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Updated: May 16, 2026

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
Published on: January 7, 2019
Association between iron content and gray matter missegmentation with voxel-based morphometry in basal ganglia
Masami Goto1, Osamu Abe, Tosiaki Miyati
1Department of Radiological Technology, University of Tokyo Hospital, Bunkyo-ku, Tokyo, Japan; Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan.
Purpose:
To show an association between T2-weighted signal intensity (T2-SI) variation and missegmentation in the putamen of healthy adults, using 3.0-tesla magnetic resonance scanner and voxel-based morphomery (VBM).
Materials And Methods:
Contiguous sagittal T1-weighted images and axial T2-weighted images of the brain were obtained from 1380 healthy participants using a 3.0 Tesla (T) MR scanner. After image preprocessing with Statistical Parametric Mapping 5, the association between T2-SI ratio (= A/B, where A is the mean of the T2-SI in the putamen, and B is that in the thalamus) variation and gray matter missegmentation was assessed using VBM.
Results:
A significant positive correlation was revealed between T2-SI ratio and bilateral putamen volume on the gray matter images. In addition, we found a significant negative correlation between T2-SI ratio and bilateral putamen volume on the white matter images. We consider that these results show the influence of missegmentation.
Conclusion:
To the best of our knowledge, this is the first VBM study to demonstrate an association between T2-SI variation and gray matter missegmentation. These results indicate the possibility that VBM may be more affected by individual differences in iron content levels than by individual differences in tissue volumes if detected-regions with VBM contained substantial iron deposition.
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