Novel Brain Imaging Approach Improves Understanding of ADHD in Children

A Japanese research team has demonstrated a new, more accurate way to analyze brain imaging data in children with attention deficit/hyperactivity disorder (ADHD), offering fresh insights into the brain structure differences that underlie the condition. The findings, published in Molecular Psychiatry, could pave the way for earlier diagnosis and more effective, personalized treatments for affected children.

Tackling Inconsistencies in ADHD Brain Imaging

ADHD affects more than 5% of children worldwide, leading to difficulties with attention, hyperactivity, and impulsivity. Brain imaging studies using magnetic resonance imaging (MRI) have long sought to uncover the neurological basis of the disorder, but past results have been mixed—some suggesting reduced gray matter volume (GMV) in children with ADHD, others reporting no difference or even increases.

These inconsistencies often stem from small sample sizes and differences in MRI machines across sites. Previous correction methods, such as ComBat harmonization, help reduce site-related bias but risk “overcorrecting,” removing not only measurement errors but also meaningful biological information.

A New Solution: The Traveling-Subject (TS) Method

To overcome these challenges, the researchers applied the traveling-subject (TS) method, which directly accounts for machine-related variation by scanning the same individuals on multiple MRI machines.

In this study, 14 healthy participants were scanned on four different machines over three months to identify measurement biases. This correction model was then applied to an independent dataset from the Child Developmental MRI (CDM) database, which includes MRI data from over 1,000 children. The analyzed sample included 178 typically developing (TD) children and 116 children with ADHD.

Key Findings

TS vs. ComBat: While both methods reduced measurement bias, the TS method preserved biological variability better than ComBat.
Brain structure differences: Using TS-corrected data, researchers found that children with ADHD had smaller volumes in the frontotemporal regions—areas crucial for information processing and emotional regulation.
Clinical potential: These structural differences could serve as neuroimaging biomarkers for early diagnosis and personalized intervention.

“Patients with ADHD displayed smaller brain volumes in regions that are essential for cognitive function and emotional control,” explained Associate Professor Yoshifumi Mizuno of the University of Fukui. “These findings help us better understand why children with ADHD experience such difficulties in daily life.”

Toward Early Detection and Personalized Care

By reliably identifying structural brain patterns linked to ADHD, the TS method could improve early detection and monitoring of treatment outcomes.

“Applying the TS harmonization method allows us to more accurately identify brain structure characteristics in ADHD,” said Assistant Professor Qiulu Shou, who led the study. “In the long term, this approach may improve quality of life for affected children and reduce the risk of secondary psychiatric disorders.”

Original Publication
Authors: Qiulu Shou, Masatoshi Yamashita, Yoshiyuki Hirano, Akiko Yao, Min Li, Yide Wang, Yoko Kato, Tokiko Yoshida, Koji Matsumoto, Tetsuya Tsujikawa, Hidehiko Okazawa, Akemi Tomoda, Kuriko Kagitani-Shimono and Yoshifumi Mizuno.
Journal: Molecular Psychiatry
DOI: 10.1038/s41380-025-03142-6
Method of Research: Imaging analysis
Subject of Research: People
Article Title: Brain structure characteristics in children with attention deficit/hyperactivity disorder elucidated using traveling-subject harmonization
Article Publication Date: 8-Aug-2025
COI Statement: The authors declare no biomedical financial interests or potential conflicts of interest.

Original Source: https://www.u-fukui.ac.jp/en-research/108749/

Frequently Asked Questions

What was the main purpose of the study involving MRI scans of participants?

The study aimed to address measurement bias in MRI scans by comparing data from different machines and ensuring accurate brain structure analysis in participants with ADHD and typically developing children.

How did the researchers correct for measurement bias in the MRI data?

The researchers used two methods, the TS harmonization method and ComBat harmonization, to estimate and correct measurement bias from different MRI machines, ensuring that the brain data was comparable across all participants.

What were the findings regarding the differences in brain structures between children with ADHD and typically developing children?

The study found that after correcting for biases, there were significant differences in brain structures between children with ADHD and typically developing children, indicating that ADHD may be associated with specific structural brain variations.