used resting‐state functional MRI (rs‐fMRI) and found that symptom recovery in ADHD was related to stronger integration of prefrontal regions in the executive control network . And in 2018, Douglas et al calculated the volumetric measures from 34 cortical and 14 noncortical brain regions per hemisphere, and found that the caudate, hippocampus, thalamus, and amygdala were more asymmetric in ADHD individuals, and that asymmetry differences were more significant than lateralized comparisons . Most of the previous studies analyzed single‐modal MRI, while a more popular research method in recent years has been multimodal fusion .…”