Schedule of Events | Search Abstracts | Invited Symposia | Symposia | Poster Sessions | Data Blitz

Comparing voxel- and deformation-based morphometry in pediatric ADHD

Poster Session C - Sunday, March 8, 2026, 5:00 – 7:00 pm PDT, Fairview/Kitsilano Ballroom

Connor Watkinson¹ (), Michelle Y. Kibby¹; ¹Southern Illinois University Carbondale

Properly quantifying and interpreting brain morphometry in structural neuroimaging studies is challenging and may yield inconsistent findings due to varying methodological approaches and their underlying assumptions. However, by utilizing and comparing complementary approaches, we may be able to improve the accuracy and interpretability of these results (Goto et al., 2022). This study compared three morphometric methods—gray matter (GM) voxel-based morphometry (VBM), white matter (WM) VBM, and deformation-based morphometry (DBM)—for detecting structural differences in pediatric ADHD to better understand how combining methodological approaches may improve interpretability of findings and prevent processing errors. DBM represents volume changes through deformation fields, while tissue-specific VBM analyses decompose these changes into GM and WM contributions. T1-weighted MRI images from 106 children (58 ADHD, 48 controls; 8–13 years; 49.1% female) were segmented, registered, modulated, and smoothed at 6mm using CAT12. Statistical analyses involved threshold-free cluster enhanced multiple regression contrasts with age, sex, image quality, and total intracranial volume as covariates. Whole-brain analyses revealed focal reductions in ADHD across GM-VBM and DBM in temporal, frontal, and insular regions. ROI analyses showed GM reductions in bilateral temporal and orbitofrontal cortices, with the right superior temporal gyrus surviving correction. WM analyses revealed complex patterns with bilateral orbitofrontal and temporal reductions but occipital increases in ADHD. Visual and quantitative comparison demonstrates how DBM captures overall structural changes independent of tissue classification, while VBM reveals which tissues drive these effects, highlighting the nuance involved in properly interpreting morphological differences through automated segmentation and the importance of multi-method analysis.

Topic Area: METHODS: Neuroimaging