A brief review of MRI studies in patients with attention-deficit/hyperactivity disorder and future perspectives
Yoshifumi Mizuno1, Masatoshi Yamashita2, Qiulu Shou2
1Research Centre for Child Mental Development, University of Fukui, Fukui, Japan; Division of Developmental Higher Brain Functions, United Graduate School of Child Development, University of Fukui, Fukui, Japan; Department of Child and Adolescent Psychological Medicine, University of Fukui Hospital, Fukui, Japan.
Abstract:
Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder characterized by persistent inattention, hyperactivity, and/or impulsivity that significantly affects academic, occupational, and social functioning. This review summarizes key findings of structural and functional magnetic resonance imaging (MRI) studies investigating the neural underpinnings of ADHD, focusing on T1-weighted structural MRI, diffusion tensor imaging (DTI), task-based functional MRI (task fMRI), and resting-state functional MRI (rs-fMRI). T1-weighted structural MRI studies have revealed reduced gray matter volume in regions implicated in executive function, particularly the frontal cortex, basal ganglia, and cerebellum, along with evidence of delayed cortical maturation. DTI findings highlighted abnormalities in white matter integrity, particularly in the fronto-striatal-cerebellar circuits and connections between the corpus callosum and cingulum. Task fMRI studies have demonstrated reduced activation of brain networks involved in cognitive control, timing, and reward processing, including fronto-striatal and fronto-parietal networks. Furthermore, rs-fMRI research has shown altered connectivity patterns within and between key brain networks, including the default mode, fronto-parietal, and salience networks. Despite these insights, inconsistencies across studies underscore the need for larger and more standardized research efforts. Future research should employ multimodal imaging techniques and advanced analytical methods such as machine learning to better subtype ADHD and customize interventions. Moreover, establishing harmonized imaging protocols across institutions, as exemplified by innovative strategies, such as the traveling-subject method, is crucial for mitigating intersite variability. Through collaborative efforts, neuroimaging studies in ADHD are anticipated to enhance our understanding of the disorder's heterogeneity while informing the development of precise clinical diagnoses and personalized therapeutic interventions.
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