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A Brain Morphometry Study with Across-Site Harmonization Using a ComBat-Generalized Additive Model in Children and
Tadashi Shiohama1,2, Norihide Maikusa3,4, Masahiro Kawaguchi5
1Department of Pediatrics, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chuo-ku, Chiba-shi 260-8677, Chiba, Japan.
Diagnostics (Basel, Switzerland)
|September 9, 2023
Summary
This study provides crucial across-site normal reference values for brain volumes in children and adolescents. These quantitative brain morphometry data aid in understanding neurodevelopment and diagnosing rare diseases.
Area of Science:
- Neuroscience
- Developmental Neuroscience
- Medical Imaging
Background:
- Brain structure and function are linked across development.
- Quantitative brain morphometry is vital for neuroscience research.
- Multicenter studies require harmonized data to control for scanner effects, especially for rare diseases lacking normative data.
Purpose of the Study:
- To establish sex- and age-specific, harmonized, across-site normal reference values for global and regional brain volumes in children and adolescents.
- To facilitate accurate brain morphometric analysis in multicenter studies and clinical settings.
- To support the investigation of brain morphology in rare and ultra-rare neurological conditions.
Main Methods:
- Collected magnetic resonance imaging (MRI) data from 846 neurotypical participants (ages 6.0-17.9 years) across five institutions.
- Utilized the CIVET 2.1.0 pipeline for regional brain volume analysis.
- Applied ComBat-GAM harmonization to combine and standardize measurements across sites.
Main Results:
- Generated normative reference values for global and regional brain volumes stratified by sex and age group.
- Provided lateral indices for detailed brain morphology assessment.
- Successfully harmonized data from multiple institutions to create a unified reference dataset.
Conclusions:
- The derived normal reference values are valuable for assessing individual brain morphology in clinical practice.
- This dataset serves as a critical resource for research on neurodevelopmental trajectories.
- The study addresses the need for standardized, multicenter brain morphometry data, particularly for rare disease research.

