Abnormal cerebral cortex structure in children with ADHD

Abstract

Objective: Examination of cerebral cortical structure in children with Attention-Deficit/ Hyperactivity Disorder (ADHD) has thus far been principally limited to volume measures. In the current study, an automated surface-based analysis technique was used to examine the ADHD-associated differences in additional morphologic features of cerebral cortical gray matter structure, including surface area, thickness, and cortical folding. Methods: MPRAGE images were acquired from 21 children with ADHD (9 girls) and 35 typically developing controls (15 girls), aged 8-12 years. Statistical difference maps were used to compare mean cortical thickness between groups along the cortical surface. Cortical volume, surface area, mean thickness, and cortical folding were measured within regions of interest, including the right/left hemispheres, frontal, temporal, parietal, and occipital lobes within each hemisphere, and sub-lobar regions. Results: Children with ADHD showed a decrease in total cerebral volume and total cortical volume of over 7 and 8%, respectively; volume reduction was observed throughout the cortex, with significant reduction in all four lobes bilaterally. The ADHD group also showed a decrease in surface area of over 7% bilaterally, and a significant decrease in cortical folding bilaterally. No significant differences in cortical thickness were detected. Conclusions: Results from the present study reveal that ADHD is associated with decreased cortical volume, surface area, and folding throughout the cerebral cortex. The findings suggest that decreased cortical folding is a key morphologic feature associated with ADHD. This would be consistent with onset early in neural development and could help to identify neurodevelopmental mechanisms that contribute to ADHD. Hum Brain Mapp 30:175-184, 2009. V V C 2007 Wiley-Liss, Inc.

Attention-Deficit/Hyperactivity Disorder and Attention Networks

“…However, cortical thickness results have not always been consonant. Wolosin et al (2009), although finding that children with ADHD displayed expected overall decreases of total cerebral and cortical volumes, and a significant decrease in cortical folding bilaterally, did not detect significant differences in cortical thickness between ADHD and healthy children.…”

Clinical Motor and Cognitive Neurobehavioral Relationships in the Basal Ganglia

“…The right hemisphere could promote the indirect pathway function by selectively enhancing or stimulating the D2 receptors in these same areas. Since many of the hyperkinetic disorders like ADHD, Tourette's and OCD have all been associated with a decreased function of the right hemisphere and an increased function of left hemisphere activity [24,33,34] that would also seem to fit with the argument that a decrease in right hemisphere function would be associated with an increase in left hemisphere function and enhancement of the direct pathway and the D1 receptor promoting hyperkinetic movement and behaviors.…”

Automated MRI Parcellation of the Frontal Lobe

“…The groups differed on diagnosis (X 2 =19.893, p<0.001) and total cerebral volume (TCV) (F=4.052, p=0.047), with the atlas group having no ADHD or ASD subjects and larger TCV than the analysis group. The group difference in TCV is in part due to the differing number of ADHD subjects, who have previously been shown to have lower TCV by 6-7% in this age range (Ranta, et al 2009;Wolosin, et al 2007). …”

“…Important contributions to the study of neuropsychiatric disorders have been made with MR automated parcellation studies since their introduction, notably in Alzheimer disease (Desikan, et al 2009;Desikan, et al 2010;Oliveira, et al 2010;Scheinin, et al 2009;Westman, et al 2011), schizophrenia (Kikinis, et al 2010;Kuperberg, et al 2003;Nesvag, et al 2008;Voets, et al 2008), depression (Bergouignan, et al 2009;Dotson, et al 2009;Nifosi, et al 2010), Parkinson disease (Tinaz, et al 2010), ADHD (Almeida, et al 2010;Wolosin, et al 2007), autism (Ecker, et al 2010;Hadjikhani, et al 2006), and bipolar disorder (Nery, et al 2009). Continuing debate on the best methods for evaluating the relative reliability, sensitivity and validity of manual versus automated parcellations exists.…”