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Establishing the Net Attainable Benefits of Long-term Exercise-LV (ENABLE-LV): volumetric brain imaging

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DataCite Commons2023-10-10 更新2024-07-13 收录
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https://dataverse.rsu.lv/citation?persistentId=doi:10.48510/FK2/JCFJZL
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This dataset includes volumetric and DTI measures and sociodemographic data from a sample of 68 older adults without diagnosis of dementia. Images were obtained using a Siemens 1.5 Tesla Avanto MRI scanner (Siemens, Germany). High-resolution anatomical images were acquired using a three-dimensional T1-weighted magnetization prepared rapid acquisition gradient echo (MPRAGE) sequence [TR = 1160 ms; TE= 4.44 ms; inversion recovery time (TI) = 600 ms; field of view (FOV), 230 x 230 mm2; matrix size, 256 x 256; flip angle θ = 15 degrees; voxel dimensions, 0.9 x 0.9 x 0.9 mm3; acquisition time, 5 min]. Visual rating scales (Global Cognitive Atrophy scale (GCA), Medial Temporal Atrophy scale (MTA scale), Parietal Atrophy scale (PAS Scale), Weighted Atrophy scale (WAS Scale), Entorhinal Cortex Atrophy (ERICA) & Frontotemporal Atrophy scale (FTAS scale)) were used to grade the level of brain atrophy. Volumetric analysis was conducted using Freesurfer 7.2. software. For cortical mapping, Desikan-Killiany-Tourville (DKT) Atlas was applied. Diffuse tensor imaging (DTI) data included fractional anisotropy (FA) and mean diffusivity (MD) calculations. For each participant Eddy correction using the eddy correct function FSL was used. Data were fitted to a diffusion tensor model using dtfit FSL, thus obtaining maps for MD and FA. The b = 0 was non-linearly warped into 2-mm MNI space using ANTS (version 2.1.) using symmetric diffeomorphic mapping. This process generates the diffeomorphic transformation required to warp each of the parameter maps to standard MNI space. The data were obtained from one sample using a cross-sectional design (different older adults at the same point in time).
提供机构:
Rīga Stradiņš University Institutional Repository Dataverse
创建时间:
2023-10-10
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