Publications by authors named "W Uchida"
The aging process induces a variety of changes in the brain detectable by magnetic resonance imaging (MRI). These changes include alterations in brain volume, fluid-attenuated inversion recovery (FLAIR) white matter hyperintense lesions, and variations in tissue properties such as relaxivity, myelin, iron content, neurite density, and other microstructures. Each MRI technique offers unique insights into the structural and compositional changes occurring in the brain due to normal aging or neurodegenerative diseases.
View Article and Find Full Text PDFThis study included 52 Japanese older adults with Pittsburgh Sleep Quality Index (PSQI) scores > 5 and 52 healthy controls (HCs) with PSQI score ≤ 5. Diffusion-weighted imaging (DWI) and 3D T1-weighted imaging were acquired using 3T magnetic resonance imaging. The diffusion tensor image analysis along the perivascular space (DTI-ALPS) index was calculated using preprocessed DWI.
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- * A study compared 50 poor sleepers and 50 good sleepers, revealing that poor sleepers had significantly lower myelin volume in key brain regions, which correlated with decreased cognitive function and increased depression.
- * The findings suggest that circadian clock gene expression plays a role in these differences, with certain genes linked to regional variations in myelin content and overall brain health in relation to sleep quality.
Article Synopsis
- The study assessed the repeatability of T1 and T2* relaxation times and quantitative susceptibility (χ) values using quantitative parameter mapping (QPM) across three different 3T MRI scanners at three sites.
- Twelve healthy volunteers underwent three separate scans at each site, and various statistical analyses were used to measure consistency and variation.
- Results showed high intra-site repeatability for all measured values (T1, T2*, and χ) and acceptable cross-site reproducibility, suggesting QPM can reliably support multisite studies in MRI research.
Article Synopsis
- A new deep learning-based method for brain segmentation (DLHBS) has been developed to accurately segment T1-weighted MRI scans into 107 brain subregions and calculate their volumes.
- The method was trained on data from 486 subjects and tested for consistency in volume measurements using scans from 11 healthy subjects across three MRI scanners.
- Results indicated that DLHBS outperformed traditional segmentation tools like SPM and FreeSurfer in terms of both repeatability and reproducibility for multiple brain regions.